WO2024103232A1 - 配电网仿真方法、系统、设备和计算机可读存储介质 - Google Patents
配电网仿真方法、系统、设备和计算机可读存储介质 Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote monitoring or remote control of equipment in a power distribution network
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for AC mains or AC distribution networks
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- the present invention relates to the technical field of power system simulation, and in particular to a distribution network simulation method, system, device and computer-readable storage medium.
- the new power system has the characteristics of cyber-physical systems (CPS), and involves multiple disciplines such as power systems, computing science, network communications, and control theory.
- CPS cyber-physical systems
- the increasingly complex network system has brought severe challenges to the perception, analysis, decision-making, and control of traditional power systems.
- the research on traditional power systems and information systems is separated in theory and methods.
- the physical power system is continuously changing, and its electrical quantities flow through power nodes and branches in the form of currents; the information communication system is a discrete system, and its information changes are triggered and driven by discrete time.
- the distribution network information-physical system fusion modeling method in related technologies takes the effect of communication information as input into the physical process for modeling and control, focusing on adding information elements to traditional physical models. It does not fully consider the interactive impact of information communication on the physical system, which reduces the adaptability of the distribution network information-physical system.
- Embodiments of the present invention provide a distribution network simulation method, system, device and computer-readable storage medium, which improve the adaptability of the distribution network information-physical system.
- an embodiment of the present invention provides a distribution network simulation method, the method comprising: performing multi-level and multi-scale platform architecture modeling according to the model differences, interactive influences, and scale and accuracy of multi-scenario simulation verification between the information system and the physical system in the distribution network to obtain a simulation platform architecture; on the simulation platform architecture, performing fusion modeling of the information-physical simulation system under time-varying information and uncertain conditions according to the coupling characteristics between the physical system and the information system in the distribution network to obtain the information-physical system of the distribution network; based on the simulation platform architecture, performing real-time simulation of the information-physical system of the distribution network in the scenario of concurrent failure of the physical system, the communication network and the information system to determine the fault simulation result of the distribution network; the fault simulation result is used to provide support for the fault isolation decision and fault recovery decision of the information-physical system of the distribution network; based on the simulation platform architecture, performing reliability simulation evaluation on the information-physical system of the distribution network using reliability evaluation indicators to determine the reliability simulation result of the distribution network.
- an embodiment of the present invention provides a distribution network simulation system, the system comprising: a platform building part, configured to perform multi-level and multi-scale platform architecture modeling according to the model differences, interactive influences, and scale and accuracy of multi-scenario simulation verification between the information system and the physical system in the distribution network, to obtain a simulation platform architecture; a fusion part, configured to perform fusion modeling of the information-physical simulation system under time-varying information and uncertain conditions on the simulation platform architecture according to the coupling characteristics between the physical system and the information system in the distribution network, to obtain the information-physical system of the distribution network; a fault simulation part, configured to perform real-time simulation of the information-physical system of the distribution network under concurrent fault scenarios of the physical system, the communication network and the information system based on the simulation platform architecture, to determine the fault simulation result of the distribution network; the fault simulation result is used to provide support for the fault isolation decision and fault recovery decision of the information-physical system of the distribution network; a reliability simulation part, configured to perform reliability simulation evaluation of the information-physical system
- an embodiment of the present invention provides a distribution network simulation device, the device comprising: a memory configured to store an executable computer program; and a processor configured to implement the above-mentioned distribution network simulation method when executing the executable computer program stored in the memory.
- an embodiment of the present invention provides a computer-readable storage medium storing a computer program, which is configured to implement the above-mentioned distribution network simulation method when executed by a processor.
- the embodiment of the present invention provides a distribution network simulation method, system, device and computer-readable storage medium.
- a multi-level and multi-scale platform architecture modeling is performed to obtain a simulation platform architecture, and the flexible loading function, real-time synchronous communication function and function construction function of the simulation platform are added, so that the event-driven and continuous time response distribution network information physical system collaborative simulation can be realized.
- the information physical simulation system under time-varying information and non-deterministic conditions is integrated and modeled to obtain the distribution network information physical system. Through the model construction under multiple scenarios, multiple resolutions and multiple response time scales, the diversity of the distribution network information physical system is improved.
- the distribution network information physical system is simulated in real time under the concurrent fault scenario of the physical system, the communication network and the information system to determine the fault simulation result of the distribution network; the fault simulation result is used to provide support for the fault isolation decision and fault recovery decision of the distribution network information physical system, meeting the needs of multi-scenario simulation analysis of the distribution network information physical system.
- reliability assessment indicators are used to conduct reliability simulation assessment on the information-physical system of the distribution network, and the reliability simulation results of the distribution network are determined, which provides theoretical support and decision-making assistance for improving the reliability of the distribution network, maintains the stable and reliable operation of the distribution network, and improves the adaptability of the information-physical system of the distribution network.
- FIG1 is a flowchart of optional steps of a distribution network simulation method provided by an embodiment of the present invention.
- FIG2 is an optional flow chart of equivalent modeling of a distribution hybrid network based on a dynamic phasor method provided by an embodiment of the present invention
- FIG3 is an optional schematic diagram of a firewall model Petri net model provided by an embodiment of the present invention.
- FIG4 is an optional schematic diagram of a cryptographic model provided in an embodiment of the present invention.
- FIG5 is an optional schematic diagram of a forged identity authentication attack process model provided by an embodiment of the present invention.
- FIG6 is an optional schematic diagram of a port management Petri net model provided in an embodiment of the present invention.
- FIG. 7 is an optional schematic diagram of a false data injection attack information network Petri net model provided by an embodiment of the present invention.
- FIG8 is an optional schematic diagram of a Petri net model of an attack process including a false closing and closing command provided by an embodiment of the present invention
- FIG9 is an optional flow chart of a distribution network cyber-physical system fusion modeling provided by an embodiment of the present invention.
- FIG10 is an optional schematic diagram of the overall architecture of a power distribution network cyber-physical simulation platform provided by an embodiment of the present invention.
- FIG11 is an optional schematic diagram of classification of fast/medium/slow dynamic components of a power distribution network cyber-physical system provided by an embodiment of the present invention.
- FIG12 is an optional schematic diagram of a decomposition optimization model provided by an embodiment of the present invention.
- FIG13 is an optional schematic diagram of network decoupling of a power distribution network cyber-physical system provided by an embodiment of the present invention.
- FIG14a is an optional schematic diagram of an equivalent model between a component and a network provided by an embodiment of the present invention.
- FIG14b is an optional schematic diagram of another equivalent model between components and networks provided in an embodiment of the present invention.
- FIG15 is an optional schematic diagram of a simulation data update mode based on interpolation method provided by an embodiment of the present invention.
- FIG16a is an optional schematic diagram of multi-time scale information interaction provided by an embodiment of the present invention.
- FIG16b is an optional schematic diagram of another multi-time scale information interaction provided by an embodiment of the present invention.
- FIG17 is an optional schematic diagram of a data interaction module with adaptive step size adjustment provided by an embodiment of the present invention.
- FIG18 is an optional schematic diagram of a maximum simulation step length calculation provided by an embodiment of the present invention.
- FIG19 is an optional schematic diagram of a simulation step size adaptation mechanism provided by an embodiment of the present invention.
- FIG20 is an optional schematic diagram of an example analysis of a power distribution network cyber-physical simulation provided by an embodiment of the present invention.
- FIG21 is an optional flow chart of reliability analysis and evaluation of a distribution network cyber-physical system based on a Monte Carlo method provided by an embodiment of the present invention
- FIG22a is an optional block diagram of reliability of a series unit provided by an embodiment of the present invention.
- FIG22b is an optional block diagram of a parallel unit reliability provided by an embodiment of the present invention.
- FIG22c is an optional block diagram of a voting unit reliability provided by an embodiment of the present invention.
- FIG23 is a schematic diagram of an optional structure of a distribution network simulation system provided by an embodiment of the present invention.
- FIG. 24 is a schematic diagram of the composition structure of a distribution network simulation device provided in an embodiment of the present invention.
- the power information-physical system needs to study how to deeply integrate the power system and the information system, explore the interaction mechanism, study the modeling, analysis and control methods that are suitable for it, and guide the application of the actual power system.
- the model of the power information-physical system can be constructed according to the prototype characteristics to support related calculations and simulations, thereby achieving the purpose of assisting, testing, and verifying the research on related theoretical and application problems, and accurately constructing a model library containing commonly used components, equipment, systems, event flows, information flows, interfaces, etc. on the information side and the physical side, and establishing an information fusion simulation method that is compatible with the discrete time-step simulation system of the power system and the event queue simulation system of the information communication system.
- the power system can include transmission network and distribution network.
- the distribution network is closer to the user.
- the distribution network has more obvious characteristics of complex and changeable topology, large node scale, source and load volatility, and strong randomness.
- the number of measurement points, measurement data volume, communication data volume, and control instruction data volume in the distribution network have all shown exponential growth. Therefore, it is necessary to study the degree of information-physical integration of the distribution system.
- the fusion modeling method of the information-physical system of the distribution network can be developed from the following three aspects: (1) Taking the effect of communication information as an input quantity for modeling and control in the physical process, focusing on adding information elements to the traditional physical model, but this idea fails to fully consider the impact of information communication on the physical system. (2) Analysis and control of the information-physical interaction process, focusing on modeling, analysis and control of the interaction between discrete information processes and continuous physical processes in the closed-loop control process. This method focuses more on the description of the information mapping relationship, but lacks research on the influence of the information side on the physical side. The propagation process and the impact results. (3) Modeling and analysis of the information-physical coupling process, focusing on the modeling, quantitative analysis and control of the information-physical coupling characteristics (including paths and performance). However, the current research methods in this area are mostly targeted at business, and the modeling and analysis methods have not formed a complete framework system, and the adaptability is insufficient.
- Joint simulation The idea of the joint simulation solution is to establish a complex power and information and communication composite system model in a single simulation tool (power system simulation tool or communication system simulation tool).
- Non-real-time hybrid simulation Another solution for simulating power and communication composite systems is to use hybrid simulation. The modeling of the two systems is still completed using their respective professional simulation software, and the time synchronization method is used to enable the two software to run in the same time domain. This is also the current research direction of the simulation platform for power and information communication composite systems.
- An embodiment of the present invention provides a distribution network simulation method, as shown in FIG1, which is a flow chart of the steps of a distribution network simulation method provided by an embodiment of the present invention.
- the method is a distribution network simulation method with deep information-physics fusion, which is applied to devices and systems for power distribution or power consumption.
- the distribution network simulation method includes the following steps:
- a multi-level, multi-scale comprehensive simulation platform architecture that maps the actual power grid information-physical system is proposed, which provides technical support for scenarios such as fault analysis and reliability assessment of distribution network information-physical systems.
- the information-physical simulation system under time-varying information and uncertain conditions is integrated and modeled to obtain the distribution network information-physical system.
- a finite state machine-based distribution hybrid network information-physical fusion modeling technology and a multi-resolution and multi-level flexible model construction method of interactive elements are proposed for the physical system, forming a simulation model library supporting the operation of distribution networks of different modes; for the communication network, a communication network physical layer and data link layer model, an extensible communication application layer model, a key event flow and information flow process model construction method are proposed to support the interaction of physical information systems, forming a cross-application and cross-node data flow model library supporting multiple typical protocols; for the information system, an information system model covering network protection units and network attack paths is constructed.
- the construction of the information-physical model of the distribution network under time-varying information and non-deterministic conditions is realized, which has the characteristics of good flexibility, high precision and strong adaptability, and can provide multi-time and space scale model support for advanced applications of distribution network simulation systems with deep information-physics integration.
- the information-physical system of the distribution network is simulated in real time to determine the fault simulation results of the distribution network; the fault simulation results are used to provide support for the fault isolation decision and fault recovery decision of the information-physical system of the distribution network.
- reliability assessment indicators are used to perform reliability simulation assessment on the information-physical system of the distribution network to determine the reliability simulation results of the distribution network.
- simulation decomposition and coordination technology in response to the urgent need for multi-scenario simulation analysis based on information-physical systems, based on the constructed distribution network information-physical system model and the designed simulation platform architecture, simulation decomposition and coordination technology, multi-rate real-time simulation method and calculation speed dynamic adjustment method are adopted, and a real-time simulation method for physical nodes of distribution network under concurrent fault scenarios of physical systems, communication networks and information systems is proposed, providing technical and auxiliary decision-making support for fault isolation and fault recovery of distribution network information-physical systems; reliability evaluation indicators of distribution network physical systems and information systems are constructed, and a reliability simulation analysis method for distribution network information-physical systems is proposed, realizing accurate quantitative analysis and improvement of system reliability.
- the embodiment of the present invention is oriented to the new power system, and proposes a distribution network information-physical deep fusion simulation system that integrates functions such as information-physical fusion modeling, simulation platform architecture construction, fault simulation and reliability simulation.
- the information-physical fusion modeling of the distribution network under time-varying information and uncertain conditions is realized; considering the model differences and interaction delays between the information system and the physical system of the distribution network, the construction of a multi-level and multi-scale comprehensive simulation platform for the information-physical system of the distribution network is realized; through the simulation of the physical nodes of the distribution network under the concurrent fault scenarios of the physical system, communication network and information system, technical and auxiliary decision-making support is provided for the fault isolation and fault recovery of the information-physical system of the distribution network; through the reliability simulation and evaluation of the information-physical system of the distribution network, accurate quantitative analysis and improvement of system reliability are realized.
- a multi-level and multi-scale platform architecture modeling is performed to obtain a simulation platform architecture, which increases the flexible loading function, real-time synchronous communication function and function construction function of the simulation platform, and can realize the event-driven and continuous time response distribution network information physical system collaborative simulation.
- the simulation platform architecture according to the coupling characteristics between the physical system and the information system in the distribution network, the information physical simulation system under time-varying information and non-deterministic conditions is integrated and modeled to obtain the distribution network information physical system.
- the distribution network information physical system is simulated in real time under the concurrent fault scenario of the physical system, communication network and information system to determine the fault simulation result of the distribution network; the fault simulation result is used to provide support for the fault isolation decision and fault recovery decision of the distribution network information physical system, meeting the needs of multi-scenario simulation analysis of the distribution network information physical system.
- reliability assessment indicators are used to conduct reliability simulation assessment on the information-physical system of the distribution network, and the reliability simulation results of the distribution network are determined. This provides theoretical support and decision-making assistance for improving the reliability of the distribution network, maintains the stable and reliable operation of the distribution network, and improves the adaptability of the information-physical system of the distribution network.
- S102 in FIG. 1 above may also include S1021 - S1025 .
- the simulation model library supporting the operation of distribution networks of different modes in the above S1021 can be implemented in the following ways: a distribution hybrid network information-physical fusion modeling method based on a finite state machine and a multi-resolution and multi-level flexible model construction method of physical side interactive elements to form a simulation model library supporting the operation of distribution networks of different modes.
- the physical system model includes a dynamic equivalent model of the distribution network, a multi-resolution and multi-level flexible model of physical-side interactive elements, and a simulation model library supporting the operation of distribution networks in different modes, which are described below respectively.
- FIG. 2 is an optional flow chart of a distribution hybrid network equivalent modeling based on the dynamic phasor method provided by an embodiment of the present invention, and the steps of the modeling method include S11-S18.
- the current dynamic phasor value of the voltage-current equation at the previous moment and the known voltage at this moment are known, and the dynamic phasor values of each order of the node voltage are calculated respectively through the reduced-order dynamic phasor equation.
- the multi-resolution and multi-level flexible model of the physical-side interactive element includes a high-resolution model and a low-resolution model of the interactive element.
- the high-resolution modeling of the interactive element can adopt the state space method, which includes a simulation model established based on the physical laws of the object operation and a digital model established based on the measured input and output data of the object.
- the low-resolution modeling of the interactive element can adopt the switching cycle average modeling method, which is to establish a switch model for the modeling object, and then average the switch model in a switching cycle to obtain it.
- a simulation model library supporting the operation of distribution networks of different modes can be constructed based on a dynamic equivalent modeling method of a distribution network hybrid network and a multi-resolution and multi-level flexible modeling technology, and the model library index is as follows: (1)
- the first-level directory of the model library can include distribution network equipment models, load models, power electronic equipment models, and distributed power supply models.
- the second-level directory under the distribution network equipment model can include models of typical equipment in the distribution network, such as lines, transformers, circuit breakers, fuses, towers/supports, section switches, disconnectors, intelligent terminals, lightning arresters, mutual inductors, and motors.
- the second-level directory under the load model can include models of common loads in the distribution network, such as constant impedance loads, constant power loads, constant current models, and polynomial models.
- the second-level directory of power electronic equipment models can include models of typical power electronic conversion equipment, such as rectifiers, inverters, choppers, and AC-AC converters.
- the second-level directory of distributed power supply models can include models of commonly used distributed power supplies in existing distribution networks, such as photovoltaic power generation, wind power generation, small hydropower, gas turbines, energy storage equipment, constant power supply, and V/F controlled power supply.
- the cross-application and cross-node data flow model library supporting multiple typical protocols in the above S1022 can be implemented in the following way: according to the construction method of the communication network physical layer model and data link layer model, the communication application layer model, the key event flow and the information flow process model used to support the interaction of physical information systems, a cross-application and cross-node data flow model library supporting multiple typical protocols is formed.
- the communication network model includes a communication network physical layer and data link layer model that supports the interaction of physical information systems, an extensible communication application layer model, a key event flow and information flow process model, and a cross-application, cross-node data flow model library that supports multiple typical protocols, which are explained below respectively.
- the communication network physical layer model includes a synchronous digital hierarchy (SDH) network physical layer model and a wireless private network physical layer model.
- SDH network physical layer model can be derived based on the existing channel model in the network simulation technology software package (for example, OPNET).
- the wireless private network physical layer model can be constructed based on the OPNET software and can include nine stages: receiver group calculation stage; transmission delay stage; link closure calculation stage; transmission antenna gain stage; propagation delay stage; receiving antenna gain stage; receiving power calculation stage; background noise power calculation stage; interference noise power calculation stage.
- the data link layer modeling is constructed based on OPNET software and may include five stages: link matching stage; signal-to-noise ratio calculation stage; bit error rate calculation stage; bit error number allocation stage; and error correction stage.
- the steps of constructing the extensible communication application layer model include: custom task modeling, application model setting and role setting.
- the steps for constructing the key event flow and information flow process model of the distribution network information-physical system include: building a DDOS scenario, configuring attack profiles, configuring effect scripts, configuring remedial action profiles, setting statistics and running simulation.
- a cross-application and cross-node data flow model library supporting multiple typical communication protocols is developed based on OPNET software, and its steps may include: modifying software in the loop (SITL) module code, building control nodes, modifying terminal node models and defining data packet structures.
- SQL software in the loop
- the information system model includes multi-source information preprocessing of the information-physical system of the distribution network and an information network security model.
- the multi-source information preprocessing includes sensor data preprocessing, network data preprocessing and multi-state information control model construction. Both sensor data preprocessing and network data preprocessing include abnormal data detection and abnormal data correction.
- the multi-state information control model can be expressed by a multi-state Markov model, which can include the following steps: determining the statistical model of each single state; establishing a mobile communication channel Markov model.
- the Markov model of the mobile communication channel can be described as a transfer matrix P and a state vector S.
- the Markov transfer matrix of the n-state is shown in formula (1).
- pij represents the transition probability from state i to state j and satisfies formula (2).
- the state vector S [s 1 , s 2 , ..., sn ], since the Markov chain is non-periodic and irreducible at this time, its steady-state distribution exists and is equal to the limiting distribution, and formula (3) can be obtained.
- the steady-state distribution means that the product between the state vector S and the transfer matrix P is equal to the state vector S.
- the network security model includes a network protection unit model and a network attack path model.
- the network protection unit model is constructed based on Petri nets, including a firewall model, a password model, an authentication model and a network device configuration management model, which are described below.
- FIG3 is an optional schematic diagram of a firewall model Petri net model provided by an embodiment of the present invention, and FIG3 shows intrusion attempts in various ways.
- Each instantaneous transition of the model is attached with a firewall penetration probability, and its value can be calculated from the firewall log.
- the probability of a malicious packet passing through the firewall via each rule can be calculated by formula (4).
- the above formula (4) is the malicious packet that passes through the firewall i through policy rule j (i.e., the malicious packet that passes through the firewall in Figure 3), where Indicates the frequency of passing through the firewall. is the total number of records for firewall rule j. fi fr is the number of rejected packets, Is the total number of firewall records. Firewall execution speed The average response speed is the number of instructions executed per second, which can be used to estimate the time to verify rules and pass the firewall. Depends on network transmission conditions.
- FIG4 is an optional schematic diagram of a password model provided in an embodiment of the present invention.
