CN112287504A - Offline/online integrated simulation system and method for power distribution network - Google Patents

Offline/online integrated simulation system and method for power distribution network Download PDF

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CN112287504A
CN112287504A CN202011555410.4A CN202011555410A CN112287504A CN 112287504 A CN112287504 A CN 112287504A CN 202011555410 A CN202011555410 A CN 202011555410A CN 112287504 A CN112287504 A CN 112287504A
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simulation
distribution network
power distribution
state
model
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CN112287504B (en
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盛万兴
孟晓丽
刘科研
贾东梨
叶学顺
何开元
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China Electric Power Research Institute Co Ltd CEPRI
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China Electric Power Research Institute Co Ltd CEPRI
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
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    • G—PHYSICS
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    • G06F2113/00—Details relating to the application field
    • G06F2113/04—Power grid distribution networks

Abstract

The invention provides a power distribution network off-line/on-line integrated simulation system and method, which comprises the following steps: the client is used for sending a simulation request to the server and obtaining a simulation result sent by the server; the server is used for performing off-line/on-line continuous state simulation based on the simulation request and the power distribution network parameters acquired from the physical power grid by adopting a complex active power distribution network multi-operation state simulation engine and a corresponding power distribution network multi-dimensional resolution model in an event-driven mode, and sending a simulation result to the client; the complex active power distribution network multi-operation state simulation engine comprises a plurality of simulation kernel algorithm engines of different levels; the invention has the following advantages: the invention can carry out continuous simulation of a plurality of continuous states by flexibly switching the computing power of the simulation engine.

Description

Offline/online integrated simulation system and method for power distribution network
Technical Field
The invention belongs to the technical field of operation analysis of a power distribution network, and particularly relates to an offline/online integrated simulation system and method for the power distribution network.
Background
The power distribution network spans a plurality of voltage levels, the power grid structure is complicated and interconnected, and the most complicated link for connecting a large power grid and user loads is provided. The power distribution network is close to the user side, the construction investment is huge, the risk caused by power failure of the power distribution network is increased rapidly, and the safe, reliable and economic operation of the power distribution network is related to national safety and national civilization.
As a basic means and an important tool for power distribution technology research and operation analysis, the power distribution network simulation shows the electrical characteristics of each node and branch of the power distribution network under different configurations, structures and working conditions, so that planning design, operation maintenance or scheduling decision can be carried out, and finally the rationality of power distribution network construction investment and the reliability of an operation and maintenance scheme are effectively improved. Therefore, the perfection degree of the power distribution network simulation directly restricts the development of the power distribution network technology, and becomes a major bottleneck to be broken through urgently in the process of improving the reliable economic operation level of the power distribution network at present.
With the continuous improvement of the power electronization degree of a power distribution network, a large number of novel elements or systems such as distributed power supplies, micro-grids and electric vehicles are introduced into the power distribution network, the complexity of the novel elements or systems is increased in a crossing manner, and the traditional power distribution network is gradually changed from a simple-topology radiation-type network to an active power distribution network comprising a plurality of distributed power supplies and multiple sections and multiple contacts. The access capacity of the distributed photovoltaic in the active power distribution network is continuously improved, a large amount of fossil energy can be saved, the loss of a transmission line of the power distribution network is reduced, the related investment of capacity expansion of the power distribution network can be delayed, a series of new problems are brought, for example, voltage is out of limit, protection coordination and voltage fluctuation are achieved, and the difficulty of simulation analysis is greatly improved. At present, in the aspect of power distribution network simulation, the existing outstanding problems are mainly reflected in the following three aspects:
(1) aspects of simulation engine
The existing power distribution network simulation engine is mainly divided into transient simulation software such as Dig-SILENT and steady state simulation software such as Cyme, which are only suitable for one simulation state, and are mutually independent simulation scenes when various states are simulated, and the simulation of each state lacks correlation and cannot effectively depict the dynamic process of coupling and interweaving the discrete state and the continuous process of the active power distribution network, so that the simulation adaptability and the precision are insufficient.
(2) And (5) simulating a model switching aspect.
Time constants of transformers, lines, power electronic inverters, mechanical switches and the like in the power distribution network are different greatly, and models with different resolutions are required to be selected in simulation of different running states of the power distribution network, so that simulation with different fineness degrees is realized, and the accuracy and the efficiency are optimal. At present, most of simulation models in a power distribution network simulation software system are manually selected for modeling, and the simulation system models in different running states are selected depending on knowledge and experience of simulation modeling personnel or the effect of trying different models, so that great uncertainty exists. Therefore, a model optimization method for a power distribution network simulation process in different states and a method for tracking self-adaptive switching of the model before and after state switching are urgently needed, so that the problem of reasonable selection of a simulation model is solved, and the simulation accuracy is improved to the greatest extent.
(3) Multi-running state simulation scenario
According to the difference of the time scales of research objects, the simulation method of the power distribution network can be mainly divided into 2 types, namely steady-state simulation and dynamic simulation. The steady-state simulation is suitable for the operation parameter change process with longer time scale, such as active power distribution network load flow calculation, reactive power optimization, load flow optimization, self-healing control and the like. However, the steady-state model is overly simplified for the structure of the element, so that the steady-state simulation cannot show the specific process of the system changing between various steady states, and the reliability of the simulation result is further reduced.
In order to analyze the state change process of an active power distribution network in a short time, dynamic simulation is used for analyzing the rapid dynamic processes of inverter type distributed power supply voltage control, power distribution network fault location and processing and the like. In addition, by combining rapid simulation methods such as parallel computation and the like, the dynamic simulation can also realize the real-time simulation of the processes of voltage control, fault protection and the like of the active power distribution network. The dynamic simulation is superior to the steady-state simulation in the aspects of accuracy and real-time performance, and simultaneously occupies a large amount of computing resources, so that the dynamic simulation is not suitable for the whole-process continuous simulation of the active power distribution network.
In order to be compatible with joint simulation of typical events of active power distribution networks with different time scales, related scholars have developed a plurality of researches. Soup surge, multiple time scale full process simulation and modeling research of ac/dc power systems new progress [ J ] grid technology, 2009, 33 (16): 1-8, methods such as transmission network electromagnetic transient/electromechanical transient hybrid simulation and electromechanical transient/medium-and-long-term dynamic hybrid simulation are provided, however, in the active power distribution network modeling process, the premise hypothesis of elements such as power supply, line and load is obviously different from that of the transmission network, so that the hybrid simulation method is not suitable for the active power distribution network. Cattail proe, chenille, wangxiaohui, et al. active power distribution network multi-source collaborative optimization scheduling architecture analysis and application design [ J ] power system automation, 2016, 40 (1): 17-23, 32 define the operation state of the active distribution network as class 3 (fault state, abnormal state, normal state), which is beneficial to performing optimized scheduling on the distribution network aiming at different operation states, but the boundary condition and the conversion relation of the operation states are not established, so that the operation state division method cannot be applied to the typical event simulation of the active distribution network. Liyuyixi, Gu Rong Wei, Lin and jin active power distribution network operation situation time sequence simulation platform based on hybrid simulation [ J ] electric power automation equipment, 2017, 37 (5): 142-147, 154, an event-driven active power distribution network operation situation time sequence simulation method is proposed, which can improve the simulation efficiency and reduce the occupation rate of simulation calculation resources by using an event-driven technology. However, the time sequence simulation method is only limited to analyzing the active power distribution network events at the quasi-steady-state level, and fails to take into account typical dynamic events such as faults, protection and the like in the active power distribution network.
In summary, most of the current power distribution network simulation tools are offline tools, which are not based on actual operation data and do not provide an interface related to the power distribution network operation system. In addition, the appearance of devices such as distributed power sources, charging piles, fuel cells and the like in the active power distribution network causes the lack of a novel element model in a simulation model library; the current mainstream power distribution network simulation software only covers basic simulation functions such as load flow, short circuit calculation and transient simulation, and does not have power distribution network line loss calculation, reliability calculation, risk analysis, fault analysis and transfer supply and other high-level simulation functions of the power distribution network with strong pertinence; the current power distribution network simulation online simulation mainly aims at performing online simulation of a certain time section on time sequence data, and continuous simulation of a plurality of continuous states cannot be performed.
The invention patent of an online optimization simulation system facing a complex power distribution network (CN 201510486151.7) provides an online optimization simulation system facing a complex power distribution network, which comprises the following steps: data layer, encapsulation layer and front end. The data layer, the packaging layer and the front end are sequentially connected, and the data layer is used for acquiring the online data and the local data of the power distribution network and initializing the online data and the local data of the power distribution network; the packaging layer is used for packaging the simulation calculation function into a simulation service, namely one simulation calculation function corresponds to one COM component, and an optimal algorithm is automatically matched to solve the objective function minimum model; the front end is used for providing a unified human-computer interaction unit to call the simulation service of the packaging layer. The system provided by the invention can realize the extraction, analysis and cleaning of the online data of the power distribution network, design a service-oriented optimized computing architecture mode, and provide an optimized computing method based on automatic matching of various algorithms. The structure of the simulation system of the invention is shown in figure 2.
The invention provides an online optimization simulation system for a complex power distribution network, which realizes the extraction, analysis and cleaning of online data of the power distribution network and is used for subsequent optimization calculation. This patent suffers from the following disadvantages:
(1) because the online data is extracted, analyzed and cleaned, the time sequence data of the power distribution network cannot be continuously calculated;
(2) a fixed step length is adopted in the optimization calculation process, and a variable step length technology is not adopted;
(3) only optimization calculation can be carried out, and continuous simulation can not be carried out on a plurality of operation states of the power distribution network.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides an offline/online integrated simulation system for a power distribution network, which comprises:
the client is used for sending a simulation request to the server and obtaining a simulation result sent by the server;
the server is used for performing off-line/on-line continuous state simulation based on the simulation request and power distribution network parameters acquired from a physical power grid by adopting a complex active power distribution network multi-operation state simulation engine and a corresponding power distribution network multi-dimensional resolution model in an event-driven manner, and sending a simulation result to the client;
the complex active power distribution network multi-operation state simulation engine comprises a plurality of simulation kernel algorithm engines of different levels; the power distribution network multi-dimensional resolution model comprises a plurality of power distribution network simulation models with different resolutions.
Preferably, the server end comprises a complex active power distribution network multi-operation state simulation engine, an active power distribution network simulation model library, a support function subsystem and an application function subsystem;
the support function subsystem is used for calling the complex active power distribution network multi-operation state simulation engine and the active power distribution network simulation model library to perform continuous simulation of an offline/online continuous state in the support function aspect when a simulation request is a simulation request in the support function aspect, and the support function comprises the following steps: three-phase load flow calculation, fault analysis, state estimation and reliability calculation;
the application function subsystem is used for calling the complex active power distribution network multi-operation state simulation engine and the active power distribution network simulation model library to perform off-line/on-line continuous state simulation in the aspect of application functions when the simulation request is a simulation request in the aspect of application functions, and the application functions comprise: risk scanning and application reconstruction;
the active power distribution network simulation model base is used for storing a power distribution network multi-dimensional resolution model and selecting power distribution network simulation model combinations with different resolutions from the power distribution network multi-dimensional resolution model to be sent to the complex active power distribution network multi-operation state simulation engine based on the power distribution network state and with the goals of minimum simulation accumulated error and simulation time consumption;
the complex active power distribution network multi-operation state simulation engine is used for selecting simulation kernel algorithm engines of different levels for simulation according to the power distribution network parameters and simulation requests based on event, power distribution network state and simulation model combination selected by an active power distribution network simulation model library according to calling information of a support function subsystem or an application function subsystem, and obtaining the state of the power distribution network at the next moment; the simulation kernel algorithm engines of different levels comprise: a unit-level engine, a function-level engine, and a state-level engine;
wherein the distribution network state is determined by distribution network parameters.
Preferably, the complex active power distribution network multi-operation state simulation engine includes: the simulation kernel algorithm comprises a simulation kernel algorithm engine module, an engine control module, a time sequence event advancing module, a communication module, a result analysis module and an interaction module;
the communication module is used for acquiring parameters of the power distribution network and sending the parameters to the time sequence event advancing module;
the timing sequence event pushing module is used for recording a timing sequence event of active power distribution network simulation, and pulling the engine control module to switch a simulation kernel algorithm engine at the triggering moment of the timing sequence event; the simulation kernel algorithm engine is also used for sending power distribution network parameters to the engine control module and sending power distribution network states and parameters calculated by the simulation kernel algorithm engine to the result analysis module;
the engine control module is used for selecting a simulation kernel algorithm engine based on the state and/or the time sequence event of the power distribution network; the simulation kernel algorithm engine module is also used for sending power distribution network parameters to the simulation kernel algorithm engine module and sending the calculated power distribution network state and parameters to the time sequence event pushing module;
the simulation kernel algorithm engine module is used for storing simulation kernel algorithm engines of a plurality of levels, carrying out simulation calculation on the basis of a simulation model combination selected by the selected simulation kernel algorithm engine, power distribution network parameters and an active power distribution network simulation model library to obtain the power distribution network state and parameters at the next moment of the power distribution network, and sending the power distribution network state and parameters to the engine control module;
the result analysis module is used for extracting the parameters and the states of the power distribution network and sending the parameters and the states to the interaction module;
the interaction module is used for sending the parameters and the states of the simulation power distribution network to the client;
wherein the unit level engine comprises: a numerical integration algorithm of a large differential algebraic equation set, a solving algorithm of a large linear sparse equation set, a solving method of a large nonlinear equation set, a solving method of a differential equation and addition, subtraction, multiplication and division of a matrix; the functional-level engine includes: newton method load flow calculation, alternating current-direct current hybrid load flow calculation, a one-way grounding short circuit fault calculation method, a short line simulation calculation method, a sequential Monte Carlo reliability algorithm and a reactive power optimization method; the state level engine comprises: fault state timing simulation, normal state timing simulation, risk state timing simulation, optimization state timing simulation, and power supply recovery process simulation.