- the intrusion attempt can be represented by a transition probability, which can be described by the following formula (5).
- fipw is the number of intrusion attempts. Calculated for the total number of records. A successful login within a specific time interval is not counted as an intrusion attempt.
- An authentication model is established by taking USB key information (key) as encryption hardware as an example.
- a typical process of identity authentication encrypted by USB key hardware is as follows: During the initialization phase, the server and the terminal user share the hardware storing the key in a secure manner; during operation, when performing identity authentication, the server generates a random number and sends it to the terminal, and the terminal performs a hash operation and sends the result back to the server; the server performs a hash operation on the stored key and random number and compares them with the received result. If the results are consistent, the authentication is passed.
- FIG5 is an optional schematic diagram of a forged identity authentication attack process model provided by the embodiment of the present invention.
- ⁇ s in FIG5 represents the time required to steal a USB key hardware already in use in a system by various means
- ⁇ c represents the time required to copy a new USB key hardware
- ⁇ f represents the cycle of the system replacing the USB key hardware.
- ⁇ r represents the time required to successfully obtain a random number sent by a server
- ⁇ a represents the time required for the server to verify the information sent back by the terminal.
- FIG. 6 is an optional schematic diagram of a port management Petri net model provided by the embodiment of the present invention.
- p v represents the probability that the idle port is not closed
- p t represents the probability that the normal working port usage permission is obtained and the malicious attack packet can be sent through the normal port
- p f represents the probability that the port management mechanism has no loopholes that are exploited by the attacker.
- network attack path modeling includes false information injection attack modeling and forged instruction attack modeling.
- the false data injection attack model is shown in Figure 7, which is an optional schematic diagram of a false data injection attack information network Petri net model provided by an embodiment of the present invention.
- the Petri net models of these protective devices are connected in series to obtain a Petri model of the false data injection attack propagation process.
- the forged instruction attack model is shown in Figure 8, which is an optional schematic diagram of an attack process Petri net model containing a false switch-on and switch-off command provided by an embodiment of the present invention.
- the forged instruction attack process may include: obtaining the ciphertext of the switch-off command; establishing communication with the meter, obtaining the access network cable at the meter through a wireless network, etc.; issuing a command message.
- system fusion modeling is performed to obtain a fusion system.
- the information-physical system fusion modeling includes system fusion modeling based on the association matrix and information-physical system modeling based on the finite state machine, which are described separately below.
- the information-physical system fusion modeling based on the association matrix can be achieved in the following ways.
- the physical matrix P, the communication network matrix C, the secondary equipment network matrix S, the information control matrix I, and the association matrix between them are integrated to construct a distribution network information-physical fusion model (i.e., the distribution network information-physical system).
- the information-physical system modeling based on the finite state machine includes a finite state machine model of the device and a finite state machine model of the system.
- the finite state machine model of the device can be implemented in the following ways. (1) Analyze the finite state set of the equipment in the distribution network and its working characteristics, including its working state (such as startup, shutdown, abnormality, etc.), operating characteristics and input/output quantities, and define the function expressions of various working states. (2) Analyze the state conversion rules of various types of power and information equipment under different external driving conditions, define the interface variables of the device-level model and the system-level model, and realize event-driven device-level model through interface variables.
- the finite state machine model of the system can be implemented in the following ways. (1) Based on the communication topology of the information-physical system of the distribution network, the primary topology of the power grid, and the business connections between information nodes, secondary nodes, and primary nodes, a static network topology between the finite state machine model of the information device and the finite state machine model of the physical device is constructed. (2) Based on the working function of the finite state machine model of the device under different working states, the quantized weights of each directed edge in the finite state machine network are defined; based on the state transition rules of the finite state machine model, the state migration rules of each node in the finite state machine network are designed.
- the overall process of the distribution network information-physical system fusion modeling method is shown in Figure 9, which is an optional flow chart of the distribution network information-physical system fusion modeling provided by an embodiment of the present invention.
- the physical system modeling includes the equivalent simulation modeling of the distribution hybrid network based on the dynamic phasor method, the multi-resolution and multi-level flexible model of the interactive elements, and the simulation model library supporting the operation of distribution networks with different modes;
- the communication network modeling includes the communication network physical layer model, the data link layer model, the event flow and information flow process model;
- the information system modeling includes multi-source information preprocessing, the network protection unit model and the network attack path model. Then, on the basis of the physical system modeling, the communication network modeling and the information system modeling, the information-physical system fusion modeling based on the spatiotemporal correlation matrix; and the information-physical system modeling based on the finite state machine.
- a fusion simulation model of the information-physical system of the distribution network is constructed, including a finite state machine-based information-physical fusion model of the distribution hybrid network, a multi-resolution and multi-level flexible model of the interactive elements of the distribution network; a communication network physical layer and data link layer model supporting the interaction of the physical information system, an extensible communication application layer model, a key event flow and information flow process model; and an information system model covering a network protection unit model and a network attack path model.
- the simulation platform architecture includes a model layer, a data layer, an algorithm layer, an interface layer and a business layer; the interface layer is used to connect the physical side and the information side of the distribution network; the distribution network simulation method also includes the following steps: in the model layer, for the physical side of the distribution network, the averaging method and the dynamic phasor method are used to construct the model to obtain a dynamic equivalent model of the distribution network; for the information side of the distribution network, a script method is used to construct the model of the key event flow and the information flow to obtain the key event flow and information flow process model; and a communication network physical layer model, a data link layer model, a communication application layer model and an information network security model are constructed; in the data layer, data collection, data processing and data storage are performed on the data in the model construction process and the simulation process; the business layer includes a simulation function module and an application scenario verification module, the simulation function module is used to support the transient simulation function of the distribution network information physical system, the steady-state simulation function of the distribution network information
- S103 in Figure 1 can also be implemented in the following manner.
- the simulation network decomposition and coordination technology, the multi-rate parallel real-time simulation method and the calculation speed dynamic adjustment method are used to perform real-time simulation of the physical nodes of the distribution network in the concurrent fault scenario of the physical system, the communication network and the information system to determine the fault simulation results of the distribution network.
- the overall architecture of the distribution network information-physical simulation platform adopts a layered architecture mode, which may include a model layer, a data layer, an algorithm layer, an interface layer, and a business layer, and also includes a platform management and control module and an application program interface (Application Program Interface, API) interface module, as shown in Figure 10.
- Figure 10 is an optional schematic diagram of the overall architecture of a distribution network information-physical simulation platform provided in an embodiment of the present invention.
- the model layer is used to provide the physical model, communication model and signal control model required for the information-physical fusion simulation of the distribution network; on the physical side, the averaging idea and the dynamic phasor method are used to construct the model, which can improve the calculation speed and efficiency and optimize the computing resources while taking into account the simulation calculation accuracy; on the communication side, scripts are used to model the key event flow and information flow.
- the data layer includes a data acquisition module, a data processing and management module, a data conversion module and a data storage module.
- the function of the data acquisition module can be connected to the PMS3.0 platform, the Supervisory Control And Data Acquisition (SCADA), the acquisition system and other data acquisition systems to collect the required data for the information physical simulation platform;
- the function of the data processing and management module can be to identify data anomalies and repair data for the existing distribution network data sources, types, poor accuracy and other problems;
- the function of the data conversion module can be to convert the collected data of different formats and forms into a format recognizable by this simulation platform;
- the function of the data storage module can be to store external collected data, internal calculation result data, model data and other data, which is composed of a graphics library and an attribute database, stored in an Oracle/Access database, and provides a basic support system and basic general data services, data persistence, and database access capabilities for the platform layer to call.
- the algorithm layer includes a distribution network information physical simulation calculation speed dynamic adjustment module, a multi-rate parallel simulation module, and a distribution network network decomposition module.
- the function of the calculation speed dynamic adjustment module can be to comprehensively consider the calculation accuracy, topological scale, and calculation speed, and select the calculation step in real time to obtain the maximum benefit of calculation accuracy and calculation efficiency;
- the function of the multi-rate parallel simulation module can be to complete the data and information interaction between components, devices, and systems with different simulation step requirements. This module cooperates with the calculation speed dynamic adjustment module to achieve efficient configuration of computing resources.
- the function of the distribution network network decomposition module can be to generate suitable network division principles, network division strategies, and segmentation interface algorithms to achieve effective decomposition and parallel calculation of large-scale distribution network topologies.
- the interface layer is used to provide an interface between the physical side and the information communication side of the distribution network.
- the business layer includes simulation function modules and application scenario verification modules that can be realized by the simulation platform.
- the simulation function modules are used to support functions such as transient simulation functions of distribution network information-physical systems, steady-state simulation functions of distribution network information-physical systems, communication systems and their fault simulations;
- the scenario verification modules are used to support distribution network information-physical concurrent fault scenario verification, distribution network information-physical system reliability analysis simulation, DDOS attacks, False Data Injection Attacks (FDIA) attacks and other distribution network information side attacks and fault scenario verifications.
- the steady-state simulation function of the information-physical system of the distribution network is realized in the following way: according to the different power values of the load and distributed power source in different time periods, the flow calculation is automatically performed according to the time-sharing data. At the same time, the synchronization of the flow calculation results is realized through the data interface. In addition, the remote control position change, remote adjustment and other data issued by the master station are monitored to realize the data synchronization between the cloud platform and the master station. The functions of period calculation, fault calculation, flow calculation, dynamic graph drawing, load management and the like under a certain time section can be realized.
- the communication system and its fault simulation function are implemented in the following way: based on the constructed and encapsulated communication system and communication system fault model, the communication system fault scenario can be quickly created and verified, the process and effect of the communication system fault can be reproduced, and the adaptability of the distribution network information-physical system can be improved.
- the verification of the concurrent information and physical fault scenarios of the distribution network can realize the reproduction of the process and effect of the simultaneous faults on the physical side and the information communication side.
- the physical side faults can realize common faults such as three-phase ground short circuit faults, single-phase ground short circuit faults, phase-to-phase short circuit faults, and line break faults
- the communication side faults can realize faults caused by DDOS attacks, FDIA attacks, virus invasions, etc., as well as common faults such as communication link interruption and communication delay.
- the reliability analysis simulation of the information-physical system of the distribution network can realize the possibility analysis of unilateral failures on the information side or the physical side or concurrent information-physical failures, and thus obtain the reliability analysis results of the information-physical system of the distribution network corresponding to different fault types.
- a distribution network information-physical system simulation architecture technology including a multi-level mapping relationship of a distribution network information-physical system simulation platform and an integrated construction scheme, a distribution network information-physical system simulation platform functional system and a computing architecture, which solves the problems of flexible loading, functional construction, synchronization and high-speed communication, and extended API interface of distribution network information-physical system simulation subsystems, and solves the technical problems of event-driven and continuous-time response coordination of distribution network information-physical system simulation, providing a strong basic guarantee for scenario verification and decision-making assistance such as power grid safety and stability analysis, reliability analysis and evaluation, and fault handling, and improves the adaptability of the distribution network information-physical system simulation platform.
- a multi-rate real-time simulation method and a calculation speed dynamic adjustment method are adopted to propose a real-time simulation method for physical nodes of a distribution network under concurrent fault scenarios of physical systems, communication networks and information systems, which meets the urgent needs of multi-scenario simulation and analysis of information-physical systems, provides technical and auxiliary decision-making support for fault isolation and fault recovery of distribution network information-physical systems, and improves the adaptability of distribution network information-physical systems and their simulation platforms.
- S103 in FIG. 1 may also include S1031 - S1034 .
- FIG. 11 is an optional schematic diagram of the classification of fast/medium/slow dynamic components of a distribution network information-physical system provided by an embodiment of the present invention.
- the simulation step size of the fast time scale is between 10 microseconds and 100 microseconds
- the representative components include distributed power sources such as photovoltaics containing power electronic components, flexible power electronic devices, etc.
- the simulation step size of the medium time scale is between 100 microseconds and 1 millisecond, and the representative components include rotating equipment represented by diesel engines and electric motors.
- the simulation step size of the slow time scale is above milliseconds, and the representative components include capacitors, reactors, transformers, control systems, and other electrical system components that do not contain power electronic components.
- the modeling method of the distribution network information-physical system described above is adopted, and according to the construction method of the distribution network information-physical system described in S102 above, the classified distribution network components are modeled to obtain a physical network in the distribution network information-physical system containing each component.
- S1033 can also be implemented in the following ways. Obtain loading data and the number of CPU cores; perform transient simulation according to the loading data and the number of CPU cores, and use genetic algorithms to allocate the number of CPUs for calculating lines and the number of CPUs for calculating each component to obtain allocation results; the allocation results include the node type, number, and line corresponding to each CPU; construct a simulation task decomposition model according to the allocation results; use the node splitting method to dynamically decouple the simulation task decomposition model corresponding to the physical network in the information-physical system of the distribution network of each component, corresponding to the component type of each component, to obtain a decoupled model; construct an equivalent model between networks of each component and an equivalent model between components and networks according to the decoupled model; the equivalent model includes an equivalent model between networks and an equivalent model between components and networks.
- the construction of a fault simulation model of a distribution network cyber-physical system includes dividing the target distribution network into three categories of fast, medium and slow according to the different time response speeds of the components therein, modeling the distribution network components, and fast/medium/slow dynamic decoupling of the distribution network cyber-physical system. Next, the fast/medium/slow dynamic decoupling of the distribution network cyber-physical system is described.
- fast/medium/slow dynamic decoupling when fast/medium/slow dynamic decoupling is performed on the information-physical system of the distribution network, fast/medium/slow dynamic decoupling is performed only on the physical network, and a corresponding equivalent model is established.
- the fast/medium/slow dynamic decoupling of the information-physical system of the distribution network includes a simulation task decomposition model of the information-physical system of the distribution network and a network decoupling of the information-physical system of the distribution network.
- constructing a distribution network information-physical system simulation task decomposition model includes: constructing a decomposition optimization model and using intelligent algorithms such as genetic algorithms to solve the optimization model, wherein the optimization process is shown in Figure 12, which is an optional schematic diagram of a decomposition optimization model provided in an embodiment of the present invention, and the decomposition optimization steps include S21-S26.
- the data includes but is not limited to network topology, number of feeders, number of nodes and central processing unit (CPU) performance data.
- User input includes, but is not limited to, the number of CPU cores involved in the calculation (corresponding to the number of central processing unit cores).
- transient simulation (corresponding to transient simulation according to the loading data and the number of CPU cores).
- the allocation results include but are not limited to the node type, quantity and feeder number of each CPU participating in the calculation (the corresponding allocation results include the node type, quantity and line corresponding to each central processor).
- the number of CPU cores participating in the traditional load node calculation and the number of CPU cores participating in the transient node calculation are determined as shown in formula (6).
- nCPU is the total number of CPU cores involved in the calculation. is the number of CPU cores of the nodes participating in the traditional load, is the number of CPU cores involved in transient calculations; n 1* is the number of traditional load nodes involved in calculations, and n 2* is the number of transient nodes involved in calculations; It is the average number of traditional load nodes equivalent to a transient model.
- the above formula (7) is the total number of CPU cores involved in the simulation calculation of the k-th transient element; n 2k* is the number of the k-th transient elements involved in the calculation; nk is the number of traditional load nodes to which a k-th transient element is equivalent, and satisfies the following formula (8).
- P1 is the weight coefficient of the first-level optimization target
- P2 is the weight coefficient of the second-level optimization target
- mia is the number of the first feeder calculated by the i-th CPU core
- mib is the number of the last feeder calculated by the i-th CPU core
- ni is the optimal calculation amount of the i-th CPU core
- ni1* is the number of traditional load nodes participating in the calculation of the i-th CPU core in this iteration
- m ja is the number of the first feeder calculated by the jth CPU core
- m jb is the number of the last feeder calculated by the jth CPU core
- n j is the optimal calculation amount of the jth CPU core
- n kj2* is the number of the kth transient elements calculated by the jth CPU core in this iteration
- the constraints are the operation constraints of the cyber-physical system of the distribution network.
- the node splitting method when decoupling the distribution network information-physical system network, can be used to decouple the distribution network information-physical system network, as shown in Figure 13.
- Figure 13 is an optional schematic diagram of distribution network information-physical system network decoupling provided by an embodiment of the present invention, including S31-S38.
- Input subsystem line topology parameters and load parameters, and calculate the three parameters of the ZIP model.
- S33 and S34 can be executed simultaneously, S33 can be executed first and then S34, or S34 can be executed first and then S33. This embodiment of the present invention does not limit this.
- the network decoupling of the information-physical system of the distribution network includes the following steps: (1) Under the premise of ensuring the balance of the computing scale of the subnet, select certain nodes in the network as split nodes, and split the network into several independent subsystems. The subsystems only exchange information through the connecting branch current of the split node. (2) For each subsystem, establish a ZIP load model respectively, calculate the three parameters of constant impedance, constant current, and constant power. The constant impedance load part parameters are used to solve the node admittance matrix, and the constant current and constant power load part parameters are used to solve the node injection current phasor. (3) Calculate the node admittance matrix of each subsystem.
- the node admittance matrix of the distribution network is a singular matrix
- the node admittance matrix is improved by the method proposed in the present invention.
- the branch current equation between the connecting subsystems and the node voltage equation inside the subsystem are combined to obtain the current on the connecting branch between the subsystems.
- a real-time simulation method for a distribution network information-physical system includes a simulation decomposition and coordination technology, a multi-rate parallel real-time simulation method, and a calculation speed dynamic adjustment method. These three methods are introduced below respectively.
- the simulation decomposition and coordination technology of the distribution network information-physical system includes a simulation decomposition component equivalent model and a fast/medium/slow data coordination method, which are introduced below respectively.
- the simulation decomposition component equivalent model of the power distribution network cyber-physical system includes an equivalent model between networks and an equivalent model between components and networks.
- the series voltage source port is recorded as a class A port, which is replaced by a current source and called a current port;
- the parallel current source port is recorded as a class B port, which is replaced by a voltage source and called a voltage port. If port 1 to port k are class A ports, and port k+1 to port m are class B ports, the superposition theorem yields the following formula (10).
- U eq is the series voltage source of the class A port;
- I eq is the parallel current source of the class B port;
- H AA , H AB , H BA , H BB are the equivalent impedances of the ports.
- FIG14a is an optional schematic diagram of an equivalent model between components and networks provided by an embodiment of the present invention
- FIG14a is a line-side equivalent model with injected current as a coordination variable, wherein R represents resistance, i represents the current of the line model, L represents inductance, us represents voltage, is is the external network equivalent injected current at the split node, and the external characteristic of the line-side subnet is represented as shown in formula (11).
- FIG14b is an optional schematic diagram of another equivalent model between components and networks provided by an embodiment of the present invention
- FIG14b is an equivalent model of a distributed power subnet with node voltage as a coordination variable, wherein R (Resistance) represents resistance, u represents voltage of a transient component model, L represents inductance, u s represents voltage, and u s is an equivalent node voltage of an external network at a split node.
- R Resistance
- u voltage of a transient component model
- L represents inductance
- u s represents voltage
- u s is an equivalent node voltage of an external network at a split node.
- the external characteristic of a distributed power subnet is represented as shown in formula (12).
- an external system data update mode based on interpolation is proposed to achieve coordination of fast/medium/slow data, as shown in Figure 15, which is an optional schematic diagram of a simulation data update mode based on interpolation provided in an embodiment of the present invention.
- subsystem 1 adopts a long simulation step length T 1
- subsystem 2 adopts a short simulation step length T 2
- T 1 mT 2 , where m is a positive integer.
- subsystem 1 transmits its own simulation result x n-1 in the time step [t n-2 , t n-1 ] and its simulation result x n in the time step [t n-1 , t n ] to subsystem 2
- subsystem 2 transmits its own simulation result yn in the time step [t n-1 , t n ] to subsystem 1 .
- subsystem 1 performs an iterative calculation using the external system state quantity yn ; subsystem 2 performs interpolation using the external system state quantities x n-1 and x n , and obtains m external system state quantities x n,1 ...x n,m in turn according to formula (13), and performs m iterative calculations.
- the external system data used by subsystem 2 in the simulation process lags behind the unit simulation step T 1 of subsystem 1, but the data interaction process is still real-time.
- Figures 16a and 16b are optional schematic diagrams of multi-time scale information interaction provided by the embodiment of the present invention.
- Figure 16a shows the interaction process between the controlled object (simulink), the communication network (OPNET) and the controller (Matlab), combined with the interaction between the various execution subjects shown in Figure 16b in the fast/medium/slow different types of coordination process (including t 1 , t 2 ...t n ).
- the controlled object and the controller are all packaged with measured data, user datagram protocol (UDP, User Datagram Protocol), sitl interface, UDP transmission protocol, and control signal decoding.