Preferably, the simulation kernel algorithm engine module further comprises: a step size control unit;
and the step size control unit is used for adjusting the simulation step size according to the gradient of the simulation result in the simulation calculation process.
Preferably, the complex active power distribution network multi-operation state simulation engine further includes: a data processing module;
the data processing module is used for processing the power distribution network parameters and sending the processed power distribution network parameters to the time sequence event pushing module.
Preferably, the active power distribution network simulation model library includes: the model selection module is used for selecting a model to be selected;
the model storage module is used for storing a plurality of power distribution network multi-dimensional resolution models with different resolutions and different types, and the types of the power distribution network multi-dimensional resolution models comprise: the system comprises an equipment model, a load model, a node model and a distributed power model, wherein each type comprises a plurality of different specific models; each concrete model has a plurality of resolutions, and concrete models with different resolutions comprise: a fine-grained detailed model, a medium-grained switch function model and a coarse-grained equivalent model;
the model selection module is used for selecting power distribution network multi-dimensional resolution models with different resolutions from the power distribution network multi-dimensional resolution model to be combined with the complex active power distribution network multi-operation state simulation engine for simulation based on the power distribution network state and with the aim of minimizing simulation accumulated errors and simulation time consumption, and is also used for switching the power distribution network multi-dimensional resolution model based on the state transition of the power distribution network corresponding to the time sequence event;
the parameter inheritance module is used for initializing the initialization parameters of the switched multi-dimensional resolution model of the power distribution network when the multi-dimensional resolution model of the power distribution network is switched, and endowing the numerical values of the inheritance parameters of the multi-dimensional resolution model of the power distribution network before switching to the corresponding parameters of the switched multi-dimensional resolution model of the power distribution network; wherein the initialization parameters include: the power supply point voltage, the topological structure and the output power of each distributed power supply, wherein the inherited parameters comprise: load model, load power and inverter control strategy.
Preferably, the calculation formula aiming at the minimum of simulation accumulated error and simulation time consumption is as follows:
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wherein the content of the first and second substances,Foptimizing a target for the model;ra model combination selected for power distribution network simulation;
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is as followslA resolution of the individual device models;
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indicating a status of
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the combination of the representation models isrTime of day state
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The simulated accumulated error of the process of (1);
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the combination of the representation models isrTime of day state
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The simulation of the process of (a) is time consuming;
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the combination of the representation models isrTime of day state
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Transition to state
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the combination of the representation models isrTime of day state
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Simulating the process of (a) a calculated end time,
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calculating the starting time for the simulation for one time;Uis the node voltage of the distribution network,
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is composed ofUThe lower limit of (a) is,
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is composed ofUThe upper limit of (d);
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consuming time for simulation
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The lower limit of (a) is,
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consuming time for simulation
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The upper limit of (a) is,
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accumulating errors for simulation
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The lower limit of (a) is,
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accumulating errors for simulation
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The upper limit of (3).
Preferably, the client includes: the system comprises a graph-model library integrated system and a data visualization module;
the graph-model-library integrated system is used for associating the simulation graph with the equipment data in the preset database based on the corresponding relation with the power distribution network equipment;
and the data visualization module is used for displaying the simulation result in a visualization mode based on the simulation graph, the equipment data and the incidence relation between the simulation graph and the equipment data.
Based on the same invention concept, the application also provides an offline/online integrated simulation method for the power distribution network, which comprises the following steps:
the method comprises the steps that a server side obtains a simulation request from a client side and obtains power distribution network parameters from a physical power grid;
the server side performs off-line/on-line continuous state simulation based on an event-driven mode by adopting a complex active power distribution network multi-operation state simulation engine and a corresponding power distribution network multi-dimensional resolution model based on the power distribution network parameters and the simulation request, and sends a simulation result to the client side;
the complex active power distribution network multi-operation state simulation engine comprises a plurality of simulation kernel algorithm engines of different levels; the power distribution network multi-dimensional resolution model comprises a plurality of power distribution network simulation models with different resolutions.
Preferably, the simulation of the off-line/on-line continuous state by using the complex active power distribution network multi-operation state simulation engine and the corresponding power distribution network multi-dimensional resolution model based on the power distribution network parameters and the simulation request includes:
selecting a support function subsystem or an application function subsystem based on the simulation request;
calling an active power distribution network simulation model library through the support function subsystem or the application function subsystem, and selecting power distribution network simulation model combinations with different resolutions from the power distribution network multi-dimensional resolution model based on the power distribution network state and with the aim of minimizing simulation accumulated errors and simulation time consumption; calling a simulation model combination selected by a complex active power distribution network multi-operation state simulation engine based on an event, a power distribution network state and an active power distribution network simulation model library, and performing off-line/on-line continuous state simulation according to the power distribution network parameters and the simulation request to obtain the state of the power distribution network at the next moment;
the support function includes: three-phase load flow calculation, fault analysis, state estimation and reliability calculation; the application functions include: risk scanning and application reconstruction.
Compared with the closest prior art, the invention has the following beneficial effects:
the invention provides a power distribution network off-line/on-line integrated simulation system and method, which comprises the following steps: the client is used for sending a simulation request to the server and obtaining a simulation result sent by the server for displaying; the system comprises a server side, a client side and a simulation server side, wherein the server side is used for performing off-line/on-line continuous state simulation based on a simulation request and power distribution network parameters acquired from a physical power grid by adopting a complex active power distribution network multi-operation state simulation engine and a corresponding power distribution network multi-dimensional resolution model in an event-driven mode and sending a simulation result to the client side; the complex active power distribution network multi-operation state simulation engine comprises a plurality of simulation kernel algorithm engines of different levels; the power distribution network multi-dimensional resolution model comprises a plurality of power distribution network simulation models with different resolutions; compared with the prior art, the invention has the following advantages: the invention can carry out continuous simulation of a plurality of continuous states by flexibly switching the computing power of the simulation engine.
Drawings
Fig. 1 is a schematic structural diagram of an offline/online integrated simulation system for a power distribution network according to the present invention;
FIG. 2 is a structural diagram of an online optimization simulation system for a complex power distribution network;
fig. 3 is a schematic structural diagram of a multi-state simulation engine of an active power distribution network according to the present invention;
FIG. 4 is a schematic diagram of a simulation kernel algorithm engine provided by the present invention;
FIG. 5 is a schematic diagram of an engine control module provided in the present invention;
FIG. 6 is a schematic diagram of a simulation mechanism for advancing timing events based on a combination of a finite state machine and time domain simulation according to the present invention;
FIG. 7 is a preferred schematic diagram of a power distribution network multi-resolution simulation model provided by the present invention;
FIG. 8 is a schematic diagram of the coarse grain model of FIG. 7;
FIG. 9 is a schematic diagram of the medium grain model of FIG. 7;
FIG. 10 is a schematic diagram of the fine grain model of FIG. 7;
FIG. 11 is a schematic diagram of parameter switching of a simulation model based on initial parameter and inherited parameter partitioning according to the present invention;
FIG. 12 is a schematic diagram of the operation and transition of the power distribution network according to the present invention;
fig. 13 is a schematic diagram of a multi-operation state simulation operation principle of the active power distribution network based on event driving according to the present invention;
FIG. 14 is a schematic diagram of the event driven approach provided by the present invention;
FIG. 15 is a schematic diagram of main functional modules of the power distribution network offline/online integrated simulation system provided by the present invention;
FIG. 16 is a schematic diagram of an on-line digital simulation data flow provided by the present invention;
fig. 17 is a schematic flow chart of an offline/online integrated simulation method for a power distribution network according to the present invention.
Detailed Description
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
Example 1:
the structural schematic diagram of the off-line/on-line integrated simulation system of the power distribution network provided by the invention is shown in fig. 1, and the structural schematic diagram comprises the following components:
the client is used for sending a simulation request to the server and obtaining a simulation result sent by the server for displaying;
the system comprises a server side, a client side and a simulation server side, wherein the server side is used for performing off-line/on-line continuous state simulation based on a simulation request and power distribution network parameters acquired from a physical power grid by adopting a complex active power distribution network multi-operation state simulation engine and a corresponding power distribution network multi-dimensional resolution model in an event-driven mode and sending a simulation result to the client side;
the complex active power distribution network multi-operation state simulation engine comprises a plurality of simulation kernel algorithm engines of different levels; the power distribution network multi-dimensional resolution model comprises a plurality of power distribution network simulation models with different resolutions.
The technical solution of the present invention is fully explained below.
Technical problem to be solved by the invention
In order to overcome the limitation of offline and online integrated simulation of the power distribution network in the prior art, the invention provides an offline and online integrated simulation method and system for the power distribution network, which support online aid decision-making and offline operation section deduction simulation in the operation process of the power distribution network and realize the generation of energy system risk scanning, fault isolation and power supply recovery strategies and the simulation verification evaluation of the treatment scheme effect under the conditions of inaccurate information, complex working conditions and the like. The method has the advantages that global risk scanning, fault simulation deduction and operation mode optimization adjustment are achieved for the power distribution network, accurate positioning and grading of reliability weak points, high loss points and potential safety hazard points of the power distribution network are achieved, fatigue aging and quality hazard equipment of the power distribution network are quickly combed, operation and maintenance major lines and equipment are comprehensively grasped, and a guide basis is provided for a power distribution network technical improvement scheme; the large-scale complex power distribution network frame is guided to evolve and reconstruct to a high-reliability and economical operation direction, and the power consumption requirements of customers are met; the targeted emergency repair force deployment is realized, the power supply recovery time is reduced, and the power supply interruption of a user is avoided; the power distribution network frame is guided to evolve and reconstruct to a high-reliability and economical operation direction, the economic benefit of power distribution network operation is improved, and power grid equipment is fully utilized.
The complete technical scheme provided by the invention
The power distribution network off-line/on-line integrated simulation method and system are based on a simulation calculation core constructed by a power distribution network multi-operation state simulation engine, the simulation of transient state, steady state and medium and long-term dynamic simulation is realized by flexibly switching the calculation capacity of the simulation engine, and meanwhile, a power distribution network multi-dimensional resolution model optimization and self-adaptive matching mechanism is designed, so that a model used by the current simulation can be matched with the simulation engines in different operation states. In the aspect of simulation function, the invention discloses a multi-state simulation method and a variable step length simulation technology of a power distribution network based on event driving, and realizes the simulation of dynamic scenes of faults, risks and power quality.
1. Method for constructing multi-operation-state simulation engine of complex active power distribution network
The simulation engine mainly comprises a simulation kernel algorithm engine, an engine control module, a time sequence event advancing module, a communication module, a data processing module, a result analysis module and the like. As shown in fig. 3, the simulation kernel algorithm engine mainly includes algorithm modules for power distribution network three-phase unbalanced load flow, fault, risk, power restoration, and the like, and the engine control module is responsible for switching the simulation kernel engine according to different operating states, and since the algorithms and parameters of the simulation kernel engine in different operating states need to be adaptively adjusted, the engine control module needs to control and drive in the execution process. The time sequence event propulsion module is a process machine driving module which draws the simulation engine to continuously run forwards according to a specific strategy, and the time sequence event propulsion module realizes the response to various simulation events through the interruption, the parallel, the switching and the like of the process.
1-1, simulation kernel algorithm engine
The complex active power distribution network simulation kernel algorithm engine is mainly used for solving power distribution network differential simulation and large-scale linear equations. The invention provides a method for constructing a simulation kernel algorithm engine of an active power distribution network based on unit level, function level, state level and the like, which is shown in figure 4. The unit level is mainly composed of a numerical calculation method library for realizing various simulation calculation functions, and comprises a large differential algebraic equation, namely a DAE equation set numerical integration algorithm, a large linear sparse equation set solving algorithm, a large nonlinear equation set solving method, a differential equation solving method, addition, subtraction, multiplication and division of a matrix and the like; the functional level mainly aims at solving each function of the complex active power distribution network, such as Newton method load flow calculation, alternating current-direct current hybrid load flow calculation, a one-way grounding short circuit fault calculation method, a short line simulation calculation method, a sequential Monte Carlo reliability algorithm, a reactive power optimization method and the like; the state level mainly faces to different running states of the active power distribution network, the running states of the active power distribution network can be divided into various different states such as normal, fault, risk, optimization, power supply recovery and the like, and time sequence solving aiming at the different running states is composed of a state level algorithm kernel.