- the communication network interacts with the controlled object through a sitl interface and interacts with the controller through another sitl interface.
- Subsystem 1 and subsystem 2 use short and medium step sizes to simulate different types of transient elements respectively;
- subsystem 3 contains all traditional load nodes on the feeder and uses long step size simulation.
- an embodiment of the present invention proposes an adaptive variable-step multi-rate parallel simulation technology, in which the simulation step size is adaptively adjusted within the subsystem, and each subsystem adopts a plurality of simulation step sizes for parallel simulation, thereby accelerating the transient response of the system without significantly increasing resource consumption, thereby ensuring the safe and stable operation of each subsystem.
- the delay module is used to record the system state value of subsystem 1 at the end of the previous simulation step, and the triangular wave generator is used to complete the interpolation coefficient of each large step.
- the calculation enables subsystem 2 to obtain the updated state of the opposite subsystem at the initial moment of each time step and start the next round of iterative calculation.
- FIG17 is an optional schematic diagram of a data interaction module with adaptive step size adjustment provided by an embodiment of the present invention
- V in in From3 represents the voltage state quantity output by subsystem 1 at large step size intervals
- V out in Goto represents the state quantity of the opposite subsystem obtained by subsystem 2 after interpolation calculation.
- Transport Delay represents the transmission delay
- Repeating Sequence represents the periodic sequence
- Add and Add1 represent adders
- Divide represents a divider.
- the signal transformation process shown in FIG17 is universal for variable step size simulation of subsystem 2, and can realize real-time interaction of simulation data between bilateral subsystems, solving technical problems such as step size mismatch.
- the dynamic adjustment method of simulation calculation speed of distribution network cyber-physical system includes the design of simulation step size comprehensive optimization objective function and simulation step size adaptive adaptation mechanism.
- FIG18 is an optional schematic diagram of a maximum simulation step calculation provided by an embodiment of the present invention.
- AC Alternating Current
- FIG18 represents alternating current
- the differential equation on the digital side in FIG18 is The representation is shown in formula (14).
- the simulation step length h 2 can be obtained from the above formula.
- the common part of h 1 and h 2 is the running direction of the simulation step length, and its upper bound (that is, the minimum value of h 1max and h 2max ) is the maximum value of the simulation step length h max .
- FIG19 is an optional schematic diagram of a simulation step length adaptive mechanism provided by an embodiment of the present invention.
- t0 represents the simulation start time (also referred to as the simulation initial moment)
- t1 represents the fault occurrence time (also referred to as the fault time)
- t2 represents the fault removal time
- tend represents the simulation end time.
- the period from t0 to t1 is the steady state before the fault
- the period from t1 to t2 is the fault
- the period from t2 to tend is the post-fault period.
- the system is in a steady state.
- the backward Euler method, the trapezoidal method and other algorithms with small computational complexity and slightly lower precision can be used to simulate with a larger step length.
- the simulation step length Assuming that the maximum step length hmax obtained by the proposed simulation step length objective function is the simulation step length, the simulation is performed to a point tk before the fault occurrence time. If the maximum step length hmax is used and the fault occurrence time t1 is exceeded, the maximum simulation step length is changed to t1 - tk . The same processing method is used for the time periods t 2 and t end .
- the distribution network information physical system fault simulation analysis method includes three steps: construction of a distribution network information physical system fault simulation model, a distribution network information physical system fault simulation method and a distribution network information physical system fault simulation example analysis.
- the construction of the distribution network information physical system fault simulation model is achieved through the above S1031-S1033.
- the distribution network information physical system fault simulation method includes the simulation decomposition and coordination method, multi-rate parallel real-time simulation method and calculation speed dynamic adjustment method in the above S1034.
- the distribution network information physical system fault simulation example analysis is introduced.
- the multi-rate parallel real-time simulation method includes a multi-rate simulation coordination strategy
- the calculation speed dynamic adjustment method is a simulation step dynamic adjustment method
- the above S1034 can also be implemented in the following manner.
- the physical network equivalent model including each component is subjected to real-time fault simulation to determine the fault extension node; the fault simulation result of the distribution network includes the fault extension node.
- the circuit breaker switch when a fault occurs in the physical layer of the distribution network, the circuit breaker switch will trip, the load switch will lose pressure and open, and after the reclosing fails, the overcurrent information of the relevant terminal will be uploaded to the control platform through the information communication layer.
- the control platform locates the fault and issues control instructions to complete the reclosing of the non-fault area. If a DDOS attack occurs to the communication link during the upload process, so that the control instruction cannot be issued, the power outage area will be expanded.
- the simulation model is shown in Figure 20.
- Figure 20 is an optional schematic diagram of a distribution network information-physical simulation example analysis provided by an embodiment of the present invention.
- Figure 20 shows the interaction between the information control layer, the information communication layer and the distribution physical layer. The simulation process is as follows.
- the method described in S1021-S1023 above is used to construct a physical system model, a communication network model and an information system model.
- a permanent fault is set between the physical system section switches 11-12, and a DDOS attack occurs in the communication link, causing the server to be unable to respond to normal requests, resulting in a communication network congestion failure.
- S104 in FIG. 1 above may also include S1041 - S1047 .
- New random numbers are drawn for the target components respectively, and the corrected working time of the target components is calculated respectively according to the new random numbers.
- a reliability assessment system for the information-physical system of the distribution network is constructed and a reliability simulation calculation method is proposed, which provides strong theoretical support and decision-making assistance for improving the reliability of the distribution network, maintains the stable and reliable operation of the distribution network, and improves the adaptability of the information-physical system of the distribution network and its simulation platform.
- the elements include: physical side elements and information side elements
- the target elements include: target physical side elements and target information side elements
- the above S1047 can also be implemented in the following ways. According to the target normal working time and target fault repair time of each physical side element, and the target normal working time and target fault repair time of each information side element, the load node evaluation result is calculated; according to the target normal working time and target fault repair time of each physical side element, the physical side reliability evaluation result is calculated; according to the target normal working time and target fault repair time of each information side element, the information side reliability evaluation result is calculated; the reliability evaluation result includes the physical side reliability evaluation result and the information side reliability evaluation result.
- the elements include: a physical side element and an information side element, new random numbers are respectively drawn for the target physical side element and the target information side element, and the corrected working time of the target physical side element and the corrected working time of the target information side element are respectively calculated according to the new random numbers; the sum of the corrected working time, normal working time and fault repair time of the target physical side element is used as the new normal working time of the target physical side element; the sum of the corrected working time, normal working time and fault repair time of the target information side element is used as the new normal working time of the target information side element; the new normal working time of the target physical side element and the new normal working time of the target information side element are used for the next simulation process, and the working time simulation is continued until the normal working time of any element on the information side or the physical side reaches the preset simulation period, so as to obtain the target normal working time and target fault repair time of each physical side element, as well as the target normal working time and target fault repair time of each information side element.
- the comprehensive failure rate of the load node is determined based on the failure rate of the physical side elements, the weight of the physical side elements, the failure rate of the information side elements, and the weight of the information side elements; based on the comprehensive failure rate of the load node, the N random numbers corresponding to the N physical side elements are converted into the normal working time of the N physical side elements.
- the embodiment of the present invention provides a reliability calculation method that considers the influence of information-physical interaction.
- the interaction between the physical and information subsystems is relatively complex. Therefore, the reliability analysis of the entire information-physical system of the distribution network needs to consider the interaction and influence between the information system and the physical system.
- the embodiment of the present invention adopts a subjective weighting method to characterize the influence of the reliability of the information system on the reliability of the physical system, and then obtains a reliability calculation method that considers the influence of information-physical interaction.
- the reliability analysis process of the information-physical system of the distribution network based on the Monte Carlo method provided by the embodiment of the present invention is shown in Figure 21, and the reliability analysis process includes S41-S48.
- the failure rate, repair time and system repair time of each physical side component and communication side component are also initialized.
- the deep search method is used to search the power supply path of the distribution network to determine the minimum power supply path; the deep search method is used to search the communication network of the distribution network to determine the shortest communication link.
- the Monte Carlo method N random numbers are drawn, and the normal working time TTF and fault repair time TTR of each component are calculated according to the following formulas (23) and (24), and the clock T is assigned to 0.
- the subjective assignment method is used to determine the comprehensive failure rate of the load node according to the relative size of the influence of the information side and the physical side of different nodes, as shown in formula (25).
- ⁇ zh ⁇ 1* ⁇ P + ⁇ 2 ⁇ ⁇ C (25)
- ⁇ zh , ⁇ P , and ⁇ C represent the node comprehensive failure rate, physical side node failure rate, and communication node failure rate, respectively; ⁇ 1 and ⁇ 2 are the impact weights of the physical side and the corresponding information side, respectively, which can be determined according to the actual conditions of different nodes.
- the same Monte Carlo method principle as the physical layer is used to calculate the normal working time TTF and fault repair time TTR of the communication node components.
- TTF+TTR+TTF' is used as the new normal working time TTF of the physical side component and the information side component of the node.
- S47 determine whether the simulation time is greater than the simulation life.
- the loop ends and continues to execute S48 (corresponding to the above S1046, that is, continue to simulate the working time until the normal working time of any component reaches the preset simulation life, and obtain the target normal working time and target fault repair time of each component).
- the above-mentioned reliability assessment indicators include physical side reliability assessment indicators;
- the distribution network simulation method also includes the following steps: based on the simulation platform architecture, according to the acquired failure rates of each component and each device, using pre-built reliability assessment models in different forms and physical side reliability assessment indicators, perform physical side reliability assessment of the distribution network information-physical system, and determine the physical side reliability simulation results;
- the reliability simulation results include physical side reliability simulation results; wherein, different forms of reliability assessment models include a series unit consisting of multiple components connected in series, a parallel unit consisting of multiple components connected in parallel, and a voting unit consisting of multiple components connected in parallel and in series with a voter.
- the reliability and failure rate calculation model of the commonly used components and equipment in the distribution network can include a series unit, a parallel unit, and a voting unit.
- the following uses a block diagram method to illustrate the construction of the reliability and failure rate calculation model of components and equipment.
- the reliability block diagram of the series unit is shown in FIG22a.
- the unit can work normally. Its reliability calculation is shown in formula (26).
- Rs represents the reliability of the series unit
- ri represents the reliability of the i-th component in the unit.
- the reliability block diagram of the parallel unit is shown in FIG22b. As long as there is a component in the unit that works normally, that is, any component among r1 , r2 ... ri , the unit can work normally. Its reliability calculation is shown in formula (27).
- R P represents the reliability of the series unit.
- the reliability block diagram of the voting unit is shown in FIG. 22c , and its reliability calculation is shown in formula (28).
- R L represents the reliability of the voting unit
- R i and F i are the reliability and unreliability of the i-th component, respectively.
- the above-mentioned physical side reliability assessment indicators include a continuous power outage indicator, an instantaneous power outage indicator, and load-related indicators; wherein the continuous power outage indicator includes at least one of the following: system average power outage frequency, system average power outage time, user average power outage duration, user total average power outage time, user average power outage frequency, average power supply availability and user multiple power supply indicator; the load-related power outage indicators include at least one of the following: average system power outage frequency and average system power outage duration; the instantaneous power outage indicator includes: average instantaneous power outage frequency.
- the reliability index of the physical system of the distribution network is divided into three categories: continuous power outage index, instantaneous power outage index, and load-related index.
- continuous power outage index instantaneous power outage index
- load-related index load-related index
- the continuous power outage index includes the system average power outage frequency, the system average power outage time, the user average power outage duration, the user's total average power outage time, the user's average power outage frequency, the average power supply availability rate and the user's multiple power supply index, which are explained below respectively.
- SAIFI system average power outage frequency
- Nc is the number of users in each power outage
- Ntotal is the total number of users
- the system average power outage time (SAIDI), in units of min/(household ⁇ a), is shown in formula (30).
- TC is the power outage time of the user.
- CTAIDI total average power outage time of users
- NC,total is the number of users affected by the power outage.
- CAIFI average power outage frequency of users
- the average supply availability factor (ASAI) is shown in formula (34).
- ha avaiable and h demand represent the available power supply hours and the user's power supply demand hours, respectively.
- CEMI n The user's multiple power supply index (CEMI n ) is shown in formula (35).
- the load-related power outage indicators include average system power outage frequency (ASIFI) and average system power outage duration (ASIDI), which are described below respectively.
- ASIFI average system power outage frequency
- ASIDI average system power outage duration
- the average system outage frequency (ASIFI) is shown in formula (36).
- L outage and L total represent the load loss and total power supply load in each power outage respectively.
- the average system outage duration (ASIDI), in minutes, is shown in formula (37).
- the instantaneous power outage index includes the average instantaneous power outage frequency (MAIFI), the unit of which is times/(household ⁇ a), as shown in formula (38).
- MAIFI average instantaneous power outage frequency
- O s and N outages represent the number of operations per power outage and the number of users per instantaneous power outage, respectively.
- the change trend of the distribution network operation index over the years can be better reflected.
- the above reliability evaluation indicators include information side reliability evaluation indicators, and the information side reliability evaluation indicators include: network connectivity reliability and network performance reliability; wherein, network connectivity reliability includes at least one of the following: connectivity, cohesion, hybrid connectivity coefficient, basic network reliability, end-to-end reliability and full-end reliability; network performance reliability includes at least one of the following: mean time between failures and mean time to repair failures.
- the reliability index of the information system of the distribution network is divided into two parts: network connectivity reliability and network performance reliability.
- the definitions of various indicators are as follows.
- network connectivity reliability includes connectivity, cohesion, mixed connectivity coefficient, basic network reliability, end-to-end reliability and full-end reliability, which are described below respectively.
- T represents the connectivity between node i and node j
- CH ij is the number of paths that must be removed to disconnect all paths between node i and node j in the Unicom network.
- the cohesion is shown in formula (40).
- S represents the cohesion between node i and node j
- CN ij is the number of nodes that must be removed to disconnect all paths between node i and node j in the Unicom network.
- the mixed connectivity coefficient is shown in formula (41).
- M represents the number of paths and nodes that need to be disconnected and removed when the information network is divided into several subnets.
- the basic reliability reflects the probability that the object (such as communication network, network component, network equipment) is fault-free, where R vi (t) represents the probability that the i-th communication link is unobstructed and fault-free, and Rej (t) represents the probability that the j-th network component or equipment is fault-free.
- the above formula (43) represents the probability network performance reliability that there is at least one path between two nodes specified in the network G.
- network performance reliability includes mean time between failures and mean time to repair, which are described below respectively.
- the average failure interval time in the above formula (46) can represent the frequency of failure occurrence during the effective period, where T represents the total duration of the failure during the effective monitoring period, d represents the average duration of the word failure, and ⁇ represents the probability of failure occurrence.
- the mean fault repair time is shown in formula (47).
- the mean repair time in the above formula (47) can be used to characterize the average time for fault repair.
- the embodiment of the present invention further provides a distribution network simulation system, as shown in Figure 23.
- Figure 23 is an optional structural schematic diagram of a distribution network simulation system provided by the embodiment of the present invention.
- the distribution network simulation system 230 includes: a platform building part 2301, which is configured to perform multi-level and multi-scale platform architecture modeling based on the model differences, interactive effects, and scale and accuracy of multi-scenario simulation verification between the information system and the physical system in the distribution network to obtain a simulation platform architecture; a fusion part 2302, which is configured to perform multi-level and multi-scale platform architecture modeling based on the coupling characteristics between the physical system and the information system in the distribution network on the simulation platform architecture.
- the information-physical simulation system under time-varying information and uncertain conditions is integrated and modeled to obtain the information-physical system of the distribution network;
- the fault simulation part 2303 is configured to perform real-time simulation of the information-physical system of the distribution network under concurrent fault scenarios of the physical system, communication network and information system based on the simulation platform architecture, and determine the fault simulation results of the distribution network;
- the fault simulation results are used to provide support for the fault isolation decision and fault recovery decision of the information-physical system of the distribution network;
- the reliability simulation part 2304 is configured to perform reliability simulation evaluation on the information-physical system of the distribution network based on the simulation platform architecture using reliability evaluation indicators, and determine the reliability simulation results of the distribution network.
- the fusion part 2302 is also configured to build a physical system model based on the dynamic equivalent model of the distribution network and a simulation model library supporting the operation of distribution networks of different modes; build a communication network model based on a cross-application and cross-node data flow model library that supports multiple typical protocols; pre-process multi-source information based on the communication network model, and build an information system model in combination with the information network security model; perform system fusion modeling based on the association matrix, physical system model, communication network model and information system model to obtain a fusion system; based on the finite state machine of the device and the finite state machine of the system, respectively construct the finite state machine model of the device in the fusion system and the finite state machine model of the system to obtain the information-physical system of the distribution network.
- the fusion part 2302 is also configured as a distribution hybrid network information-physical fusion modeling method based on a finite state machine and a multi-resolution and multi-level flexible model construction method for physical-side interactive elements to form a simulation model library that supports the operation of distribution networks of different modes; according to the construction method of the communication network physical layer model and data link layer model, the communication application layer model, the key event flow and the information flow process model used to support the interaction of the physical information system, a cross-application and cross-node data flow model library that supports multiple typical protocols is formed.
- the simulation platform architecture includes a model layer, a data layer, an algorithm layer, an interface layer, and a business layer; the interface layer is used to connect the physical side and the information side of the distribution network;
- the fusion part 2302 is also configured to construct a model in the model layer for the physical side of the distribution network by using the averaging method and the dynamic phasor method to obtain a dynamic equivalent model of the distribution network; for the information side of the distribution network, a script method is used to construct a model of the key event flow and information flow to obtain a key event flow and information flow process model; and a communication network physical layer model, a data link layer model, a communication application layer model and an information network security model are constructed; in the data layer, data collection, data processing and data storage are performed on the data in the model construction process and the simulation process; the business layer includes a simulation function module and an application scenario verification module, the simulation function module is used to support the transient simulation function of the distribution network information physical system, the steady-state simulation function of the distribution network information physical system, and the communication network and communication network fault simulation function; the scenario verification module is used to support the concurrent fault scenario verification of the distribution network information physical system, the reliability analysis simulation of the distribution network information physical system, and the information side attack and
- the fault simulation part 2303 is also configured to use simulation network decomposition and coordination technology, multi-rate parallel real-time simulation method and calculation speed dynamic adjustment method in the algorithm layer to perform real-time simulation of the physical nodes of the distribution network under concurrent fault scenarios of physical systems, communication networks and information systems to determine the fault simulation results of the distribution network.
- the fault simulation part 2303 is also configured to classify the components according to the dynamic response time or response speed of different components to obtain the component type of each component; wherein the component types include fast type, intermediate type and slow type, and the simulation step length corresponding to the intermediate type is greater than the simulation step length corresponding to the fast type, and less than or equal to the simulation step length corresponding to the slow type; modeling is performed on the classified components in the distribution network; the physical network in the information-physical system of the distribution network containing each component is dynamically decoupled, and an equivalent model is established; a simulation decomposition and coordination method, a multi-rate parallel real-time simulation method and a calculation speed dynamic adjustment method are used to perform real-time fault simulation on the equivalent model of the physical network containing each component to determine the fault simulation result of the distribution network.
- the component types include fast type, intermediate type and slow type
- the simulation step length corresponding to the intermediate type is greater than the simulation step length corresponding to the fast type, and less than or equal to the simulation step length corresponding to the slow type
- the multi-rate parallel real-time simulation method includes a multi-rate simulation coordination strategy, and the calculation speed dynamic adjustment method is a simulation step size dynamic adjustment method;
- the fault simulation part 2303 is also configured to perform real-time fault simulation on the physical network equivalent model including each component based on the multi-rate simulation coordination strategy and the dynamic adjustment method of the simulation step according to the nodes where permanent faults occur in the preset physical system section switches, the preset physical system fault occurrence time and the preset communication link fault occurrence time, and determine the fault extension node; the fault simulation result of the distribution network includes the fault extension node.
- the fault simulation part 2303 is also configured to obtain loading data and the number of CPU cores; perform transient simulation based on the loading data and the number of CPU cores, and use a genetic algorithm to allocate the number of CPUs for the calculation line and the number of CPUs for each component to obtain an allocation result; the allocation result includes the node type, quantity and line corresponding to each CPU; based on the allocation result, construct a simulation task decomposition model; use the node splitting method to dynamically decouple the simulation task decomposition model corresponding to the physical network in the information-physical system of the distribution network of each component according to the component type to obtain a decoupled model; based on the decoupled model, construct an equivalent model between the networks of each component and an equivalent model between the component and the network; the equivalent model includes an equivalent model between the networks and an equivalent model between the component and the network.