1-2, engine control module
The complex active power distribution network simulation engine control module is mainly used for switching and configuring management of simulation kernel algorithm engines in different running states. The invention provides a method for constructing an engine control module based on multiple parameter identification, which is shown in figure 5. The simulation engine control module firstly assigns the power distribution network model by using the initial operation parameters and carries out primary calculation by using the steady-state model so as to enable the model to enter a continuous simulation process. When the multi-state simulation model finishes the operation of a time step by a steady-state or dynamic model, updating all the operation parameters by the operation result in the step, and simultaneously judging whether the operation process reaches the preset simulation duration: if the preset time length is reached, terminating the simulation; if the preset time length is not reached, judging the running state of the system again, and further judging the running state of the system in the next long-term operation.
The engine control module based on multiple parameter identification is mainly characterized in that different characteristic quantities and judgment conditions thereof are designed for 5 power distribution network operation states such as normal state, optimization state, risk state, failure state, recovery state and the like as triggering conditions of simulation engine switching control under different operation states:
1-2-1) normal state: when the conditions such as risks, faults and the like do not occur in the operation area of the active power distribution network and the voltage, the line current and the network loss index of each node are in a state to be optimized in the operation of the system, the system is considered to be in a normal operation state.
1-2-2) optimization state: and the running state of the power distribution network when the running index reaches the optimization target. Taking the network loss rate as an example, when the system reduces the network loss rate to the threshold value through optimizing the reconstruction and the likeη opt When the system is in the next step, the system is transferred to an optimization state; otherwise, the system is transferred from the optimization state to the normal state. In general, the state threshold is optimizedη opt Under normal operation, the target area is flatThe average transmission loss is 0.4 times.
1-2-3) risk status: the system approaches a critical state where normal operation cannot be maintained. When the maximum voltage deviation exceeds a risk thresholdU r When the system is in the risk state, the system enters the risk state; and vice versa to other states.
1-2-4) fault condition: when the protection device detects that the overcurrent signal or the voltage deviation exceeds the safe operation limit value, the power distribution network is judged to enter a fault state. Setting the voltage fault threshold toU f The relay protection setting value isI f 。
1-2-5) recovery state: when the system has a fault, the fault is removed, and when a power loss area still exists, the system is in a recovery state; when the topology is complete and power is restored, the system is out of the restoration state.
1-3, time sequence event advancing module
The invention provides a time sequence time advancing module based on the combination of a finite state machine and time domain simulation, which is used as a traction module of a complex active power distribution network multi-state simulation engine and provides a direction for the switching and continuous simulation of the simulation engine.
As shown in fig. 6, the specific combination manner of the time sequence events based on the combination of the finite state machine and the time domain simulation adopted by the time sequence event simulation module in the present invention is as follows: the simulation of the active power distribution network is dragged by the time sequence event propelling module, time domain simulation is continuously carried out forward along a time axis, and the time domain simulation is triggered when an event of each running state (a normal state, an optimized state, a risk state, a fault state and a recovery state) is receivedt f Performing model and simulation core algorithm engine switching, and
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the data of the simulation model are used as initialization, small-step transient fine simulation is carried out, and the simulation is continued
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The simulation engine is then tuned to either a large step simulation or a steady state simulation. In this way, discrete switching of the simulation engine between different states can be realized while the active power distribution network is progressive along a time axis.
2. Optimal and adaptive matching mechanism for multidimensional resolution model of power distribution network
The invention provides a power distribution network multi-dimensional resolution model optimization and self-adaption matching mechanism aiming at the situation that how to select a proper simulation model by adopting simulation engine calculation in different states is mainly solved, and the specific technical implementation comprises two steps: optimizing a multi-resolution simulation model of the power distribution network and carrying out parameter inheritance during simulation model switching.
2-1 optimization method of multi-resolution simulation model of power distribution network
As shown in fig. 7, in the present invention, an active power distribution network simulation model library including 18 types of device models, 17 types of load models, 9 types of node models, and 12 types of distributed power models is constructed, and for each model, a multidimensional resolution model is constructed, taking VSC as an example, and the model library includes a fine-grained detailed model, a medium-grained switching function model, and a coarse-grained equivalent model, and each model can be adapted to simulation in different operating states, so that a simulation error is minimized, and a simulation speed is fastest. Fig. 8-10 are the coarse-grained model, the medium-grained model, and the fine-grained model of fig. 7, respectively.
The optimal model of the power distribution network multi-resolution simulation model provided by the invention is shown as a formula (1):
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（1）
wherein the content of the first and second substances,Foptimizing a target for the model;ra model combination selected for power distribution network simulation;
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is as followslA resolution of the individual device models;
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indicating a status of
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The process of (2);
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the combination of the representation models isrTime of day state
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The simulated accumulated error of the process of (1);
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the combination of the representation models isrTime of day state
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The simulation of the process of (a) is time consuming;
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the combination of the representation models isrTime of day state
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Of process (2)kThe calculated value of the sub-iteration calculation,
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the combination of the representation models isrTime of day state
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Simulating the process of (a) a calculated end time,
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calculating the starting time for the simulation for one time;Uis the node voltage of the distribution network,
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is composed ofUThe lower limit of (a) is,
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is composed ofUThe upper limit of (d);
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consuming time for simulation
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The lower limit of (a) is,
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consuming time for simulation
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The upper limit of (a) is,
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accumulating errors for simulation
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The lower limit of (a) is,
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accumulating errors for simulation
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The upper limit of (3).
The multi-resolution simulation model of the power distribution network shown in the formula (1) can preferably select the model combination in the current state and the state conversion process, and because the power distribution network is formed by connecting a plurality of devices during system-level simulation, compared with the traditional single simulation model matching method, the method has two obvious characteristics by the preferred method: 1) the system-level combined resolution model is preferably selected, and different resolutions of each device are determined, so that the cascade error of the process of constructing the system-level model by a single model is reduced to the maximum extent; 2) compared with a simulation selection model in which only one state is considered in a traditional single simulation model, the accumulated errors in the migration process of different states considered in the optimal method have the following significant advantages: and in consideration of time scale, the obvious reduction of simulation precision caused by accumulated error diffusion caused by continuous switching of states is avoided to the maximum extent.
2-2 model switching and parameter integrating method
The power distribution network model tracking simulation engine is switched, besides the optimization of the 2-1 power distribution network multi-resolution simulation model, the problem that the parameter inheritance of different simulation models is required to be solved, the unreasonable model parameter inheritance easily causes the sudden change of the simulation result in the model switching process, and more burrs are generated on a result curve, so that the reduction of the simulation precision is caused. In order to solve the problem, the invention provides a simulation model parameter switching method based on initial parameter and inherited parameter division, which is used for coordinating the stable transition of model parameters between steady-state simulation and dynamic simulation. As shown in fig. 11, the simulation model-related parameters are divided from the perspective of initialization parameters and inherited parameters, where the initialization parameters are parameters set at the beginning of each model-using stage, and the parameters change before and after model switching; the inherited parameters are inherited parameters of the new model and the old model, and are not changed before and after the model switching, and specifically, the load model, the load power, namely the load data, the transfer preset scheme, the inverter control strategy and the like are used as initialization and are directly loaded into the new model after the model switching; the voltage of the power supply point, the topological structure and the output power of each distributed power supply are used as parameters to be inherited, and the error of the voltage of each node before and after the model is ensured not to generate sudden change, so that the simulation result curve is relatively smooth, and the simulation instability caused by the sudden change is avoided.
3. Multi-operation state simulation scene realization of power distribution network off-line/on-line integrated simulation system
The method mainly adopts an event-driven mechanism and a variable step length technology to realize a multi-operation state simulation scene of the power distribution network off-line/on-line integrated simulation system.
3-1 power distribution network multi-state simulation method based on event driving
The operation state of the distribution network is not kept unchanged, and the conversion relation among the 5 operation states is shown in fig. 12. When the running state of the power distribution network changes, the simulation model needs to be switched and certain initialization needs to be carried out. Based on finite state machine theory, the operation process of the distribution network state can be equivalent to a state transition process driven by an event. The invention relates to a power distribution network multi-state simulation method based on event driving. The method has the advantages that the typical events and the corresponding characteristic parameters are judged, the operation state of the active power distribution network is kept or transferred, the simulation model is guided to be automatically switched along with the change of the operation state, and the multi-state simulation of the power distribution network is realized. The simulation operation principle of the multi-operation state of the power distribution network based on event driving is shown in fig. 13.
The core of event-driven is the event. The method is a driving mode of triggering simulation calculation by event points based on a series of event points.
The following describes a simulation mode triggered by an event point by taking power distribution network flow simulation as an example. Events that can change the power flow distribution mainly include load size changes, equipment parameter changes, line or equipment faults, and the like. Some of the events are already given at the beginning of the simulation, such as determined load change conditions, fault conditions and the like; some of the simulation results cannot be completely predicted at the beginning, but the simulation results can be predicted in the simulation process, such as switching change conditions of each controllable element, faults which randomly occur under certain conditions, and the like. For the initially determined event points, the priority of each event is determined, and one of the events is listed and sequenced to be used as a trigger point of load flow calculation; for an event point that can be anticipated in the simulation, this event can be inserted into the team of subsequent events in anticipation of the event to trigger the flow calculation at the appropriate time. Thus, after the update is calculated at each event point, the simulation program should already know the time of occurrence of the next event point. Since all events occurring in the simulation are generated by the simulation program, i.e. determined by the given external inputs or internal parameters, no unforeseen events are missed. Thus, all events except random events are accurately predictable. Although the random event cannot be accurately predicted, the possible time points of the random event can be completely enumerated, so that the possibility of missing the random event is eliminated.
When the event-driven mode is used for triggering calculation, the basis for sequencing each event is generally the occurrence time of the event, and the occurrence time is used for marking each event, so that the events can be conveniently managed. Therefore, in the event-driven method, a time axis is set, and event points are inserted into corresponding scales on the time axis one by one according to the occurrence time of the event points. The time-driven manner is shown in fig. 14.
If 2 or more events occur at the same time point, the events are processed according to a certain priority. Specifically, when some important events occur simultaneously, the priority logic is defined by the software system, and when other unimportant events occur simultaneously, the priority logic adopts the default setting of the software system.
3-2, variable step length technique
In the process of online simulation, time sequence data of a certain section is simulated, and the frequency of sampling calculation of a simulation object is required to be smaller than the fluctuation frequency of the simulation object. Fluctuations in power flow in a power distribution network are mainly caused by load changes: during the peak time period and the valley time period, the load changes slowly; in the time interval with alternating peaks and valleys, the load changes more sharply. In a power distribution network with a large amount of distributed energy, the load changes are more severe and difficult to predict. Therefore, if a fixed-step simulation mode is adopted, an extremely small simulation step is inevitably required, so that the simulation speed is greatly reduced, and the calculation resources are wasted.
In the off-line/on-line integrated simulation system of the power distribution network, a variable step size simulation technology is used.
The variable-step simulation technology is a technology that in the process of simulation, the simulation step size is changed along with the change of the fluctuation condition of a simulation object, and the simulation technology automatically adapts to the requirements of the simulation object so as to shorten the simulation time and improve the simulation precision. The variable step length technology requires that the change condition of a simulation object is concerned at any time in the simulation calculation, the gradient of the simulation object is calculated, and the simulation step length is adjusted accordingly. The variable-step-size simulation can effectively solve the contradiction between the simulation precision and the simulation speed under the fixed-step-size simulation, and effectively save the computing resources.
When the running state of the power distribution network is changed, simulation model switching is required, and a corresponding initialization process is executed:
3-2-1) when the power distribution network is switched from a normal state to a risk state or a fault state, the simulation model needs to be switched from the steady-state model to the dynamic model, and the initial values of the voltage of the power supply point after switching and the distributed photovoltaic output power are equal to the calculation result of the steady-state model in the last time section before switching.
3-2-2) when the power distribution network is switched to a normal state from a risk state, a fault state or a recovery state, the simulation model needs to be switched from the dynamic model to the steady-state model, and the initial values of the voltage of each node and the distributed photovoltaic output power after switching are equal to the calculation result of the last step length before model switching.
4. Offline/online integrated simulation method for power distribution network
The power distribution network off-line/on-line integrated simulation system aims at a power distribution network, measures data of all points of a power distribution automation terminal, namely a DA terminal acquisition system, and serves as an on-line data source, a digital simulation model of the power distribution network is formed in the simulation system, on-line power flow, faults, reliability, risk, state estimation, network reconstruction of the power distribution network, production aid decision information, and decision basis for power supply system operation evaluation and fault rapid power supply recovery are executed.
The power distribution network off-line/on-line integrated simulation system consists of a server side, a client side and a data interface. The server is deployed on a server group and comprises three functions, namely basic data processing, a support function and an application function. The basic data processing is realized by a basic data processing module, the supporting function comprises a three-phase power flow module, a fault analysis module, a state estimation module and a reliability calculation module, and the application function comprises a risk scanning module, a network reconstruction module and the like. The client can be deployed on a user desktop or a large display screen and comprises a graph-model integration system and a data visualization module. The main functional modules of the power distribution network online/offline integrated simulation system are shown in fig. 15.
(1) The graph-model library integrated system comprises: the simulation graph is used for integrating the simulation graph and information corresponding to the simulation graph in the database, so that the graph and the data are associated together according to a certain relation, the associated data and the simulation graph are defined and modified by operating the simulation graph and taking the data in the database as the attribute of the graph, and the binding of the data and the graph is realized.