- the reliability simulation part 2304 is also configured to search the power supply path and communication network of the distribution network respectively according to the deep search method to determine the minimum power supply path and the shortest communication link; adopt the Monte Carlo method to randomly select N components from multiple components according to the minimum power supply path and the shortest communication link, and calculate the normal working time and fault repair time of the N components; according to the routing table and the association relationship, find the target components directly affected by each load node; re-extract new random numbers for the target components, and calculate the corrected working time of the target components according to the new random numbers; take the sum of the corrected working time, normal working time and fault repair time of the target component as the new normal working time of the target component; the new normal working time of the target component is used for the next working time simulation process; continue the working time simulation until the normal working time of any component reaches the preset simulation life, and obtain the target normal working time and target fault repair time of each component; calculate the load node evaluation result and the reliability evaluation result according to the target normal working time and the target fault repair
- the element includes: a physical side element and an information side element
- the target element includes: a target physical side element and a target information side element
- the reliability simulation part 2304 is also configured to calculate the load node evaluation results based on the target normal working time and target fault repair time of each physical side element, and the target normal working time and target fault repair time of each information side element; calculate the physical side reliability evaluation results based on the target normal working time and target fault repair time of each physical side element; calculate the information side reliability evaluation results based on the target normal working time and target fault repair time of each information side element; the reliability evaluation results include the physical side reliability evaluation results and the information side reliability evaluation results.
- the reliability assessment indicator includes a physical side reliability assessment indicator
- the reliability simulation part 2304 is also configured to perform physical side reliability assessment of the information-physical system of the distribution network based on the simulation platform architecture, according to the acquired failure rates of each component and each device, and by using pre-built reliability assessment models in different forms and physical side reliability assessment indicators, and determine the physical side reliability simulation results; the reliability simulation results include physical side reliability simulation results; wherein, different forms of reliability assessment models include a series unit consisting of multiple components connected in series, a parallel unit consisting of multiple components connected in parallel, and a voting unit consisting of multiple components connected in parallel and in series with a voter.
- physical side reliability assessment indicators include continuous power outage indicators, instantaneous power outage indicators, and load-related indicators; wherein the continuous power outage indicator includes at least one of the following: system average power outage frequency, system average power outage time, user average power outage duration, user total average power outage time, user average power outage frequency, average power supply availability, and user multiple power supply indicators; load-related power outage indicators include at least one of the following: average system power outage frequency and average system power outage duration; instantaneous power outage indicators include: average instantaneous power outage frequency.
- the reliability evaluation index includes an information side reliability evaluation index
- the information side reliability evaluation index includes: network connectivity reliability and network performance reliability; wherein, network connectivity reliability includes at least one of the following: connectivity, cohesion, hybrid connectivity coefficient, basic network reliability, end-to-end reliability and full-end reliability; network performance reliability includes at least one of the following: mean time between failures and mean time to repair failures.
- the distribution network simulation system provided in the above embodiment only uses the division of the above-mentioned program parts as an example when performing distribution network simulation.
- the above-mentioned processing can be assigned to different program parts as needed, that is, the internal structure of the system is divided into different program parts to complete all or part of the processing described above.
- the distribution network simulation system and the distribution network simulation method embodiment provided in the above embodiment belong to the same concept. The specific implementation process and beneficial effects are detailed in the method embodiment, which will not be repeated here. For technical details not disclosed in the embodiment of this system, please refer to the description of the method embodiment of the present invention for understanding.
- FIG24 is a schematic diagram of the composition structure of the distribution network simulation device proposed in an embodiment of the present invention.
- the distribution network simulation device 240 proposed in an embodiment of the present invention includes a processor 2401 and a memory 2402 storing an executable computer program.
- the processor 2401 is configured to execute the executable computer program stored in the memory 2402 to implement the distribution network simulation method provided in an embodiment of the present invention.
- the distribution network simulation device 240 may further include a communication interface 2403, and a bus 2404 for connecting the processor 2401, the memory 2402 and the communication interface 2403.
- the processor 2401 may be at least one of an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a central processing unit (CPU), a controller, a microcontroller, and a microprocessor.
- ASIC application specific integrated circuit
- DSP digital signal processor
- DSPD digital signal processing device
- PLD programmable logic device
- FPGA field programmable gate array
- CPU central processing unit
- the electronic device used to realize the function of the processor may also be other, and the embodiment of the present invention does not specifically limit it.
- the bus 2404 is used to connect the communication interface 2403, the processor 2401 and the memory 2402 to achieve mutual communication between these devices.
- the memory 2402 is used to store executable computer programs and data.
- the executable computer programs include computer operation instructions.
- the memory 2402 may include high-speed RAM memory, and may also include non-volatile memory, for example, at least two disk memories.
- the memory 2402 may be a volatile memory (volatile memory), such as a random access memory (Random-Access Memory, RAM); or a non-volatile memory (non-volatile memory), such as a read-only memory (Read-Only Memory, ROM), a flash memory (flash memory), a hard disk (Hard Disk Drive, HDD) or a solid-state drive (Solid-State Drive, SSD); or a combination of the above types of memory, and provide the processor 2401 with executable computer programs and data.
- volatile memory such as a random access memory (Random-Access Memory, RAM)
- non-volatile memory non-volatile memory
- ROM read-only memory
- flash memory flash memory
- HDD Hard Disk Drive
- each functional module in this embodiment can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.
- the above integrated unit can be implemented in the form of hardware or software functional modules.
- the integrated unit is implemented in the form of a software function module and is not sold or used as an independent product, it can be stored in a computer-readable storage medium.
- the technical solution of this embodiment is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product.
- the computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) or a processor to perform all or part of the steps of the method of this embodiment.
- the aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.
- An embodiment of the present invention provides a computer-readable storage medium storing a computer program, which is configured to implement the distribution network simulation method as described in any of the above embodiments when executed by a processor.
- program instructions corresponding to a distribution network simulation method in this embodiment can be stored on a storage medium such as a CD, a hard disk, or a USB flash drive.
- a storage medium such as a CD, a hard disk, or a USB flash drive.
- the embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program codes.
- each process and/or box in the flow diagram and/or block diagram can be implemented by computer program instructions, as well as the combination of the process and/or box in the flow diagram and/or block diagram.
- These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the function specified in one process or multiple processes and/or one box or multiple boxes in the flow diagram.
- These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in implementing one or more processes in the flowchart and/or one or more boxes in the block diagram.
- These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.
- the embodiment of the present invention discloses a distribution network simulation method, system, device and computer-readable storage medium.