(2) And (3) state estimation: when bad data appear in the measured data, the simulation system carries out state estimation based on the measured data, identifies the bad data, eliminates the bad data and calculates the correct value of the bad data, and supports advanced application of the power system.
(3) And (3) tidal current simulation: aiming at the change of parameters such as running state, load fluctuation and the like in an energy system, online and offline integrated tidal current simulation is realized, and the change and trend of the electrical quantity of each node in the system are displayed.
(4) And (3) reliability analysis: and (4) carrying out sensitivity analysis on related factors influencing the power supply reliability index to obtain related characteristic quantity which is sensitive to the power supply reliability index.
(5) Risk scanning: by utilizing the power grid operation data, the risk batch scanning, the weak point analysis, the risk source statistics and rating and the risk early warning of the power distribution network can be realized, the operation risk, the external risk and the equipment body risk in a target area can be rapidly scanned, the operation and maintenance strategy can be pertinently developed aiming at the scanned risk, and the robustness of the power distribution network is improved.
(6) And (3) fault analysis: the fault diagnosis method can simulate various short circuit and disconnection faults of the system caused by physical attack, artificial damage and line and equipment problems, calculate the voltage and current levels of the system when the system fails, evaluate the severity of the system when the system fails, and generate a fault isolation scheme, thereby providing an auxiliary decision basis for emergency treatment of the fault.
(7) Network reconstruction: the topological structure of the system is changed by changing the on-off state of the switch at each position in the system, when one or more points in the system have faults, a network reconstruction and recovery power supply scheme is generated by using the standby line and the switch in the network, the load transfer is completed, and the system load power supply is ensured to the maximum extent.
The online/offline integrated simulation system can be used for online and offline simulation, and the main process is as follows:
4-1, on-line simulation
The online/offline integrated simulation system adopts a dual-bus mode for network connection, and adopts an independent network for data reading and writing and external data source extraction, so that the real-time performance of data transmission is ensured. The communication bus is connected with the simulation client and the simulation server, the client uses the DCOM component to call the simulation service provided by the server based on an open interface, and the simulation coordination server distributes the tasks to be processed to each cluster node. If the network scale is large, task cutting service is required to be called, and the network is automatically partitioned to realize parallel computing.
Fig. 16 shows a data flow at a server end of the simulation system, where the server end provides a unified simulation service, and the method specifically includes the following steps:
4-1-1) defining a coordination server from distributed cluster by means of appointed mode, and the main function of said server is to respond to client access request and maintain a pending task queueA={a 1,a 2,a 3⋯, and distributing the simulation tasks based on the dynamic polling method, wherein the specific selection process comprises the following steps:
4-1-1a) for all nodes participating in the simulation (number of nodes isN) Polling is carried out, the real-time performance and the current task quantity of each node are obtained, and the time of the current task quantity is estimated to bet q (q<N)。
4-1-1b) calculating the estimated time of the current tasks of all nodesT={T 1,T 2,T 3⋯ and coefficient of performance𝜕={𝜕 1,𝜕,𝜕 3⋯, and obtaining a task node set Re =to be allocatedf min(T×𝜕,m) Here, thef min(S,m) Presentation fetch setSIs smallestmAnd (4) the number.
4-1-1c) according to the set RemAnd updating the task queue to be processed by each task.
4-1-2) reading a target network in the task queue from the database, performing unified topology and sharing the target network to each simulation server, coordinating the continuous monitoring of the servers, continuously updating, and reasonably distributing the tasks to the clusters based on the real-time performance analysis of each simulation server. And if the number of the network nodes of a certain task exceeds a threshold value, jumping to the step 4-1-3), otherwise, jumping to the step 4-1-4).
4-1-3) cutting simulation tasks with complex network scale and more nodes, distributing the simulation tasks to an idle simulation server, maintaining a coordinated communication process, and then obtaining a final result by integrating intermediate results of all nodes.
4-1-4) ending the simulation calculation and returning the simulation result.
4-2, offline simulation
The online/offline integrated simulation system performs simulation analysis based on section data at a certain moment. The working principle of the online/offline integrated simulation system and the power grid for matching to develop online simulation is to perform analysis, prediction and control based on online operation data, and the online/offline integrated simulation system is to perform analysis, prediction and simulation based on historical data and user input data independent of the working principle of the power grid for developing offline simulation.
5. Interface
The off-line/on-line integrated simulation system of the power distribution network is provided with an interface with a data acquisition and monitoring control System (SCADA), the interface is deployed at a server end and mainly comprises a three-remote data receiving interface with power distribution automation. The data interface realizes data exchange between the power distribution network off-line/on-line integrated simulation system and the physical power grid through the three remote modules, and data used by the power distribution network off-line/on-line integrated simulation system is stored in the server. According to the requirement, the power distribution network off-line/on-line integrated simulation system can be provided with interfaces of a PMS (system management system), a GIS (geographic information system) and other systems.
Example 2:
based on the same inventive concept, the application also provides an offline/online integrated simulation method for the power distribution network, as shown in fig. 17, comprising the following steps:
step 1: the method comprises the steps that a server side obtains a simulation request from a client side and obtains power distribution network parameters from a physical power grid;
step 2: the server side is used for carrying out off-line/on-line continuous state simulation based on the power distribution network parameters and the simulation request by adopting a complex active power distribution network multi-operation state simulation engine and a corresponding power distribution network multi-dimensional resolution model in an event-driven mode, and sending a simulation result to the client side;
the complex active power distribution network multi-operation state simulation engine comprises a plurality of simulation kernel algorithm engines of different levels; the power distribution network multi-dimensional resolution model comprises a plurality of power distribution network simulation models with different resolutions.
The step 2 comprises the following steps:
step 2-1: selecting a support function subsystem or an application function subsystem based on the simulation request;
step 2-2: calling an active power distribution network simulation model library through a support function subsystem or an application function subsystem, and selecting power distribution network simulation model combinations with different resolutions from a power distribution network multidimensional resolution model based on the power distribution network state and with the aim of minimizing simulation accumulated errors and simulation time consumption;
step 2-3: meanwhile, a complex active power distribution network multi-operation state simulation engine is called to perform off-line/on-line continuous state simulation based on a simulation model combination selected by an event, a power distribution network state and an active power distribution network simulation model library according to power distribution network parameters and simulation requests to obtain the state of the power distribution network at the next moment;
the support function includes: three-phase load flow calculation, fault analysis, state estimation and reliability calculation; the application functions include: risk scanning and application reconstruction.
The power distribution network off-line/on-line integrated simulation system and method provided by the invention have the following advantages:
(1) the power distribution network off-line/on-line integrated simulation system can support on-line aid decision-making and off-line operation section deduction simulation in the power distribution network operation process, and achieves simulation verification evaluation of the effects of risk scanning, fault isolation and power supply recovery strategies of the energy system under the conditions of inaccurate information, complex working conditions and the like and the effects of a disposal scheme.