- the method includes: according to the model differences, interactive effects, and scale and accuracy of multi-scenario simulation verification between the information system and the physical system in the distribution network, a multi-level and multi-scale platform architecture modeling is performed to obtain a simulation platform architecture; on the simulation platform architecture, according to the coupling characteristics between the physical system and the information system in the distribution network, the information-physical simulation system under time-varying information and uncertain conditions is integrated and modeled to obtain the information-physical system of the distribution network; based on the simulation platform architecture, in the concurrent fault scenario of the physical system, the communication network and the information system, the information-physical system of the distribution network is simulated in real time to determine the fault simulation result of the distribution network; based on the simulation platform architecture, the reliability simulation evaluation of the information-physical system of the distribution network is performed using the reliability evaluation index to determine the reliability simulation result of the distribution network.
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Abstract
本发明实施例公开一种配电网仿真方法、系统、设备和计算机可读存储介质。该方法包括:根据配电网中信息系统与物理系统之间的模型差异性、交互影响,及多场景仿真验证的规模和精度,进行多层级、多尺度的平台架构建模,得到仿真平台架构;在仿真平台架构上,根据配电网中物理系统与信息系统之间的耦合特性,对时变信息、非确定条件下的信息物理仿真系统进行融合建模,得到配电网信息物理系统;基于仿真平台架构,在物理系统、通信网络及信息系统的并发故障场景下,对配电网信息物理系统进行实时仿真,确定配电网的故障仿真结果;基于仿真平台架构,利用可靠性评估指标对配电网信息物理系统进行可靠性仿真评估,确定配电网的可靠性仿真结果。
Description
本发明涉及电力系统仿真技术领域,尤其涉及一种配电网仿真方法、系统、设备和计算机可读存储介质。
随着先进信息技术的快速发展及其在电力系统中的深度应用,电力基础网络和电力信息网络的联系日益紧密,新型电力系统已具备信息物理系统(Cyber Physical Systems,CPS)的特点,同时涉及电力系统、计算科学、网络通信、控制理论等多个学科。日益复杂的网络系统给传统电力系统的感知、分析、决策与控制等环节带来了严峻挑战。传统电力系统研究与信息系统研究在理论和方法上是割裂的,物理电力系统是连续变化的,其电气量已潮流形式流经电力节点和支路;信息通信系统则是离散系统,其信息变化由离散时间触发和驱动。
相关技术中的配电网信息物理系统融合建模方法,将通信信息的作用效果作为输入量考虑到物理过程中进行建模与控制,侧重将信息元素加入到传统的物理模型中,未全面考虑信息通信对物理系统的交互影响,降低了配电网信息物理系统的适应性。
发明内容
本发明实施例提供一种配电网仿真方法、系统、设备和计算机可读存储介质,提高了配电网信息物理系统的适应性。
本发明实施例的技术方案是这样实现的:
第一方面,本发明实施例提供一种配电网仿真方法,所述方法包括:根据配电网中信息系统与物理系统之间的模型差异性、交互影响,以及多场景仿真验证的规模和精度,进行多层级、多尺度的平台架构建模,得到仿真平台架构;在所述仿真平台架构上,根据所述配电网中所述物理系统与所述信息系统之间的耦合特性,对时变信息、非确定条件下的信息物理仿真系统进行融合建模,得到所述配电网信息物理系统;基于所述仿真平台架构,在所述物理系统、通信网络及所述信息系统的并发故障场景下,对所述配电网信息物理系统进行实时仿真,确定所述配电网的故障仿真结果;所述故障仿真结果用于向所述配电网信息物理系统的故障隔离决策和故障恢复决策提供支持;基于所述仿真平台架构,利用可靠性评估指标对所述配电网信息物理系统进行可靠性仿真评估,确定所述配电网的可靠性仿真结果。
第二方面,本发明实施例提供一种配电网仿真系统,所述系统包括:平台搭建部分,被配置为根据配电网中信息系统与物理系统之间的模型差异性、交互影响,以及多场景仿真验证的规模和精度,进行多层级、多尺度的平台架构建模,得到仿真平台架构;融合部分,被配置为在所述仿真平台架构上,根据所述配电网中所述物理系统与所述信息系统之间的耦合特性,对时变信息、非确定条件下的信息物理仿真系统进行融合建模,得到所述配电网信息物理系统;故障仿真部分,被配置为基于所述仿真平台架构,在所述物理系统、通信网络及所述信息系统的并发故障场景下,对所述配电网信息物理系统进行实时仿真,确定所述配电网的故障仿真结果;所述故障仿真结果用于向所述配电网信息物理系统的故障隔离决策和故障恢复决策提供支持;可靠性仿真部分,被配置为基于所述仿真平台架构,利用可靠性评估指标对所述配电网信息物理系统进行可靠性仿真评估,确定所述配电网的可靠性仿真结果。
第三方面,本发明实施例提供一种配电网仿真设备,所述设备包括:存储器,被配置为存储可执行计算机程序;处理器,被配置为执行所述存储器中存储的可执行计算机程序时,实现上述配电网仿真方法。
第四方面,本发明实施例提供一种计算机可读存储介质,存储有计算机程序,被配置为被处理 器执行时,实现上述配电网仿真方法。
本发明实施例提供了一种配电网仿真方法、系统、设备和计算机可读存储介质。根据本发明实施例提供的方案,根据配电网中信息系统与物理系统之间的模型差异性、交互影响,以及多场景仿真验证的规模和精度,进行多层级、多尺度的平台架构建模,得到仿真平台架构,增加了仿真平台的灵活加载功能、实时同步通信功能和功能构建功能,可以实现事件驱动与连续时间响应的配电网信息物理系统协同仿真。在仿真平台架构上,根据配电网中物理系统与信息系统之间的耦合特性,对时变信息、非确定条件下的信息物理仿真系统进行融合建模,得到配电网信息物理系统,通过多场景、多分辨率、多响应时间尺度下模型构建,提高了配电网信息物理系统的多样性。基于仿真平台架构,在物理系统、通信网络及信息系统的并发故障场景下,对配电网信息物理系统进行实时仿真,确定配电网的故障仿真结果;故障仿真结果用于向配电网信息物理系统的故障隔离决策和故障恢复决策提供支持,满足了配电网信息物理系统的多场景仿真分析的需求。基于仿真平台架构,利用可靠性评估指标对配电网信息物理系统进行可靠性仿真评估,确定配电网的可靠性仿真结果,为配电网可靠性提高提供了理论支撑与决策辅助,维护了配电网的稳定可靠运行,提高了配电网信息物理系统的适应性。
图1为本发明实施例提供的一种配电网仿真方法的可选的步骤流程图;
图2为本发明实施例提供的一种基于动态相量法的配电混合网等值建模的可选的流程图;
图3为本发明实施例提供的一种防火墙模型Petri网模型的可选的示意图;
图4为本发明实施例提供的一种密码模型的可选的示意图;
图5为本发明实施例提供的一种伪造身份认证攻击过程模型的可选的示意图;
图6为本发明实施例提供的一种端口管理Petri网模型的可选的示意图;
图7为本发明实施例提供的一种虚假数据注入攻击信息网络Petri网模型的可选的示意图;
图8为本发明实施例提供的一种含虚假拉合闸命令的攻击过程Petri网模型的可选的示意图;
图9为本发明实施例提供的一种配电网信息物理系统融合建模的可选的流程图;
图10为本发明实施例提供的一种配电网信息物理仿真平台总体架构的可选的示意图;
图11为本发明实施例提供的一种配电网信息物理系统快/中/慢动态元件分类的可选的示意图;
图12为本发明实施例提供的一种分解优化模型的可选的示意图;
图13为本发明实施例提供的一种配电网信息物理系统网络解耦的可选的示意图;
图14a为本发明实施例提供的一种元件与网络间的等效模型的可选的示意图;
图14b为本发明实施例提供的另一种元件与网络间的等效模型的可选的示意图;
图15为本发明实施例提供的一种基于插值法的仿真数据更新模式的可选的示意图;
图16a为本发明实施例提供的一种多时间尺度信息交互的可选的示意图;
图16b为本发明实施例提供的另一种多时间尺度信息交互的可选的示意图;
图17为本发明实施例提供的一种自适应步长调整的数据交互模块的可选的示意图;
图18为本发明实施例提供的一种最大仿真步长计算的可选的示意图;
图19为本发明实施例提供的一种仿真步长自适应机制的可选的示意图;
图20为本发明实施例提供的一种配电网信息物理仿真算例分析的可选的示意图;
图21为本发明实施例提供的一种基于蒙特卡洛方法的配电网信息物理系统可靠性分析评估的可选的流程图;
图22a为本发明实施例提供的一种串联式单元可靠性的可选的框图;
图22b为本发明实施例提供的一种并联式单元可靠性的可选的框图;
图22c为本发明实施例提供的一种表决式单元可靠性的可选的框图;
图23为本发明实施例提供的一种配电网仿真系统的可选的结构示意图;
图24为本发明实施例提供的一种配电网仿真设备组成结构示意图。
下面将结合本发明实施例中的附图,对本发明实施例中的技术方案进行清楚、完整地描述。应 当理解的是,此处所描述的一些实施例仅仅用以解释本发明的技术方案,并不用于限定本发明的技术范围。
为了更好地理解本发明实施例中提供的配电网仿真方法,在对本发明实施例的技术方案进行介绍之前,先对应用背景和相关技术进行说明。
电力信息物理系统需要研究如何深度融合电力系统与信息系统,探索交互影响机理,研究与之相适应的建模、分析与控制方法,并指导实际电力系统的应用。然而,在相关技术的理论方法与框架下,难以深入分析信息系统对电力系统分析与控制的影响,相关电力系统架构已经不再使用,因此,需要对电力信息物理系统的架构体系进行研究。示例性的,可以根据电力信息物理系统原型特征构造其模型以支撑相关计算、仿真,进而实现对相关理论、应用问题研究的辅助、测试、验证等目,并且准确构建包含信息侧与物理侧常用元件、设备、系统、事件流、信息流、接口等的模型库,建立兼容电力系统离散时步仿真体系与信息通信系统事件队列仿真体系的信息融合仿真方法。
对于电力系统,可以包括输电网与配电网。其中,配电网更贴近于用户,同时由于近年来清洁能源与新型负荷的接入,配电网拓扑复杂多变、节点规模庞大、源荷波动性、随机性强的特点更加显著。为进一步加强对配电系统的观测与控制,随着量测技术、通信技术、计算机技术的发展,配电网络中的测点数量、测量数据量、通信数据量、控制指令数据量均呈现指数级的增长,因此,需要对配电系统信息物理融合程度进行研究。
配电网信息物理系统融合建模方法可以从以下三个方面展开:(1)将通信信息的作用效果作为输入量考虑到物理过程中进行建模与控制,侧重将信息元素加入到传统的物理模型中,但该种思想未能全面考虑信息通信对物理系统的影响。(2)信息物理交互影响过程分析与控制,侧重针对闭环控制过程中解决离散信息过程和连续物理过程之间的交互影响建模、分析与控制。该种方法更加侧重于对信息映射关系的描述,但缺乏信息侧对物理侧影响传播过程及影响结果的研究。(3)信息物理耦合过程的建模与分析,侧重对信息物理耦合特性(包括路径、性能)的建模、定量分析与控制。但目前此方面的研究方法多针对业务,建模与分析方法没有形成完整的框架体系,适应性不足。
对于配电网信息物理仿真平台架构体系方面,传统仿真工具通常采用离散时步对系统当前状态进行相对精确的估计。而信息通信系统仿真工具通常采用离散状态模型对网络在离散参数和事件进行描述,将复杂的通信过程转化为事件队列,通过离散事件仿真工具进行模拟。由于两个系统在数学模型上的本质区别,因此需要一套完整可靠的统一仿真软件。相关技术中存在不同架构的联合仿真平台方案。从平台组成结构,这些方案可分为以下三类:(1)联立仿真:联立仿真方案的思想是在单一仿真工具(电力系统仿真工具或通信系统仿真工具)中建立一个复杂的电力和信息通信复合系统模型。这种方法的关键在于在电力(或通信)系统仿真工具中搭建通信(或电力)系统模型。其优势在于,由于是在同一个仿真工具中运行,两个系统模型处于同一时间域,因此不需要额外的时间同步工作。虽然这类方案不需要面对时间同步问题,但无法处理动力学DAE系统复杂的时间连续的动态问题建模及机电特性仿真。(2)非实时混合仿真:电力通信复合系统仿真的另一个解决方案是采用混合仿真。两个系统的建模工作仍采用其各自的专业仿真软件完成,通过时间同步方法使两个软件能够运行于同一时间域。这也是当前电力和信息通信复合系统仿真平台的研究方向。但该方法涉及的软件接口、数据交互和仿真时间同步等问题仍未能得到合理的解决。(3)实时混合仿真:电力和信息通信系统均采用能够实时运行的仿真软件,因此形成在物理时间域上的天然同步。这类仿真方案与非实时混合仿真的区别是采用多处理器分布式实时仿真平台,能够在实时范围内对系统动态特性进行精确模拟。实时混合仿真方案面向的应用与非实时混合仿真类似,但能够更高效的得到精确结果。但是,该平台的建设复杂程度高、消耗资源多。
在配电网信息物理系统仿真方面,相关技术中研究其应用时,大部分集中在电力和通信等基础设施关联性研究以及电力系统和通信系统的交互影响、电力系统的安全稳定性研究。研究电力和通信等基础设施关联性,往往采用大粒度,大时间同步间隔,用于分析电力行业的基础设施和通信基础设施间交互作用和相互依存关系的问题。研究电力系统和通信系统的交互影响,分析电力系统的安全稳定性,这类仿真系统是面向电力行业的专业性仿真,其仿真颗粒度小、仿真同步时间间隔小(毫秒级或秒级),可以为电力系统的控制和管理做决策。与上述仿真系统不同,这类仿真系统还没有相应的成熟产品,相关系统的开发还处于研究和完善的过程中。
本发明实施例提供一种配电网仿真方法,如图1所示,图1为本发明实施例提供的一种配电网仿真方法的步骤流程图,该方法是一种信息物理深度融合的配电网仿真方法,应用于配电或用电的装置及系统,配电网仿真方法包括以下步骤:
S101、根据配电网中信息系统与物理系统之间的模型差异性、交互影响,以及多场景仿真验证 的规模和精度,进行多层级、多尺度的平台架构建模,得到仿真平台架构。
在本发明实施例中,针对配电网信息物理融合仿真平台架构研究匮乏的现状,考虑配电网中信息系统和物理系统之间的交互影响及多场景仿真验证的规模和精度,提出映射实际电网信息物理系统的多层级、多尺度综合仿真平台架构,为配电网信息物理系统故障分析和可靠性评估等场景提供了技术保障。
S102、在仿真平台架构上,根据配电网中物理系统与信息系统之间的耦合特性,对时变信息、非确定条件下的信息物理仿真系统进行融合建模,得到配电网信息物理系统。
在本发明实施例中,针对配电网及其中新型设备信息物理融合模型构建困难的问题,面向物理系统,提出了基于有限状态机的配电混合网信息物理融合建模技术和交互元件的多分辨率多层次柔性模型构建方法,形成支撑不同模态配电网运行的仿真模型库;面向通信网络,提出了支撑物理信息系统交互的通信网络物理层和数据链路层模型、可扩展的通信应用层模型、关键事件流和信息流过程模型的构建方法,形成支持多种典型协议的跨应用、跨节点数据流模型库;面向信息系统,构建了涵盖网络防护单元和网络攻击路径的信息系统模型。实现了时变信息、非确定条件下配电网信息物理模型的构建,具有灵活性好、精度高和自适应性强的特点,可为信息物理深度融合的配电网仿真系统高级应用提供多时空尺度模型支撑。
S103、基于仿真平台架构,在物理系统、通信网络及信息系统的并发故障场景下,对配电网信息物理系统进行实时仿真,确定配电网的故障仿真结果;故障仿真结果用于向配电网信息物理系统的故障隔离决策和故障恢复决策提供支持。
S104、基于仿真平台架构,利用可靠性评估指标对配电网信息物理系统进行可靠性仿真评估,确定配电网的可靠性仿真结果。
在本发明实施例中,面向基于信息物理系统的多场景仿真分析迫切需求,基于所构建配电网信息物理系统模型及所设计的仿真平台架构,采用仿真分解协调技术、多速率实时仿真方法和计算速度动态调节方法,提出物理系统、通信网络及信息系统并发故障场景下配电网物理节点实时仿真方法,为配电网信息物理系统故障隔离和故障恢复提供技术和辅助决策支撑;构建了配电网物理系统与信息系统的可靠性评价指标,提出了配电网信息物理系统可靠性仿真分析方法,实现了系统可靠性精准量化分析与提升。
本发明实施例面向新型电力系统,提出一种集成信息物理融合建模、仿真平台架构构建、故障仿真及可靠性仿真等功能的配电网信息物理深度融合仿真系统。考虑配电网物理系统与信息系统之间耦合特性,实现时变信息、非确定条件下的配电网信息物理融合建模;考虑配电网信息系统与物理系统的模型差异性及交互延时性,实现配电网信息物理系统多层级、多尺度综合仿真平台的构建;通过物理系统、通信网络及信息系统并发故障场景下配电网物理节点的仿真,为配电网信息物理系统故障隔离和故障恢复提供技术和辅助决策支撑;通过配电网信息物理系统的可靠性仿真评估,实现系统可靠性精准量化分析与提升。
根据本发明实施例提供的方案,根据配电网中信息系统与物理系统之间的模型差异性、交互影响,以及多场景仿真验证的规模和精度,进行多层级、多尺度的平台架构建模,得到仿真平台架构,增加了仿真平台的灵活加载功能、实时同步通信功能和功能构建功能,可以实现事件驱动与连续时间响应的配电网信息物理系统协同仿真。在仿真平台架构上,根据配电网中物理系统与信息系统之间的耦合特性,对时变信息、非确定条件下的信息物理仿真系统进行融合建模,得到配电网信息物理系统,通过多场景、多分辨率、多响应时间尺度下模型构建,提高了配电网信息物理系统的多样性。基于仿真平台架构,在物理系统、通信网络及信息系统的并发故障场景下,对配电网信息物理系统进行实时仿真,确定配电网的故障仿真结果;故障仿真结果用于向配电网信息物理系统的故障隔离决策和故障恢复决策提供支持,满足了配电网信息物理系统的多场景仿真分析的需求。基于仿真平台架构,利用可靠性评估指标对配电网信息物理系统进行可靠性仿真评估,确定配电网的可靠性仿真结果,为配电网可靠性提高提供了理论支撑与决策辅助,维护了配电网的稳定可靠运行,提高了配电网信息物理系统的适应性。
在一些实施例中,上述图1中S102还可以包括S1021-S1025。
S1021、基于配电网络动态等值模型和支撑不同模态配电网运行的仿真模型库,构建物理系统模型。
在一些实施例中,上述S1021中支撑不同模态配电网运行的仿真模型库可以通过以下方式实现:基于有限状态机的配电混合网信息物理融合建模方法和物理侧交互元件的多分辨率多层次柔性模型构建方法,形成支撑不同模态配电网运行的仿真模型库。
在本发明实施例中,物理系统模型包括配电网络动态等值模型、物理侧交互元件的多分辨率多层次柔性模型和支撑不同模态配电网运行的仿真模型库,以下分别进行说明。
在本发明实施例中,对于配电网络动态等值模型,考虑大规模电力系统仿真精度和求解规模的矛盾,提出基于动态相量法的配电混合网等值建模方法,如图2所示,图2为本发明实施例提供的一种基于动态相量法的配电混合网等值建模的可选的流程图,建模方法的步骤包括S11-S18。
S11、选择系统阶数,初始化。
选择系统阶数,并设置各个计算量的初值。
S12、构造动态相量网络导纳矩阵。
S13、检测网络拓扑是否改变,若改变,则执行S12,即需要修改网络导纳矩阵,若未改变,则执行S14。
S14、计算电压数值(当前时刻的电压数值),并进行时域到动态相量域的转换。
S15、网络求解。
已知上一时刻的电压电流方程的电流动态相量值和此刻的已知电压量,通过降阶的动态相量方程,分别计算节点电压的各阶动态相量值。
S16、更新动态相量值,由节点电压量求出所有支路的电流。
S17、各阶动态相量域到时域的转换
对各阶动态相量值进行从量域到时域的转换。
S18、检测是否达到仿真结束时刻。若是,则仿真结束,若否,即未达到结束时刻,则向前推移一个时间步长,返回S13继续循环执行S13-S18。
在本发明实施例中,物理侧交互元件的多分辨率多层次柔性模型包括交互元件的高分辨率模型和低分辨率模型。交互元件高分辨率建模可以采用状态空间法,其包括基于对象运行物理规律建立的模拟模型和基于对象输入输出实测数据建立的数字模型。交互元件低分辨率建模可以采用开关周期平均建模法,为针对建模对象建立其开关模型,然后对开关模型在一个开关周期进行平均获得。
在本发明实施例中,支撑不同模态配电网运行的仿真模型库可以基于配电网混合网络的动态等值建模方法与多分辨率多层次柔性建模技术构建,模型库索引如下:(1)模型库一级目录可以有配电网设备模型、负荷模型、电力电子设备模型和分布式电源模型等。(2)配电网设备模型下的二级目录可以有线路、变压器、断路器、熔断器、杆塔/支架、分段开关、隔离开关、智能终端、避雷器、互感器、电机等配电网中典型设备的模型。(3)负荷模型下的二级目录可以有恒阻抗负荷、恒功率负荷、恒流模型、多项式模型等配电网常用负荷的模型。(4)电力电子设备模型二级目录可以有整流器、逆变器、斩波器、交-交变换器等典型电力电子变换设备的模型。(5)分布式电源模型二级目录可以有光伏发电、风力发电、小型水电、燃气轮机、储能设备、恒功率电源、V/F控制型电源等现有配电网常用分布式电源的模型。
S1022、基于支持多种典型协议的跨应用、跨节点的数据流模型库,构建通信网络模型。
在一些实施例中,上述S1022中支持多种典型协议的跨应用、跨节点的数据流模型库可以通过以下方式实现:根据用于支撑物理信息系统交互的通信网络物理层模型和数据链路层模型、通信应用层模型、关键事件流和信息流过程模型的构建方法,形成支持多种典型协议的跨应用、跨节点的数据流模型库。
在本发明实施例中,通信网络模型包括支撑物理信息系统交互的通信网络物理层和数据链路层模型、可扩展的通信应用层模型、关键事件流和信息流过程模型以及支持多种典型协议的跨应用、跨节点数据流模型库,以下分别进行说明。
在本发明实施例中,通信网络物理层模型包括同步数字体系(Synchronous Digital Hierarchy,SDH)网络物理层模型和无线专网物理层模型。其中,SDH网络物理层模型可以基于网络仿真技术软件包(例如,OPNET)中已有的信道模型进行派生。无线专网物理层模型可以基于OPNET软件构建,可以包括九个阶段:接收器组计算阶段;传输时延阶段;链路封闭性计算阶段;发送天线增益阶段;传播时延阶段;接收天线增益阶段;接收功率计算阶段;背景噪声功率计算阶段;干扰噪声功率计算阶段。
在本发明实施例中,数据链路层建模基于OPNET软件构建,可以包括5个阶段:链路匹配阶段;信噪比计算阶段;误码率计算阶段;误码数目分配阶段;纠错阶段。
在本发明实施例中,可扩展的通信应用层模型构建步骤包括:自定义任务建模、应用模型设定和角色设定。
在本发明实施例中,对于关键事件流和信息流过程模型,以分布式拒绝服务攻击(Distributed Denial of Service,DDOS)为例,配电网信息物理系统关键事件流和信息流过程模型构建步骤包括:搭建DDOS场景、配置攻击配置文件(Attack Profiles)、配置影响脚本(Effect Scripts)、配置补救措施概要文件(Remedy Profiles)、设置统计量和运行仿真。
在本发明实施例中,支持多种典型通信协议的跨应用、跨节点数据流模型库基于OPNET软件开发,其步骤可以包括:修改环仿真(software in the loop,SITL)模块代码、构建控制节点、修改终端节点模型和定义数据包结构。
S1023、基于通信网络模型,对多源信息进行预处理,结合信息网络安全模型,构建信息系统模型。
在本发明实施例中,信息系统模型包括配电网信息物理系统多源信息预处理、信息网络安全模型。其中,多源信息预处理包括传感器数据预处理、网络数据预处理以及多状态信息控制模型构建。传感器数据预处理和网络数据预处理均包括异常数据检测和异常数据修正。多状态信息控制模型可通过多状态马尔科夫(Markov)模型来表达,可以包括以下步骤:确定每个单一状态的统计模型;建立移动通信信道Markov模型。
在本发明实施例中,移动通信信道Markov模型可描述成转移矩阵P和状态向量S,n状态的Markov转移矩阵如公式(1)所示。
上述公式(1)中,pij表示由状态i转移到状态j的转移概率且满足公式(2)。
状态向量S=[s
1,s
2,…,s
n],由于此时的Markov链是非周期、不可约的,它的稳态分布存在且等于极限分布,可得到公式(3)。
SP=S (3)
在上述公式(3)中,稳态分布表示状态向量S与转移矩阵P之间的乘积等于状态向量S。
在本发明实施例中,网络安全模型包括网络防护单元模型和网络攻击路径模型。其中,网络防护单元模型基于Petri网构建,包括防火网模型、密码模型、认证模型和网络设备配置管理模型,以下分别进行说明。
在本发明实施例中,对构建网络防护模型进行说明,网络防护模型也可以称为防火墙模型Petri网模型,如图3所示,图3为本发明实施例提供的一种防火墙模型Petri网模型的可选的示意图,图3中示出了多种不同方式的入侵尝试。模型每个瞬时变迁都附加了一个防火墙渗透概率,其值可由防火墙日志计算得出。恶意包经由每条规则通过防火墙的概率可由公式(4)计算。
上述公式(4)为防火墙i处经策略规则j通过的恶意包(即图3中通过防火墙的恶意包),其中
表示通过防火墙的频率,
是防火墙规则j的总记录数。f
i
fr是被拒绝的包的数量,
是防火墙记录的总数。防火墙执行速度
是每秒执行的指令数,可用于估计验证规则和通过防火墙的时间。平均响应速度
取决于网络传输状况。
在本发明实施例中,对构建密码模型进行说明,密码模型由两部分组成:登录尝试概率和响应速度,其模型如图4所示,图4为本发明实施例提供的一种密码模型的可选的示意图。
侵入尝试可用一个变迁概率表示,变迁概率可由下公式(5)进行描述。
在本发明实施例中,对构建认证模型进行说明,以USB关键信息(key)作为加密硬件为例建 立认证模型,经USB key硬件加密的身份认证典型过程如下:初始化阶段,服务器和终端用户通过安全的方式共享存有Key的硬件;运行中,进行身份认证时,服务器产生随机数发给终端,终端进行散列运算并把结果发回服务器;服务器将储存的Key和随机数进行散列运算并与收到的结果比较,结果一致则说明通过认证。
在本发明实施例中,参照此身份认证过程,建立如图5的硬件加密身份认证攻击模型,图5为本发明实施例提供的一种伪造身份认证攻击过程模型的可选的示意图。其中,图5中的λ
s表示以各种手段偷取一个系统内已在使用的USB key硬件所需要的时间,λ
c表示复制一个新的USB key硬件所需要的时间,λ
f表示系统更换USB key硬件的周期。λ
r表示成功获取到一个服务器发来的随机数需要的时间,λ
a表示服务器校验终端发回信息所需要的时间。
在本发明实施例中,对构建网络设备配置管理模型进行说明,考虑攻击者可能采取的攻击方法步骤,建立如图6所示端口管理Petri网模型,图6为本发明实施例提供的一种端口管理Petri网模型的可选的示意图。图6中的p
v表示闲置端口没有被关闭的概率,p
t表示取得了正常工作端口的使用权限,通过正常端口可以发送恶意攻击包的概率,p
f示端口管理机制没有出现漏洞被攻击者利用的情况的概率。
在本发明实施例中,网络攻击路径建模包括虚假信息注入攻击建模和伪造指令攻击建模。其中,虚假数据注入攻击模型如图7所示,图7为本发明实施例提供的一种虚假数据注入攻击信息网络Petri网模型的可选的示意图。虚假数据的传输从终端层开始上传主站的过程中,经过了变电站与终端间防火墙、主站与变电站间防火墙以及纵向加密认证设备,将这些防护设备的Petri网模型串联,可得虚假数据注入攻击传播过程的Petri模型。伪造指令攻击模型如图8所示,图8为本发明实施例提供的一种含虚假拉合闸命令的攻击过程Petri网模型的可选的示意图。以虚假拉闸命令为例,伪造指令攻击流程可以有:获取拉闸命令的密文;建立与表计的通信,通过无线网络等获取表计处接入网线;发出命令报文。
S1024、基于关联矩阵、物理系统模型、通信网络模型和信息系统模型,进行系统融合建模,得到融合系统。
S1025、基于设备的有限状态机和系统的有限状态机,分别对融合系统中设备的有限状态机模型和系统的有限状态机模型进行构建,得到配电网信息物理系统。
在本发明实施例中,在构建物理系统模型、通信网络模型和信息系统模型之后,对信息物理系统融合建模进行说明,配电信息物理融合建模包括基于关联矩阵的系统融合建模和基于有限状态机的信息物理系统建模,以下分别进行说明。
在本发明实施例中,基于关联矩阵的信息物理系统融合建模可以通过以下方式实现。(1)针对配电网信息物理系统,分别构建其物理矩阵P、通信网络矩阵C、二次设备网矩阵S和信息控制矩阵I。(2)基于通信网络和二次设备之间的关联关系,建立二次设备层网络模型。(3)基于物理系统与二次设备之间的关联关系,建立二次设备-物理节点关联模型;基于信息系统与二次设备之间的关联关系,建立二次设备-信息节点关联模型。(4)综合物理矩阵P,通信网络矩阵C,二次设备网矩阵S、信息控制矩阵I,以及它们之间的关联矩阵,构建配电网信息物理融合模型(即配电网信息物理系统)。
在本发明实施例中,基于有限状态机的信息物理系统建模包括设备的有限状态机模型和系统的有限状态机模型。设备的有限状态机模型可以通过以下方式实现。(1)分析配电网中设备有限状态集合及其工作特性,包括其工作状态(例如启动、停运、异常等)、运行特性与输入/输出量,并定义各类工作状态的函数表达式。(2)分析电力及信息各类设备在不同外部驱动条件下的状态转换规则,定义设备级模型与系统级模型的接口变量,通过接口变量实现对设备级模型的事件驱动。(3)基于有限状态机理论定义设备的各类属性,包括有限状态集合、各状态下的工作函数集合、状态转换规则、状态迁移函数、初始状态集合等,构建设备的有限状态机模型。
在本发明实施例中,系统的有限状态机模型可以通过以下方式实现。(1)依据配电网信息物理系统的通信拓扑、电网一次拓扑、信息节点-二次节点-一次节点之间的业务连接,构建信息设备的有限状态机模型与物理设备的有限状态机模型之间的静态网络拓扑。(2)依据设备有限状态机模型在不同工作状态下的工作函数,定义有限状态机网络中各有向边的量化权重;依据有限状态机模型的状态转换规则,设计有限状态机网络中各节点的状态迁移规则。(3)依据特定业务场景的业务规则,对有限状态机网络中非必要设备和连接关系进行约减,再将配电网信息物理系统运行的初始参数输入到有限状态机网络,构建系统有限状态机模型。
在本发明实施例中,配电网信息物理系统融合建模方法整体流程如图9所示,图9为本发明实施例提供的一种配电网信息物理系统融合建模的可选的流程图。其中,物理系统建模包括基于动态相量法的配电混合网等值仿真建模、交互元件的多分辨率多层次柔性模型和支撑不同模态配电网运行的仿真模型库;通信网络建模包括通信网络物理层模型、数据链路层模型、事件流和信息流过程模型;信息系统建模包括多源信息预处理、网络防护单元模型和网络攻击路径模型。然后,在物理系统建模、通信网络建模和信息系统建模的基础上,基于时空关联矩阵的信息物理系统融合建模;以及基于有限状态机的信息物理系统建模。
在本发明实施例中,构建了配电网信息物理系统融合仿真模型,包括基于有限状态机的配电混合网信息物理融合模型、配电网交互元件多分辨率多层次柔性模型;支撑物理信息系统交互的通信网络物理层和数据链路层模型、可扩展的通信应用层模型、关键事件流和信息流过程模型;涵盖网络防护单元模型和网络攻击路径模型的信息系统模型。解决了配电网信息物理系统多场景、多分辨率、多响应时间尺度下模型构建的技术问题,为后续信息物理深度融合高级仿真应用提供模型支撑,提高了配电网信息物理系统的适应性。
在一些实施例中,仿真平台架构包括模型层、数据层、算法层、接口层和业务层;接口层用于连接配电网的物理侧与信息侧;该配电网仿真方法还包括以下步骤:在模型层中,针对配电网的物理侧,采用平均化方法与动态相量法进行模型构建,得到配电网络动态等值模型;针对配电网的信息侧,采用脚本方法,对关键事件流和信息流进行模型构建,得到关键事件流和信息流过程模型;并构建通信网络物理层模型、数据链路层模型、通信应用层模型和信息网络安全模型;在数据层中,对模型构建过程和仿真过程中的数据进行数据采集、数据处理和数据存储;业务层包括仿真功能模块和应用场景验证模块,仿真功能模块用于支持配电网信息物理系统的暂态仿真功能、配电网信息物理系统的稳态仿真功能、通信网络及通信网络故障仿真功能;场景验证模块用于支持配电网信息物理系统的并发故障场景验证、配电网信息物理系统的可靠性分析仿真、配电网的信息侧攻击与故障场景验证。
在一些实施例中,基于上述仿真平台架构中的模型层、数据层、算法层、接口层和业务层,上述图1中S103还可以通过以下方式实现。在算法层中,采用仿真网络分解协调技术、多速率并行实时仿真方法和计算速度动态调节方法,在物理系统、通信网络及信息系统的并发故障场景下,对配电网物理节点进行实时仿真,确定配电网的故障仿真结果。
在本发明实施例中,配电网信息物理仿真平台总体架构采用分层架构模式,可以包括模型层、数据层、算法层、接口层、业务层,同时包含平台管控模块和应用程序界面(Application Program Interface,API)接口模块,如图10所示,图10为本发明实施例提供的一种配电网信息物理仿真平台总体架构的可选的示意图。
在本发明实施例中,模型层用于提供配电网信息物理融合仿真所需的物理模型、通信模型和信控模型;在物理侧,采用平均化思想与动态相量法进行模型构建,可在兼顾仿真计算精度的前提下,提升计算速度与效率,优化计算资源;在通信侧采用脚本的方式对关键事件流和信息流进行模型构建。
在本发明实施例中,数据层包括数据采集模块、数据处理与管理模块、数据转换模块与数据存储模块。其中,数据采集模块的功能可以是与PMS3.0平台、数据采集与监视控制系统(Supervisory Control And Data Acquisition,SCADA)、用采系统等数据采集系统相连并为信息物理仿真平台采集所需数据;数据处理与管理模块的功能可以是针对现有配电网数据来源多、种类多、精度差等问题进行数据异常辨识与数据修复;数据转换模块的功能可以是将所采集之不同格式、不同形式的数据转换为本仿真平台可识别的格式;数据储存模块的功能可以是将外来采集数据、内部计算结果数据、模型数据等数据进行存储,由图形库和属性数据库组成,存储于Oracle/Access数据库内,提供基础支撑系统与基础通用数据服务,数据持久化、数据库访问能力,供平台层调用。
在本发明实施例中,算法层包括配电网信息物理仿真计算速度动态调节模块、多速率并行仿真模块、配电网网络分解模块。其中,计算速度动态调节模块的功能可以是综合考虑计算精度、拓扑规模、计算速度,对计算步长进行实时选取,以获得计算精度与计算效率的最大收益;多速率并行仿真模块的功能可以是完成不同仿真步长需求的元件、设备、系统之间的数据、信息交互。该模块与计算速度动态调节模块相互配合,可实现计算资源的高效配置。配电网网络分解模块的功能可以是生成适合的分网原则、分网策略与分割接口算法,以实现大规模配电网拓扑的有效分解与并行计算。
在本发明实施例中,接口层用于提供配电网物理侧与信息通信侧之间的接口。
在本发明实施例中,业务层包括该仿真平台可实现的仿真功能模块及应用场景验证模块,仿真功能模块用于支持配电网信息物理系统暂态仿真功能、配电网信息物理系统稳态仿真功能、通信系统及其故障仿真等功能;场景验证模块用于支持配电网信息物理并发故障场景验证、配电网信息物理系统可靠性分析仿真、DDOS攻击、错误数据注入攻击(False Data Injection Attacks,FDIA)攻击等配电网信息侧攻击与故障场景验证。
在本发明实施例中,配电网信息物理系统稳态仿真功能通过以下方式实现,根据不同时段内负荷、分布式电源的不同功率值,定时按分时数据自动进行潮流计算。同时通过数据接口,实现潮流计算结果的同步。并且,监听主站下发的遥控变位、遥调等数据,实现云平台与主站的数据同步。可实现某一时间断面下的周期计算、故障计算、潮流计算、动态图绘制、负荷管理等功能。
在本发明实施例中,通信系统及其故障仿真功能通过以下方式实现,基于已构建、封装的通信系统及通信系统故障模型,可实现通信系统故障场景的快速创建与验证,复现通信系统故障的过程和效果,提高了配电网信息物理系统的适应性。
在本发明实施例中,配电网信息物理并发故障场景验证,可实现物理侧与信息通信侧同时发生故障的过程与效果重现。其中物理侧故障可实现三相接地短路故障、单相接地短路故障、相间短路故障、断线故障等常见故障,通信侧故障可实现DDOS攻击、FDIA攻击、病毒入侵等引起的故障以及通信链路中断、通信延时等常见故障。
在本发明实施例中,配电网信息物理系统可靠性分析仿真,可实现信息侧、物理侧单侧故障或信息物理并发故障的可能性分析,进而可获得对应不同故障类型的配电网信息物理系统可靠性分析结果。
在本发明实施例中,通过分析配电网信息物理系统仿真的特征,提出了配电网信息物理系统仿真架构技术,包括配电网信息物理系统仿真平台多层级映射关系以及一体化构建方案、配电网信息物理系统仿真平台功能体系以及计算架构,解决了配电网信息物理系统仿真子系统灵活加载、功能构建、同步与高速通讯、扩展API接口等问题,解决了事件驱动与连续时间响应的配电网信息物理系统仿真协同的技术问题,为电网安全稳定分析、可靠性分析评估、故障处置等场景验证与决策辅助提供了有力的基础保障,提高了配电网信息物理系统仿真平台的适应性。
在本发明实施例中,基于所构建配电网信息物理系统模型及所设计的仿真平台架构,采用仿真分解协调技术、多速率实时仿真方法和计算速度动态调节方法,提出了物理系统、通信网络及信息系统并发故障场景下配电网物理节点实时仿真方法,满足了信息物理系统的多场景仿真分析迫切需求,为配电网信息物理系统故障隔离和故障恢复提供技术和辅助决策支撑;提高了配电网信息物理系统及其仿真平台的适应性。
在一些实施例中,上述图1中S103还可以包括S1031-S1034。
S1031、根据不同元件动态响应时间或响应速度,对元件进行分类,得到各个元件的元件类型;其中,元件类型包括快类型、中间类型和慢类型,中间类型对应的仿真步长大于快类型对应的仿真步长,且小于或等于慢类型对应的仿真步长。
在本发明实施例中,针对目标配电网,按照其中元件的不同时间响应速度,将其分为快、中、慢三类,如图11所示,图11为本发明实施例提供的一种配电网信息物理系统快/中/慢动态元件分类的可选的示意图。
示例性的,快时间尺度仿真步长在10微秒-100微秒之间,代表元件有含电力电子元件的光伏等分布式电源、柔性电力电子设备等。中时间尺度的仿真步长在100微秒-1毫秒之间,代表元件有以柴油机、电动机为代表的旋转设备。慢时间尺度的仿真步长在毫秒以上,代表元件有电容器、电抗器、变压器、控制系统等不包含电力电子元件的电气系统其他元件。
S1032、对配电网中分类后的元件进行建模。
在本发明实施例中,采用上述所描述的配电网信息物理系统的建模方法,根据上述S102中所描述的配电网信息物理系统的构建方法,对所分类的配电网元件进行建模,得到包含各个元件的配电网信息物理系统中的物理网络。
S1033、对包含各个元件的配电网信息物理系统中的物理网络进行动态解耦,并建立等效模型。
在一些实施例中,S1033还可以通过以下方式实现。获取加载数据和中央处理器核心数量;根据加载数据和中央处理器核心数量进行暂态仿真,利用遗传算法,对计算线路的中央处理器数量和计算各个元件的中央处理器数量,进行分配,得到分配结果;分配结果包括各个中央处理器对应的节点类型、数量和所在的线路;根据分配结果,构建仿真任务分解模型;采用节点分裂法,对各个元件的配电网信息物理系统中物理网络对应的仿真任务分解模型,进行与各个元件的元件类型对应 的动态解耦,得到解耦后的模型;根据解耦后的模型,构建各个元件的网络间的等效模型和元件与网络之间的等效模型;等效模型包括网络间的等效模型和元件与网络之间的等效模型。
在本发明实施例中,配电网信息物理系统故障仿真模型的构建包括针对目标配电网,按照其中元件的不同时间响应速度,将其分为快、中、慢三类、配电网元件建模,以及配电网信息物理系统快/中/慢动态解耦。接下来对配电网信息物理系统快/中/慢动态解耦进行说明。
在本发明实施例中,在对配电网信息物理系统进行快/中/慢动态解耦时,仅针对物理网络进行快/中/慢动态解耦,并建立相应的等效模型。配电网信息物理系统快/中/慢动态解耦包括配电网信息物理系统仿真任务分解模型和配电网信息物理系统网络解耦。
在本发明实施例中,构建配电网信息物理系统仿真任务分解模型包括:构建分解优化模型和采用遗传算法等智能算法对优化模型进行求解,其中,优化流程如图12所示,图12为本发明实施例提供的一种分解优化模型的可选的示意图,分解优化步骤包括S21-S26。
S21、加载数据。
数据包括但不限于网络拓扑、馈线数、节点数和中央处理器(central processing unit,CPU)性能数据。
S22、用户输入。
用户输入包括但不限于参与计算的CPU核心数量(对应于中央处理器核心数量)。
S23、暂态仿真(对应于根据加载数据和中央处理器核心数量进行暂态仿真)。
S24、分配计算线路的CPU数和计算各暂态元件的CPU核心数。
S25、利用遗传算法计算暂态场景下各CPU核心仿真的不同类型节点数最优值(对应于利用遗传算法,对计算线路的中央处理器数量和计算各个元件的中央处理器数量,进行分配,得到分配结果)。
S26、输出分配结果。
分配结果包括但不限于各CPU参与计算的节点类型、数量及其所在馈线编号(对应于分配结果包括各个中央处理器对应的节点类型、数量和所在的线路)。
在本发明实施例中,在构建分解优化模型时,确定参与传统负荷节点计算的CPU核心个数和参与暂态节点计算的CPU核心个数如公式(6)所示。
上述公式(6)中,n
CPU为参与计算的CPU核心总数,
为参与传统负荷节点的CPU核心数,
为参与暂态计算的CPU核心数;n
1*为参与计算的传统负荷节点数,n
2*为参与计算的暂态节点数;
为将一个暂态模型等效成为的传统负荷节点数平均值。
若仿真系统内包含q种不同类型的暂态元件,且每种元件的个数分别为n
2k*(k=1,2,...,q),则参与每种暂态元件计算的CPU核心个数如公式(7)所示。
上述公式(9)中:P
1为第一级优化目标的权重系数,P
2为第二级优化目标的权重系数,P
1>P
2>0;m
ia为第i个CPU核心计算的首条馈线编号,m
ib为第i个CPU核心计算的末条馈线编号,n
i为第i个CPU核心最优计算量,n
i1*为本次迭代第i个CPU核心参与计算的传统负荷节点数,
m
ja为第j个CPU核心计算的首条馈线编号,m
jb为第j个CPU核心计算的末条馈线编号,n
j为第j个CPU核心最优计算量,n
kj2*为本次迭代第j个CPU核心参与计算的第k种暂态元件数,
约束条件为配电网信息物理系统的运行约束。
在本发明实施例中,在对配电网信息物理系统网络进行解耦时,可以采用节点分裂法对配电网信息物理系统网络进行解耦,如图13所示,图13为本发明实施例提供的一种配电网信息物理系统网络解耦的可选的示意图,包括S31-S38。
S31、选取分割节点,设置收敛判据δ,令k=1。
S32、输入子系统线路拓扑参数、负荷参数,计算ZIP模型三部分参数。
S33、考虑负荷恒阻抗部分,计算各子系统节点导纳矩阵。
需要说明的是,S33和S34的执行顺序不分先后,可以同时执行S33和S34,也可以先执行S33,然后执行S34,也可以先执行S34,然后执行S33,对此本发明实施例不做限制。
示例性的,配电网信息物理系统网络解耦包括以下步骤:(1)在保证子网的计算规模均衡前提下,选取网络中某些节点为分割节点,将网络分割为若干个相互独立的子系统,子系统间仅通过分割节点的联络支路电流进行信息交互。(2)针对各子系统,分别建立ZIP负荷模型,计算恒阻抗、恒电流、恒功率三部分参数,恒阻抗负荷部分参数用于求解节点导纳矩阵,恒电流、恒功率负荷部分参数用于求解节点注入电流相量。(3)计算各子系统的节点导纳矩阵,考虑到配电网节点导纳矩阵为奇异矩阵,采用本发明所提方法对节点导纳矩阵进行改进。(4)联立连接子系统之间的支路电流方程与子系统内部的节点电压方程求出子系统之间联络支路上的电流。(5)引入联络支路电流求出各子系统的节点电压相量,不断迭代直至相邻两次的联络支路电流差小于收敛判据。
S1034、采用仿真分解协调方法、多速率并行实时仿真方法和计算速度动态调节方法,对包含各个元件的物理网络等效模型进行故障实时仿真,确定配电网的故障仿真结果。
在本发明实施例中,配电网信息物理系统实时仿真方法包括仿真分解协调技术、多速率并行实时仿真方法和计算速度动态调节方法,接下来对这三种方法分别进行介绍。
在本发明实施例中,对于仿真分解协调技术,配电网信息物理系统的仿真分解协调技术包括仿真分解元件等效模型和快/中/慢数据协调方法,以下分别进行介绍。
在本发明实施例中,配电网信息物理系统的仿真分解元件等效模型包括网络间的等效模型和元件及网络间的等效模型。
示例性的,对于构建网络间的等效模型,记串联电压源端口为A类端口,用电流源代替,称作 电流端口;记并联电流源端口为B类端口,用电压源代替,称作电压接口。如果端口1至端口k为A类端口,端口k+1至端口m为B类端口,由叠加定理得到如下公式(10)。
上述公式(10)中u
A=[u
1…u
k]
T为A类端口等效电压;i
A=[i
1…i
k]
T为A类端口等效电流源;U
eq为A类端口串联电压源;i
B=[i
k+1…i
m]
T为B类端口等效电流;u
B=[u
k+1…u
m]
T为B类端口等效电压源;I
eq为B类端口并联电流源;H
AA、H
AB、H
BA、H
BB为端口的等效阻抗。
示例性的,对于构建元件与网络间的等效模型,针对线路侧子网和分布式电源子网提出基于不同接口电气量的网络等效模型。如图14a所示,图14a为本发明实施例提供的一种元件与网络间的等效模型的可选的示意图,图14a为以注入电流为协调变量的线路侧等效模型,其中,R表示电阻,i表示线路模型的电流,L表示电感,u
s表示电压,i
s为分裂节点处的外网等效注入电流,线路侧子网外特性表示如公式(11)所示。
示例性的,对于构建元件与网络间的等效模型,如图14b所示,图14b为本发明实施例提供的另一种元件与网络间的等效模型的可选的示意图,图14b为以节点电压为协调变量的分布式电源子网等效模型,其中,R(Resistance)表示电阻,u表示暂态元件模型的电压,L表示电感,u
s表示电压,u
s为分裂节点处的外网等效节点电压。分布式电源子网外特性表示如公式(12)所示。
在本发明实施例中,关于快/中/慢数据协调方法,由于并行计算的多子系统仿真步长不同,数据交互只能在最大仿真步长的整数倍时刻进行,使得小步长仿真系统难以得到每个时步开始时刻外部系统的仿真结果,难以保证信息交互的实时性。因此提出基于插值法的外部系统数据更新模式,实现快/中/慢数据的协调,如图15所示,图15为本发明实施例提供的一种基于插值法的仿真数据更新模式的可选的示意图。
在本发明实施例中,子系统1采用长仿真步长T
1,子系统2采用短仿真步长T
2,且T
1=mT
2,m为正整数。在t
n时刻,子系统1向子系统2传递自身在[t
n-2,t
n-1]时步内仿真结果x
n-1和在[t
n-1,t
n]时步内的仿真结果x
n;子系统2向子系统1传递自身在[t
n-1,t
n]时步内的仿真结果y
n。在[t
n,t
n+1]时步内,子系统1利用外部系统状态量y
n进行一次迭代计算;子系统2利用外部系统状态量x
n-1和x
n进行插值,根据公式(13)依次得到m个外部系统状态量x
n,1…x
n,m,进行m次迭代计算。
在本发明实施例中,子系统2在仿真过程所利用的外部系统数据滞后于子系统1单位仿真步长T
1,但其数据交互过程仍然具有实时性。
在本发明实施例中,对于多速率并行实时仿真方法,在同一仿真时段内对不同时间尺度元件采用不同仿真步长,配电网信息物理仿真系统多速率协调过程如图16a和图16b所示,图16a和图16b为本发明实施例提供的一种多时间尺度信息交互的可选的示意图。图16a中示出了被控对象(simulink)、通信网络(OPNET)和控制器(Matlab)之间的交互过程,结合图16b中所示出的各个执行主体之间分别在快/中/慢不同类型的协调过程中时间(包括t
1、t
2…t
n)上的交互。其中,被控对象和控制器均是经过量测数据打包、用户数据报协议(UDP,User Datagram Protocol)、sitl接口、UDP传输协议、控制信号解码。通信网络通过sitl接口与被控对象进行交互,并通过另一个sitl接口与控制器进行交互,子系统1、子系统2分别采用短步长和中步长对不同类型暂态元件进行仿真;子系统3包含馈线上的全部传统负荷节点,采用长步长仿真。
示例性的,由于不同暂态元件通常动态响应速度不同,其跟踪系统状态变化的能力也不同,因此,本发明实施例提出一种自适应变步长的多速率并行仿真技术,子系统内部自适应调整仿真步长,各子系统采用多种仿真步长并行仿真,在不大幅增加资源消耗量的基础上加速系统的暂态响应,保证各子系统的安全稳定运行。
示例性的,在整个仿真过程中,如果子系统2的仿真步长不断发生变化,但双侧子系统仿真步长仍然满足T
1=mT
2、m为正整数的关系,根据插值算法,利用延时模块记录子系统1上一仿真步长结束时刻的系统状态值,采用三角波发生器完成每个大步长内插值系数
的计算,使子系统2能够在每一时步初始时刻得到经过更新的对侧子系统状态,并开始下一轮迭代计算。
示例性的,如图17所示,图17为本发明实施例提供的一种自适应步长调整的数据交互模块的可选的示意图,From3中的V
in表示子系统1按大步长间隔输出的电压状态量,Goto中V
out表示子系统2经插值计算后得到的对侧子系统状态量。图17中Transport Delay表示传输时延,Repeating Sequence表示周期序列,Add和Add1表示加法器,Divide表示分配器。图17示出的信号变换过程针对子系统2的变步长仿真具有普适性,且能够实现双侧子系统间仿真数据的实时交互,解决步长不匹配等技术问题。
在本发明实施例中,对于计算速度动态调节方法,为满足仿真的高精度和高实时性的要求,引入计算速度动态调节,即变步长。因此,配电网信息物理系统仿真计算速度动态调节方法包括仿真步长综合优化目标函数设计和仿真步长自适应适应机制。
示例性的,对于仿真步长综合优化目标函数设计,最大仿真步长的求解算法流程图如图18所示,图18为本发明实施例提供的一种最大仿真步长计算的可选的示意图。图18中AC(Alternating Current)表示交流,图18中数字侧的微分方程
表征如公式(14)所示。
设其步长为h,采用前向欧拉法做数值积分,得到的y
n+1如公式(15)所示。
y
n+1=y
n+hf
1(y
n,u
n,i
n) (15)
i
n=i
n-τ/h (16)
在公式(16)中,τ为延时。则系统总的方程z=f(x,y)描述如公式(17)所示。
上述公式(17)可简写为如公式(18)。
X
n+1=X
n+1-k+hf(y
n,u
n,i
n) (18)
假定接口为纯迟延系统,不考虑其误差,由上式可得公式(19)所示。
上述公式(19)中,e表示积分误差。若要求数值稳定则需要满足公式(20)。
据上述公式(20)可得仿真步长的h
1。其截断误差如公式(21)所示。
由上式可得仿真步长h
2。h
1和h
2的公共部分即为仿真步长的运行方位,其上界(即h
1max和h
2max二者最小值)即为仿真步长的最大值h
max。
示例性的,对于仿真步长自适应机制,不同场景下的仿真步长自适应机制如图19所示,图19 为本发明实施例提供的一种仿真步长自适应机制的可选的示意图。图19中t
0表示仿真开始时刻(也可以称为仿真初刻),t
1表示故障发生时刻(也可以称为故障时刻),t
2表示故障切除时刻,t
end表示仿真结束时刻。t
0至t
1这段时间是故障前稳态,t
1至t
2这段时间是故障中,t
2至t
end这段时间是故障后。在t
0至t
1这段时间内系统处于稳态,这时可以采用后向欧拉法,梯形法等运算量小,精度稍低的算法,采用较大的步长进行仿真,假设以所提的仿真步长目标函数求得的最大步长h
max为仿真步长,仿真到故障发生时刻前一点t
k,若采用最大步长h
max后越过故障发生时刻t
1,则最大仿真步长更改为t
1-t
k。t
2、t
end时刻的处理方法也采用同样的处理方法。
在本发明实施例中,配电网信息物理系统故障仿真分析方法包括三个步骤:配电网信息物理系统故障仿真模型的构建、配电网信息物理系统故障仿真方法和配电网信息物理系统故障仿真算例分析,通过以上S1031-S1033实现对配电网信息物理系统故障仿真模型的构建,配电网信息物理系统故障仿真方法包括以上S1034中的仿真分解协调方法、多速率并行实时仿真方法和计算速度动态调节方法。接下来对配电网信息物理系统故障仿真算例分析进行介绍。
在一些实施例中,多速率并行实时仿真方法包括多速率仿真协调策略,计算速度动态调节方法是仿真步长动态调节方法;上述S1034还可以通过以下方式实现。根据预设物理系统分段开关中发生永久性故障的节点、预设物理系统故障发生时间和预设通信链路故障发生时间,基于多速率仿真协调策略和仿真步长动态调节方法,对包含各个元件的物理网络等效模型进行故障实时仿真,确定故障扩展节点;配电网的故障仿真结果包括故障扩展节点。
在本发明实施例中,以配电网信息物理系统故障仿真算例分析是信息物理系统并发故障仿真为例,当配电网物理层发生故障时,断路器开关会发生跳闸,负荷开关失压分闸,重合失败后,相关终端的过流信息会通过信息通信层上传到控制平台,控制平台对故障进行定位并下达控制指令完成非故障区域的重合闸。若上传过程中通信链路发生DDOS攻击,使得控制指令无法下达,会造成停电区域扩大。仿真模型如图20所示,图20为本发明实施例提供的一种配电网信息物理仿真算例分析的可选的示意图,图20示出了信息控制层、信息通信层和配电物理层之间的交互。仿真过程如下。
示例性的,针对目标配电网信息物理系统,采用上述S1021-S1023所描述的方法,构建物理系统模型、通信网络模型和信息系统模型。针对目标配电网信息物理系统,设置物理系统分段开关11-12之间发生永久性故障,通信链路中发生DDOS攻击,导致服务器无法响应正常请求,造成通信网络堵塞故障。针对配电网物理系统中不同元件动态响应时间的差异,将其分为快/中/慢类型,并进行仿真任务解耦和网络解耦;基于快/中/慢多速率仿真协调策略和仿真步长动态调节方法,实现信息物理系统的实时仿真;设置物理系统故障发生时间和通信链路故障发生时间。在物理系统分段开关11-12之间发生永久性故障后,会造成断路器5保护动作跳闸,重合闸失败后通过通信层上传过流信息至控制中心,此时由于通信链路中发生DDOS攻击,导致服务器无法响应正常请求,控制指令无法下达,断路器5及非故障区域的负荷开关6-10、13-16以及联络开关3-13没有正常合闸,停电区域由节点11-12扩散至节点15-16(即故障扩展节点)。
在一些实施例中,上述图1中S104还可以包括S1041-S1047。
S1041、根据深度搜索法分别对配电网的供电路径和通信网络进行搜索,确定最小供电路径和最短通信链路。
S1042、采用蒙特卡洛方法,根据最小供电路径和最短通信链路,在多个元件中随机抽取N个元件,计算N个元件的正常工作时间和故障修复时间。
S1043、根据路由表和关联关系,查找每个负荷节点直接影响的目标元件。
S1044、重新对目标元件分别抽取新随机数,并根据新随机数分别计算目标元件的修正工作时间。
S1045、将目标元件的修正工作时间、正常工作时间和故障修复时间之和作为目标元件的新正常工作时间;目标元件的新正常工作时间用于下一次的工作时间模拟过程。
S1046、持续进行工作时间模拟,直至任一元件的正常工作时间达到预设仿真年限,得到各个元件的目标正常工作时间和目标故障修复时间。
S1047、根据各个元件的目标正常工作时间和目标故障修复时间,计算负荷节点评价结果和可靠性评价结果;可靠性仿真结果包括负荷节点评价结果和可靠性评价结果。
在本发明实施例中,基于配电网信息物理交互特性,构建了配电网信息物理系统可靠性评估体系并提出了可靠性仿真计算方法,为配电网可靠性提升提供了有力的理论支撑与决策辅助,维护了配电网的稳定可靠运行,提高了配电网信息物理系统及其仿真平台的适应性。
在一些实施例中,元件包括:物理侧元件和信息侧元件,目标元件包括:目标物理侧元件和目标信息侧元件;上述S1047还可以通过以下方式实现。根据各个物理侧元件的目标正常工作时间和目标故障修复时间,以及各个信息侧元件的目标正常工作时间和目标故障修复时间,计算负荷节点评价结果;根据各个物理侧元件的目标正常工作时间和目标故障修复时间,计算物理侧可靠性评价结果;根据各个信息侧元件的目标正常工作时间和目标故障修复时间,计算信息侧可靠性评价结果;可靠性评价结果包括物理侧可靠性评价结果和信息侧可靠性评价结果。
在本发明实施例中,元件包括:物理侧元件和信息侧元件,重新对目标物理侧元件和目标信息侧元件分别抽取新随机数,并根据新随机数分别计算目标物理侧元件的修正工作时间,以及目标信息侧元件的修正工作时间;将目标物理侧元件的修正工作时间、正常工作时间和故障修复时间之和作为目标物理侧元件的新正常工作时间;将目标信息侧元件的修正工作时间、正常工作时间和故障修复时间之和作为目标信息侧元件的新正常工作时间;目标物理侧元件的新正常工作时间和目标信息侧元件的新正常工作时间用于下一次的模拟过程,持续进行工作时间模拟,直至信息侧或物理侧的任一元件的正常工作时间达到预设仿真年限,得到各个物理侧元件的目标正常工作时间和目标故障修复时间,以及各个信息侧元件的目标正常工作时间和目标故障修复时间。
在本发明实施例中,根据物理侧元件的故障率、物理侧元件的权重、信息侧元件的故障率、信息侧元件的权重,确定负荷节点综合故障率;根据负荷节点的综合故障率,将N个物理侧元件对应的N个随机数转化为N个物理侧元件的正常工作时间。
本发明实施例提供了一种考虑信息物理交互影响的可靠性计算方法,在配电网信息物理系统中,物理和信息子系统间的相互作用较为复杂,因此,对于整个配电网信息物理系统的可靠性分析需要考虑信息系统和物理系统间的相互作用与影响。本发明实施例采用主观赋权法表征信息系统可靠性对物理系统可靠性的影响,进而获得考虑信息物理交互影响的可靠性计算方法。本发明实施例提供的基于蒙特卡洛方法的配电网信息物理系统可靠性分析流程如图21所示,该可靠性分析流程包括S41-S48。
S41、初始参数输入(即输入物理系统参数与信息系统参数)。
在初始化参数时,还初始化各个物理侧元件和通信侧元件的故障率、修复时间及系统修复时间。
S42、采用深度搜索法对配电网的供电路径进行搜索,并确定最小供电路径与最短通信链路(对应于上述S1041,即根据深度搜索法分别对配电网的供电路径和通信网络进行搜索,确定最小供电路径和最短通信链路)。
采用深度搜索法对配电网的供电路径进行搜索,确定最小供电路径;采用深度搜索法对配电网通信网络进行搜索,确定最短通信链路。
S43、在物理侧,确定需要进行故障模拟的元件(n个),对于每个元件,在相应节点的物理侧,产生0-1之间的随机数;根据元件的综合故障率将其转化为物理侧元件的正常工作时间TTF
p,时钟T=0(对应于上述S1042,即采用蒙特卡洛方法,根据最小供电路径和最短通信链路,在多个元件中随机抽取N个元件,计算N个元件的正常工作时间和故障修复时间)。
根据蒙特卡洛方法,抽取N个随机数,并依据如下公式(23)和公式(24)计算各元件正常工作时间TTF和故障修复时间TTR,并赋值时钟T=0。考虑信息侧与物理侧故障间的相互影响,采用主观赋值法依据不同节点信息侧和物理侧影响程度的相对大小,确定该负荷节点的综合故障率,如公式(25)所示。
TTF=-1/[λln(n)] (23)
TTR=-1/[μln(n)] (24)
λ
zh=α
1*λ
P+α
2·λ
C (25)
上述公式(25)中,λ
zh,λ
P,λ
C分别代表节点综合故障率、物理侧节点故障率、通信节点故障率,α
1和α
2分别为物理侧和对应信息侧的影响权重,可根据不同节点的实际情况进行确定。
S44、在相应节点的信息侧,产生0-1之间的随机数;根据元件的综合故障率将其转化为信息侧元件的正常工作时间TTF
c。
针对信息层,采用与物理层相同的蒙特卡洛方法原理,进行通信节点元件的正常工作时间TTF和故障修复时间TTR。
S45、认为该元件故障,根据路由表、关联关系,找出其直接影响的物理侧负荷点和直接影响的通信节点,记录每个节点的运行情况,完成一次模拟过程(对应于上述S1043,根据路由表和关联关系,查找每个负荷节点直接影响的目标元件)。
S46、对该节点所对应的物理侧元件和信息侧元件分别产生一个新的随机数,求取相应的TTF’(对应于上述S1044,即重新对目标元件分别抽取新随机数,并根据新随机数分别计算目标元件的修正工作时间),并将TTF+TTR+TTF’作为该节点新的正常工作时间TTF
p和TTF
c(对应于上述S1045,即将目标元件的修正工作时间、正常工作时间和故障修复时间之和作为目标元件的新正常工作时间;目标元件的新正常工作时间用于下一次的工作时间模拟过程)。
重新对该元件所处节点的物理侧元件和信息侧元件分别抽取新随机数,求取相应的TTF’,并将TTF+TTR+TTF’作为该节点物理侧元件和信息侧元件新的正常工作时间TTF;
S47、判断模拟时间是否大于仿真年限,当信息侧或物理侧元件任一元件TTF达到仿真年限后,循环结束,继续执行S48(对应于上述S1046,即持续进行工作时间模拟,直至任一元件的正常工作时间达到预设仿真年限,得到各个元件的目标正常工作时间和目标故障修复时间)。
做出判断,当模拟时间未达到仿真年限时,重复步骤S43-S47。
S48、计算负荷点指标及系统物理侧可靠性指标,程序结束(对应于上述S1047,即根据各个元件的目标正常工作时间和目标故障修复时间,计算负荷节点评价结果和可靠性评价结果;可靠性仿真结果包括负荷节点评价结果和可靠性评价结果)。
在一些实施例中,上述可靠性评估指标包括物理侧可靠性评估指标;该配电网仿真方法还包括以下步骤:基于仿真平台架构,根据获取的各个元件的故障率和各个设备的故障率,利用预先构建的不同形式的可靠性评估模型和物理侧可靠性评估指标,进行配电网信息物理系统的物理侧可靠性评估,确定物理侧可靠性仿真结果;可靠性仿真结果包括物理侧可靠性仿真结果;其中,不同形式的可靠性评估模型包括多个组件串联构成的串联式单元、多个组件并联构成的并联式单元,以及多个组件并联后与表决器串联构成的表决式单元。
在本发明实施例中,在进行配电网信息物理系统物理侧可靠性评估之前,需要建立元件、设备的可靠性评估模型,并获得各个元件、设备的故障率,配电网常用元件、设备的可靠度与故障率计算模型可以包括串联式单元、并联式单元和表决式单元。以下采用框图法对元件及设备的可靠度与故障率计算模型的构建进行说明。
示例性的,对于串联式单元的建模,串联式单元的可靠性框图如图22a所示,单元内所有组件全部正常工作时,即r
1、r
2...r
i组件全部正常工作,单元才能正常工作,其可靠度计算如公式(26)所示。
公式(26)中R
s表示串联式单元的可靠度,r
i表示单元内第i个组件的可靠度。
示例性的,对于并联式单元的建模,并联式单元的可靠性框图如图22b所示,单元内只要存在正常工作的组件,即r
1、r
2...r
i中任一个组件,单元即能正常工作,其可靠度计算如式(27)所示。
公式(27)中R
P表示串联式单元的可靠度。
示例性的,对于表决式单元的建模,由n个组件r
1、r
2...r
i,i=n组成的并联单元,其中有任意r个组件r/n正常工作时,单元可正常工作,表决式单元的可靠性框图如图22c所示,其可靠度计算如公式(28)所示。
公式(28)中R
L表示表决式单元的可靠度,R
i和F
i分别为第i个组件的可靠度和不可靠度。
在一些实施例中,上述物理侧可靠性评估指标包括持续停电指标、瞬时停电指标,以及与负荷相关的指标;其中,持续停电指标包括以下至少一项:系统平均停电频率、系统平均停电时间、用户平均停电持续时间、用户总平均停电时间、用户平均停电频率、平均供电可用率和用户多次供电指标;与负荷相关的停电指标包括以下至少一项:平均系统停电频率和平均系统停电持续时间;瞬时停电指标包括:平均瞬时停电频率。
在本发明实施例中,当配电网信息物理系统可靠性仿真时,还需要构建配电网信息物理系统物理侧可靠性评估指标,配电网物理系统可靠性指标分为三大类,持续停电指标、瞬时停电指标、与负荷相关的指标,各类指标定义如下所示。
在本发明实施例中,持续停电指标包括系统平均停电频率、系统平均停电时间、用户平均停电持续时间、用户总平均停电时间、用户平均停电频率、平均供电可用率和用户多次供电指标,以下分别进行说明。
系统平均停电频率(SAIFI),单位是次/(户·a),如公式(29)所示。
上述公式(29)中,N
c为每次停电用户数,N
total为用户总数。
系统平均停电时间(SAIDI),单位是min/(户·a),如公式(30)所示。
上述公式(30)中,T
C为用户停电时间。
用户平均停电持续时间(CAIDI),单位是min/次,如公式(31)所示。
用户总平均停电时间(CTAIDI),单位是min/(户·a),如公式(32)所示。
上述公式(32)中,N
C,total为停电影响的用户数。
用户平均停电频率(CAIFI),单位是次/(户·a),如公式(33)所示。
平均供电可用率(ASAI),如公式(34)所示。
上述公式(34)中,h
avaiable和h
demand分别表示供电可用小时数与用户供电需求小时数。
用户多次供电指标(CEMI
n),如公式(35)所示。
在本发明实施例中,与负荷相关的停电指标包括平均系统停电频率(ASIFI)和平均系统停电持续时间(ASIDI),以下分别进行说明。
平均系统停电频率(ASIFI)如公式(36)所示。
其中,L
outage和L
total分别表示每次停电损失负荷和供电负荷总量。
平均系统停电持续时间(ASIDI),单位是min,如公式(37)所示。
在本发明实施例中,瞬时停电指标包括平均瞬时停电频率(MAIFI),单位是次/(户·a),如公式(38)所示。
上述公式(38)中O
s和N
outages分别表示每次停电的操作次数和每次瞬时停电用户数。
在本发明实施例中,当使用上述配电网物理系统可靠性指标进行可靠性判定时,可较好的反映 配电网历年运行指标的变化趋势。
在一些实施例中,上述可靠性评估指标包括信息侧可靠性评估指标,信息侧可靠性评估指标包括:网络连通度可靠性和网络性能可靠性;其中,网络连通度可靠性包括以下至少一项:连通度、粘聚度、混合连通系数、网络基本可靠度、端对端可靠度和全端可靠度;网络性能可靠性包括以下至少一项:平均故障间隔时间和平均故障修复时间。
在本发明实施例中,当配电网信息物理系统可靠性仿真时,还需要构建配电网信息物理系统信息侧可靠性评价指标,配电网信息系统可靠性指标分为两个部分,网络连通度可靠性和网络性能可靠性。各类指标定义如下所示。
在本发明实施例中,网络连通度可靠性包括连通度、粘聚度、混合连通系数、网络基本可靠度、端对端可靠度和全端可靠度,以下分别进行说明。
连通度如公式(39)所示。
上述公式(39)中,T表示节点i与节点j之间的连通度,CH
ij为断开联通网络中节点i与节点j之间所有路径必须去掉的路径数。
粘聚度如公式(40)所示。
上述公式(40)中,S表示节点i与节点j之间的粘聚度,CN
ij为断开联通网络中节点i与节点j之间所有路径必须去掉的节点数。
混合连通系数如公式(41)所示。
C=min(M) (41)
上述公式(41)中,M表示使得信息网络分为几个子网时所需断开及去掉路径数与节点数。
网络基本可靠度如公式(42)所示。
上述公式(42)中,基本可靠度反映对象(如通信网络、网络部件、网络设备)无故障的概率,其中R
vi(t)表示第i条通信链路通畅无故障的概率,R
ej(t)表示j个网络部件或设备无故障的概率。
端对端可靠度如公式(43)所示。
上述公式(43)表示网络G中规定的两个节点之间至少存在一条路径的概率网络性能可靠性。
全端可靠度如公式(44)所示。
表示网络中所有节点之间至少存在一条路径的概率。
由上述网络基本可靠度、端对端可靠度和全端可靠度的定义可知,对于某一负荷节点,其对应信息侧的故障率为λ
C如公式(45)所示。
λ
C=1-R
G (45)
在本发明实施例中,网络性能可靠性包括平均故障间隔时间和平均故障修复时间,以下分别进行说明。
平均故障间隔时间如公式(46)所示。
上述公式(46)中平均故障间隔时间可表示有效期内故障发生的频繁程度,其中T表示有效监控期故障持续总时间,d表示单词故障平均持续时间,λ表示故障发生概率。
平均故障修复时间如公式(47)所示。
上述公式(47)中平均修复时间可用以表征故障修复的平均时间。
为实现本发明实施例的配电网仿真方法,本发明实施例还提供一种配电网仿真系统,如图23所示,图23为本发明实施例提供的一种配电网仿真系统的可选的结构示意图,该配电网仿真系统230包括:平台搭建部分2301,被配置为根据配电网中信息系统与物理系统之间的模型差异性、交互影响,以及多场景仿真验证的规模和精度,进行多层级、多尺度的平台架构建模,得到仿真平台架构;融合部分2302,被配置为在仿真平台架构上,根据配电网中物理系统与信息系统之间的耦合特性,对时变信息、非确定条件下的信息物理仿真系统进行融合建模,得到配电网信息物理系统;故障仿真部分2303,被配置为基于仿真平台架构,在物理系统、通信网络及信息系统的并发故障场景下,对配电网信息物理系统进行实时仿真,确定配电网的故障仿真结果;故障仿真结果用于向配电网信息物理系统的故障隔离决策和故障恢复决策提供支持;可靠性仿真部分2304,被配置为基于仿真平台架构,利用可靠性评估指标对配电网信息物理系统进行可靠性仿真评估,确定配电网的可靠性仿真结果。
在一些实施例中,融合部分2302,还被配置为基于配电网络动态等值模型和支撑不同模态配电网运行的仿真模型库,构建物理系统模型;基于支持多种典型协议的跨应用、跨节点的数据流模型库,构建通信网络模型;基于通信网络模型,对多源信息进行预处理,结合信息网络安全模型,构建信息系统模型;基于关联矩阵、物理系统模型、通信网络模型和信息系统模型,进行系统融合建模,得到融合系统;基于设备的有限状态机和系统的有限状态机,分别对融合系统中设备的有限状态机模型和系统的有限状态机模型进行构建,得到配电网信息物理系统。
在一些实施例中,融合部分2302,还被配置为基于有限状态机的配电混合网信息物理融合建模方法和物理侧交互元件的多分辨率多层次柔性模型构建方法,形成支撑不同模态配电网运行的仿真模型库;根据用于支撑物理信息系统交互的通信网络物理层模型和数据链路层模型、通信应用层模型、关键事件流和信息流过程模型的构建方法,形成支持多种典型协议的跨应用、跨节点的数据流模型库。
在一些实施例中,仿真平台架构包括模型层、数据层、算法层、接口层和业务层;接口层用于连接配电网的物理侧与信息侧;
融合部分2302,还被配置为在模型层中,针对配电网的物理侧,采用平均化方法与动态相量法进行模型构建,得到配电网络动态等值模型;针对配电网的信息侧,采用脚本方法,对关键事件流和信息流进行模型构建,得到关键事件流和信息流过程模型;并构建通信网络物理层模型、数据链路层模型、通信应用层模型和信息网络安全模型;在数据层中,对模型构建过程和仿真过程中的数据进行数据采集、数据处理和数据存储;业务层包括仿真功能模块和应用场景验证模块,仿真功能模块用于支持配电网信息物理系统的暂态仿真功能、配电网信息物理系统的稳态仿真功能、通信网络及通信网络故障仿真功能;场景验证模块用于支持配电网信息物理系统的并发故障场景验证、配电网信息物理系统的可靠性分析仿真、配电网的信息侧攻击与故障场景验证;
故障仿真部分2303,还被配置为在算法层中,采用仿真网络分解协调技术、多速率并行实时仿真方法和计算速度动态调节方法,在物理系统、通信网络及信息系统的并发故障场景下,对配电网物理节点进行实时仿真,确定配电网的故障仿真结果。
在一些实施例中,故障仿真部分2303,还被配置为根据不同元件动态响应时间或响应速度,对元件进行分类,得到各个元件的元件类型;其中,元件类型包括快类型、中间类型和慢类型,中间类型对应的仿真步长大于快类型对应的仿真步长,且小于或等于慢类型对应的仿真步长;对配电网中分类后的元件进行建模;对包含各个元件的配电网信息物理系统中的物理网络进行动态解耦,并建立等效模型;采用仿真分解协调方法、多速率并行实时仿真方法和计算速度动态调节方法,对包含各个元件的物理网络等效模型进行故障实时仿真,确定配电网的故障仿真结果。
在一些实施例中,多速率并行实时仿真方法包括多速率仿真协调策略,计算速度动态调节方法是仿真步长动态调节方法;
故障仿真部分2303,还被配置为根据预设物理系统分段开关中发生永久性故障的节点、预设物理系统故障发生时间和预设通信链路故障发生时间,基于多速率仿真协调策略和仿真步长动态调节方法,对包含各个元件的物理网络等效模型进行故障实时仿真,确定故障扩展节点;配电网的故障仿真结果包括故障扩展节点。
在一些实施例中,故障仿真部分2303,还被配置为获取加载数据和中央处理器核心数量;根据加载数据和中央处理器核心数量进行暂态仿真,利用遗传算法,对计算线路的中央处理器数量和计算各个元件的中央处理器数量,进行分配,得到分配结果;分配结果包括各个中央处理器对应的节 点类型、数量和所在的线路;根据分配结果,构建仿真任务分解模型;采用节点分裂法,对各个元件的配电网信息物理系统中物理网络对应的仿真任务分解模型,进行与各个元件的元件类型对应的动态解耦,得到解耦后的模型;根据解耦后的模型,构建各个元件的网络间的等效模型和元件与网络之间的等效模型;等效模型包括网络间的等效模型和元件与网络之间的等效模型。
在一些实施例中,可靠性仿真部分2304,还被配置为根据深度搜索法分别对配电网的供电路径和通信网络进行搜索,确定最小供电路径和最短通信链路;采用蒙特卡洛方法,根据最小供电路径和最短通信链路,在多个元件中随机抽取N个元件,计算N个元件的正常工作时间和故障修复时间;根据路由表和关联关系,查找每个负荷节点直接影响的目标元件;重新对目标元件分别抽取新随机数,并根据新随机数分别计算目标元件的修正工作时间;将目标元件的修正工作时间、正常工作时间和故障修复时间之和作为目标元件的新正常工作时间;目标元件的新正常工作时间用于下一次的工作时间模拟过程;持续进行工作时间模拟,直至任一元件的正常工作时间达到预设仿真年限,得到各个元件的目标正常工作时间和目标故障修复时间;根据各个元件的目标正常工作时间和目标故障修复时间,计算负荷节点评价结果和可靠性评价结果;可靠性仿真结果包括负荷节点评价结果和可靠性评价结果。
在一些实施例中,元件包括:物理侧元件和信息侧元件,目标元件包括:目标物理侧元件和目标信息侧元件;
可靠性仿真部分2304,还被配置为根据各个物理侧元件的目标正常工作时间和目标故障修复时间,以及各个信息侧元件的目标正常工作时间和目标故障修复时间,计算负荷节点评价结果;根据各个物理侧元件的目标正常工作时间和目标故障修复时间,计算物理侧可靠性评价结果;根据各个信息侧元件的目标正常工作时间和目标故障修复时间,计算信息侧可靠性评价结果;可靠性评价结果包括物理侧可靠性评价结果和信息侧可靠性评价结果。
在一些实施例中,可靠性评估指标包括物理侧可靠性评估指标;
可靠性仿真部分2304,还被配置为基于仿真平台架构,根据获取的各个元件的故障率和各个设备的故障率,利用预先构建的不同形式的可靠性评估模型和物理侧可靠性评估指标,进行配电网信息物理系统的物理侧可靠性评估,确定物理侧可靠性仿真结果;可靠性仿真结果包括物理侧可靠性仿真结果;其中,不同形式的可靠性评估模型包括多个组件串联构成的串联式单元、多个组件并联构成的并联式单元,以及多个组件并联后与表决器串联构成的表决式单元。
在一些实施例中,物理侧可靠性评估指标包括持续停电指标、瞬时停电指标,以及与负荷相关的指标;其中,持续停电指标包括以下至少一项:系统平均停电频率、系统平均停电时间、用户平均停电持续时间、用户总平均停电时间、用户平均停电频率、平均供电可用率和用户多次供电指标;与负荷相关的停电指标包括以下至少一项:平均系统停电频率和平均系统停电持续时间;瞬时停电指标包括:平均瞬时停电频率。
在一些实施例中,可靠性评估指标包括信息侧可靠性评估指标,信息侧可靠性评估指标包括:网络连通度可靠性和网络性能可靠性;其中,网络连通度可靠性包括以下至少一项:连通度、粘聚度、混合连通系数、网络基本可靠度、端对端可靠度和全端可靠度;网络性能可靠性包括以下至少一项:平均故障间隔时间和平均故障修复时间。
需要说明的是,上述实施例提供的配电网仿真系统在进行配电网仿真时,仅以上述各程序部分的划分进行举例说明,实际应用中,可以根据需要而将上述处理分配由不同的程序部分完成,即将系统的内部结构划分成不同的程序部分,以完成以上描述的全部或者部分处理。另外,上述实施例提供的配电网仿真系统与配电网仿真方法实施例属于同一构思,其具体实现过程及有益效果详见方法实施例,这里不再赘述。对于本系统实施例中未披露的技术细节,请参照本发明方法实施例的描述而理解。
在本发明实施例中,图24为本发明实施例提出的配电网仿真设备组成结构示意图,如图24所示,本发明实施例提出的配电网仿真设备240包括处理器2401、存储可执行计算机程序的存储器2402,处理器2401,被配置为执行存储器2402中存储的可执行计算机程序时,实现本发明实施例提供的配电网仿真方法。在一些实施例中,配电网仿真设备240还可以包括通信接口2403,以及用于连接处理器2401、存储器2402和通信接口2403的总线2404。
在本发明实施例中,上述处理器2401可以为特定用途集成电路(Application Specific Integrated Circuit,ASIC)、数字信号处理器(Digital Signal Processor,DSP)、数字信号处理装置(Digital Signal Processing Device,DSPD)、可编程逻辑装置(ProgRAMmable Logic Device,PLD)、现场可编程门阵列(Field ProgRAMmable Gate Array,FPGA)、中央处理器(Central Processing Unit,CPU)、控制 器、微控制器、微处理器中的至少一种。可以理解地,对于不同的设备,用于实现上述处理器功能的电子器件还可以为其它,本发明实施例不作具体限定。
在本发明实施例中,总线2404用于连接通信接口2403、处理器2401以及存储器2402,实现这些器件之间的相互通信。
存储器2402用于存储可执行计算机程序和数据,该可执行计算机程序包括计算机操作指令,存储器2402可能包含高速RAM存储器,也可能还包括非易失性存储器,例如,至少两个磁盘存储器。在实际应用中,上述存储器2402可以是易失性存储器(volatile memory),例如随机存取存储器(Random-Access Memory,RAM);或者非易失性存储器(non-volatile memory),例如只读存储器(Read-Only Memory,ROM),快闪存储器(flash memory),硬盘(Hard Disk Drive,HDD)或固态硬盘(Solid-State Drive,SSD);或者上述种类的存储器的组合,并向处理器2401提供可执行计算机程序和数据。
另外,在本实施例中的各功能模块可以集成在一个处理单元中,也可以是各个单元单独物理存在,也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现,也可以采用软件功能模块的形式实现。
集成的单元如果以软件功能模块的形式实现并非作为独立的产品进行销售或使用时,可以存储在一个计算机可读取存储介质中,基于这样的理解,本实施例的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来,该计算机软件产品存储在一个存储介质中,包括若干指令用以使得一台计算机设备(可以是个人计算机,服务器,或者网络设备等)或processor(处理器)执行本实施例方法的全部或部分步骤。而前述的存储介质包括:U盘、移动硬盘、只读存储器(Read Only Memory,ROM)、随机存取存储器(Random Access Memory,RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
本发明实施例提供一种计算机可读存储介质,存储有计算机程序,被配置为被处理器执行时实现如上任一实施例所述的配电网仿真方法。
示例性的,本实施例中的一种配电网仿真方法对应的程序指令可以被存储在光盘,硬盘,U盘等存储介质上,当存储介质中的与一种配电网仿真方法对应的程序指令被一电子设备读取或被执行时,可以实现如上述任一实施例所述的配电网仿真方法。
本领域内的技术人员应明白,本发明实施例可提供为方法、系统、或计算机程序产品。因此,本发明可采用硬件实施例、软件实施例、或结合软件和硬件方面的实施例的形式。而且,本发明可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器和光学存储器等)上实施的计算机程序产品的形式。
本发明是参照根据本发明实施例的方法、设备(系统)、和计算机程序产品的实现流程示意图和/或方框图来描述的。应理解可由计算机程序指令实现流程示意图和/或方框图中的每一流程和/或方框、以及实现流程示意图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器,使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在实现流程示意图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中,使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品,该指令装置实现在实现流程示意图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上,使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理,从而在计算机或其他可编程设备上执行的指令提供用于实现在实现流程示意图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
以上所述,仅为本发明的较佳实施例而已,并非用于限定本发明的保护范围。
本发明实施例公开一种配电网仿真方法、系统、设备和计算机可读存储介质。该方法包括:根据配电网中信息系统与物理系统之间的模型差异性、交互影响,及多场景仿真验证的规模和精度,进行多层级、多尺度的平台架构建模,得到仿真平台架构;在仿真平台架构上,根据配电网中物理系统与信息系统之间的耦合特性,对时变信息、非确定条件下的信息物理仿真系统进行融合建模,得到配电网信息物理系统;基于仿真平台架构,在物理系统、通信网络及信息系统的并发故障场景下,对配电网信息物理系统进行实时仿真,确定配电网的故障仿真结果;基于仿真平台架构,利用可靠性评估指标对配电网信息物理系统进行可靠性仿真评估,确定配电网的可靠性仿真结果。
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- 一种配电网仿真方法,所述方法包括:根据配电网中信息系统与物理系统之间的模型差异性、交互影响,以及多场景仿真验证的规模和精度,进行多层级、多尺度的平台架构建模,得到仿真平台架构;在所述仿真平台架构上,根据所述配电网中所述物理系统与所述信息系统之间的耦合特性,对时变信息、非确定条件下的信息物理仿真系统进行融合建模,得到配电网信息物理系统;基于所述仿真平台架构,在所述物理系统、通信网络及所述信息系统的并发故障场景下,对所述配电网信息物理系统进行实时仿真,确定所述配电网的故障仿真结果;所述故障仿真结果用于向所述配电网信息物理系统的故障隔离决策和故障恢复决策提供支持;基于所述仿真平台架构,利用可靠性评估指标对所述配电网信息物理系统进行可靠性仿真评估,确定所述配电网的可靠性仿真结果。
- 根据权利要求1所述的方法,其中,所述根据所述配电网中所述物理系统与所述信息系统之间的耦合特性,对时变信息、非确定条件下的信息物理仿真系统进行融合建模,得到配电网信息物理系统,包括:基于配电网络动态等值模型和支撑不同模态配电网运行的仿真模型库,构建物理系统模型;基于支持多种典型协议的跨应用、跨节点的数据流模型库,构建通信网络模型;基于所述通信网络模型,对多源信息进行预处理,结合信息网络安全模型,构建信息系统模型;基于关联矩阵、所述物理系统模型、所述通信网络模型和所述信息系统模型,进行系统融合建模,得到融合系统;基于设备的有限状态机和系统的有限状态机,分别对所述融合系统中设备的有限状态机模型和系统的有限状态机模型进行构建,得到所述配电网信息物理系统。
- 根据权利要求2所述的方法,其中,所述方法还包括:基于有限状态机的配电混合网信息物理融合建模方法和物理侧交互元件的多分辨率多层次柔性模型构建方法,形成所述支撑不同模态配电网运行的仿真模型库;根据用于支撑物理信息系统交互的通信网络物理层模型和数据链路层模型、通信应用层模型、关键事件流和信息流过程模型的构建方法,形成所述支持多种典型协议的跨应用、跨节点的数据流模型库。
- 根据权利要求2或3所述的方法,其中,所述仿真平台架构包括模型层、数据层、算法层、接口层和业务层;所述接口层用于连接所述配电网的物理侧与信息侧;所述方法还包括:在所述模型层中,针对所述配电网的物理侧,采用平均化方法与动态相量法进行模型构建,得到所述配电网络动态等值模型;针对所述配电网的信息侧,采用脚本方法,对关键事件流和信息流进行模型构建,得到所述关键事件流和信息流过程模型;并构建所述通信网络物理层模型、数据链路层模型、通信应用层模型和所述信息网络安全模型;在所述数据层中,对模型构建过程和仿真过程中的数据进行数据采集、数据处理和数据存储;所述业务层包括仿真功能模块和应用场景验证模块,所述仿真功能模块用于支持所述配电网信息物理系统的暂态仿真功能、所述配电网信息物理系统的稳态仿真功能、所述通信网络及通信网络故障仿真功能;所述场景验证模块用于支持所述配电网信息物理系统的并发故障场景验证、所述配电网信息物理系统的可靠性分析仿真、所述配电网的信息侧攻击与故障场景验证;所述在所述物理系统、通信网络及所述信息系统的并发故障场景下,对所述配电网信息物理系统进行实时仿真,确定所述配电网的故障仿真结果,包括:在所述算法层中,采用仿真网络分解协调技术、多速率并行实时仿真方法和计算速度动态调节方法,在所述物理系统、所述通信网络及所述信息系统的并发故障场景下,对配电网物理节点进行实时仿真,确定所述配电网的故障仿真结果。
- 根据权利要求1-3任一项所述的方法,其中,所述对所述配电网信息物理系统进行实时仿真,确定所述配电网的故障仿真结果,包括:根据不同元件动态响应时间或响应速度,对元件进行分类,得到各个元件的元件类型;其中,所述元件类型包括快类型、中间类型和慢类型,所述中间类型对应的仿真步长大于所述快类型对应 的仿真步长,且小于或等于所述慢类型对应的仿真步长;对所述配电网中分类后的元件进行建模;对包含所述各个元件的配电网信息物理系统中的物理网络进行动态解耦,并建立等效模型;采用仿真分解协调方法、多速率并行实时仿真方法和计算速度动态调节方法,对包含所述各个元件的物理网络等效模型进行故障实时仿真,确定所述配电网的故障仿真结果。
- 根据权利要求5所述的方法,其中,所述多速率并行实时仿真方法包括多速率仿真协调策略,所述计算速度动态调节方法是仿真步长动态调节方法;所述采用仿真分解协调方法、多速率并行实时仿真方法和计算速度动态调节方法,对包含所述各个元件的物理网络等效模型进行故障实时仿真,确定所述配电网的故障仿真结果,包括:根据预设物理系统分段开关中发生永久性故障的节点、预设物理系统故障发生时间和预设通信链路故障发生时间,基于所述多速率仿真协调策略和所述仿真步长动态调节方法,对包含所述各个元件的物理网络等效模型进行故障实时仿真,确定故障扩展节点;所述配电网的故障仿真结果包括所述故障扩展节点。
- 根据权利要求5所述的方法,其中,所述对包含所述各个元件的配电网信息物理系统中的物理网络,进行动态解耦,并建立等效模型,包括:获取加载数据和中央处理器核心数量;根据所述加载数据和所述中央处理器核心数量进行暂态仿真,利用遗传算法,对计算线路的中央处理器数量和计算各个元件的中央处理器数量,进行分配,得到分配结果;所述分配结果包括各个中央处理器对应的节点类型、数量和所在的线路;根据所述分配结果,构建仿真任务分解模型;采用节点分裂法,对所述各个元件的配电网信息物理系统中物理网络对应的仿真任务分解模型,进行与所述各个元件的元件类型对应的动态解耦,得到解耦后的模型;根据所述解耦后的模型,构建所述各个元件的网络间的等效模型和元件与网络之间的等效模型;所述等效模型包括所述网络间的等效模型和所述元件与网络之间的等效模型。
- 根据权利要求1-3任一项所述的方法,其中,所述基于所述仿真平台架构,利用可靠性评估指标对所述配电网信息物理系统进行可靠性仿真评估,确定所述配电网的可靠性仿真结果,包括:根据深度搜索法分别对配电网的供电路径和通信网络进行搜索,确定最小供电路径和最短通信链路;采用蒙特卡洛方法,根据所述最小供电路径和所述最短通信链路,在多个元件中随机抽取N个元件,计算所述N个元件的正常工作时间和故障修复时间;根据路由表和关联关系,查找每个负荷节点直接影响的目标元件;重新对目标元件分别抽取新随机数,并根据所述新随机数分别计算所述目标元件的修正工作时间;将所述目标元件的修正工作时间、正常工作时间和故障修复时间之和作为所述目标元件的新正常工作时间;所述目标元件的新正常工作时间用于下一次的工作时间模拟过程;持续进行工作时间模拟,直至任一元件的正常工作时间达到预设仿真年限,得到各个元件的目标正常工作时间和目标故障修复时间;根据所述各个元件的目标正常工作时间和目标故障修复时间,计算负荷节点评价结果和可靠性评价结果;所述可靠性仿真结果包括所述负荷节点评价结果和所述可靠性评价结果。
- 根据权利要求8所述的方法,其中,所述元件包括:物理侧元件和信息侧元件,所述目标元件包括:目标物理侧元件和目标信息侧元件;所述根据所述各个元件的目标正常工作时间和目标故障修复时间,计算负荷节点评价结果和可靠性评价结果,包括:根据各个物理侧元件的目标正常工作时间和目标故障修复时间,以及各个信息侧元件的目标正常工作时间和目标故障修复时间,计算所述负荷节点评价结果;根据所述各个物理侧元件的目标正常工作时间和目标故障修复时间,计算物理侧可靠性评价结果;根据所述各个信息侧元件的目标正常工作时间和目标故障修复时间,计算信息侧可靠性评价结果;所述可靠性评价结果包括所述物理侧可靠性评价结果和所述信息侧可靠性评价结果。
- 根据权利要求1-3任一项所述的方法,其中,所述可靠性评估指标包括物理侧可靠性评估指标;所述方法还包括:基于所述仿真平台架构,根据获取的各个元件的故障率和各个设备的故障率,利用预先构建的不同形式的可靠性评估模型和物理侧可靠性评估指标,进行所述配电网信息物理系统的物理侧可靠性评估,确定物理侧可靠性仿真结果;所述可靠性仿真结果包括所述物理侧可靠性仿真结果;其中,所述不同形式的可靠性评估模型包括多个组件串联构成的串联式单元、多个组件并联构成的并联式单元,以及多个组件并联后与表决器串联构成的表决式单元。
- 根据权利要求10所述的方法,其中,所述物理侧可靠性评估指标包括持续停电指标、瞬时停电指标,以及与负荷相关的指标;其中,所述持续停电指标包括以下至少一项:系统平均停电频率、系统平均停电时间、用户平均停电持续时间、用户总平均停电时间、用户平均停电频率、平均供电可用率和用户多次供电指标;所述与负荷相关的停电指标包括以下至少一项:平均系统停电频率和平均系统停电持续时间;所述瞬时停电指标包括:平均瞬时停电频率。
- 根据权利要求1-3任一项所述的方法,其中,所述可靠性评估指标包括信息侧可靠性评估指标,所述信息侧可靠性评估指标包括:网络连通度可靠性和网络性能可靠性;其中,所述网络连通度可靠性包括以下至少一项:连通度、粘聚度、混合连通系数、网络基本可靠度、端对端可靠度和全端可靠度;所述网络性能可靠性包括以下至少一项:平均故障间隔时间和平均故障修复时间。
- 一种配电网仿真系统,所述系统包括:平台搭建部分,被配置为根据配电网中信息系统与物理系统之间的模型差异性、交互影响,以及多场景仿真验证的规模和精度,进行多层级、多尺度的平台架构建模,得到仿真平台架构;融合部分,被配置为在所述仿真平台架构上,根据所述配电网中所述物理系统与所述信息系统之间的耦合特性,对时变信息、非确定条件下的信息物理仿真系统进行融合建模,得到配电网信息物理系统;故障仿真部分,被配置为基于所述仿真平台架构,在所述物理系统、通信网络及所述信息系统的并发故障场景下,对所述配电网信息物理系统进行实时仿真,确定所述配电网的故障仿真结果;所述故障仿真结果用于向所述配电网信息物理系统的故障隔离决策和故障恢复决策提供支持;可靠性仿真部分,被配置为基于所述仿真平台架构,利用可靠性评估指标对所述配电网信息物理系统进行可靠性仿真评估,确定所述配电网的可靠性仿真结果。
- 一种配电网仿真设备,所述设备包括:存储器,被配置为存储可执行计算机程序;处理器,被配置为执行所述存储器中存储的可执行计算机程序时,实现权利要求1-12任一项所述的方法。
- 一种计算机可读存储介质,存储有计算机程序,被配置为用于被处理器执行时,实现权利要求1-12任一项所述的方法。
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