(2) The off-line/on-line integrated simulation system of the power distribution network can realize archive data, operation data, topology data management and the like, and ensure the data consistency of the power distribution network;
(3) related simulation calculation functions such as reliability calculation, risk analysis, fault transfer analysis and the like are realized, auxiliary decisions are provided for scheduling personnel and operation and maintenance personnel, and the operation economy and the operation reliability of the power distribution network are improved;
(4) the method comprises the steps that versioning management is carried out on a constructed and transformed target power grid through a software module, and multi-scheme compilation of a future power grid is achieved;
(5) the construction transformation scheme is evaluated through various electric calculations and grid analysis, the technical indexes of different schemes are compared, the optimal scheme is determined, and the aid decision is realized.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be noted that the above-mentioned embodiments are only for illustrating the technical solutions of the present application and not for limiting the scope of protection thereof, and although the present application is described in detail with reference to the above-mentioned embodiments, those skilled in the art should understand that after reading the present application, they can make various changes, modifications or equivalents to the specific embodiments of the application, but these changes, modifications or equivalents are all within the scope of protection of the claims to be filed.

Claims (10)

1. An off-line/on-line integrated simulation system for a power distribution network is characterized by comprising:
the client is used for sending a simulation request to the server; obtaining a simulation result sent by the server;
the server is used for performing off-line/on-line continuous state simulation based on the simulation request and power distribution network parameters acquired from a physical power grid by adopting a complex active power distribution network multi-operation state simulation engine and a corresponding power distribution network multi-dimensional resolution model in an event-driven manner, and sending a simulation result to the client;
the complex active power distribution network multi-operation state simulation engine comprises a plurality of simulation kernel algorithm engines of different levels; the power distribution network multi-dimensional resolution model comprises a plurality of power distribution network simulation models with different resolutions.
2. The system of claim 1, wherein the server side comprises a complex active power distribution network multi-operation state simulation engine, an active power distribution network simulation model library, a support function subsystem and an application function subsystem;
the support function subsystem is used for calling the complex active power distribution network multi-operation state simulation engine and the active power distribution network simulation model library to perform continuous simulation of an offline/online continuous state in the support function aspect when a simulation request is a simulation request in the support function aspect, and the support function comprises the following steps: three-phase load flow calculation, fault analysis, state estimation and reliability calculation;
the application function subsystem is used for calling the complex active power distribution network multi-operation state simulation engine and the active power distribution network simulation model library to perform off-line/on-line continuous state simulation in the aspect of application functions when the simulation request is a simulation request in the aspect of application functions, and the application functions comprise: risk scanning and application reconstruction;
the active power distribution network simulation model base is used for storing a power distribution network multi-dimensional resolution model and selecting power distribution network simulation model combinations with different resolutions from the power distribution network multi-dimensional resolution model to be sent to the complex active power distribution network multi-operation state simulation engine based on the power distribution network state and with the goals of minimum simulation accumulated error and simulation time consumption;
the complex active power distribution network multi-operation state simulation engine is used for selecting simulation kernel algorithm engines of different levels for simulation according to the power distribution network parameters and simulation requests based on event, power distribution network state and simulation model combination selected by an active power distribution network simulation model library according to calling information of a support function subsystem or an application function subsystem, and obtaining the state of the power distribution network at the next moment; the simulation kernel algorithm engines of different levels comprise: a unit-level engine, a function-level engine, and a state-level engine;
wherein the distribution network state is determined by distribution network parameters.
3. The system of claim 2, wherein the complex active power distribution network multi-operation state simulation engine comprises: the simulation kernel algorithm comprises a simulation kernel algorithm engine module, an engine control module, a time sequence event advancing module, a communication module, a result analysis module and an interaction module;
the communication module is used for acquiring parameters of the power distribution network and sending the parameters to the time sequence event advancing module;
the timing sequence event pushing module is used for recording a timing sequence event of active power distribution network simulation, and pulling the engine control module to switch a simulation kernel algorithm engine at the triggering moment of the timing sequence event; the simulation kernel algorithm engine is also used for sending power distribution network parameters to the engine control module and sending power distribution network states and parameters calculated by the simulation kernel algorithm engine to the result analysis module;
the engine control module is used for selecting a simulation kernel algorithm engine based on the state and/or the time sequence event of the power distribution network; the simulation kernel algorithm engine module is also used for sending power distribution network parameters to the simulation kernel algorithm engine module and sending the calculated power distribution network state and parameters to the time sequence event pushing module;
the simulation kernel algorithm engine module is used for storing simulation kernel algorithm engines of a plurality of levels, carrying out simulation calculation on the basis of a simulation model combination selected by the selected simulation kernel algorithm engine, power distribution network parameters and an active power distribution network simulation model library to obtain the power distribution network state and parameters at the next moment of the power distribution network, and sending the power distribution network state and parameters to the engine control module;
the result analysis module is used for extracting the parameters and the states of the power distribution network and sending the parameters and the states to the interaction module;
the interaction module is used for sending the parameters and the states of the simulation power distribution network to the client;
wherein the unit level engine comprises: a numerical integration algorithm of a large differential algebraic equation set, a solving algorithm of a large linear sparse equation set, a solving method of a large nonlinear equation set, a solving method of a differential equation and addition, subtraction, multiplication and division of a matrix; the functional-level engine includes: newton method load flow calculation, alternating current-direct current hybrid load flow calculation, a one-way grounding short circuit fault calculation method, a short line simulation calculation method, a sequential Monte Carlo reliability algorithm and a reactive power optimization method; the state level engine comprises: fault state timing simulation, normal state timing simulation, risk state timing simulation, optimization state timing simulation, and power supply recovery process simulation.
4. The system of claim 3, wherein the simulation kernel algorithm engine module further comprises: a step size control unit;
and the step size control unit is used for adjusting the simulation step size according to the gradient of the simulation result in the simulation calculation process.
5. The system of claim 3, wherein the complex active power distribution network multiple operation state simulation engine comprises further comprising: a data processing module;
the data processing module is used for processing the power distribution network parameters and sending the processed power distribution network parameters to the time sequence event pushing module.
6. The system of claim 3, wherein the library of active power distribution network simulation models comprises: the model selection module is used for selecting a model to be selected;
the model storage module is used for storing a plurality of power distribution network multi-dimensional resolution models with different resolutions and different types, and the types of the power distribution network multi-dimensional resolution models comprise: the system comprises an equipment model, a load model, a node model and a distributed power model, wherein each type comprises a plurality of different specific models; each concrete model has a plurality of resolutions, and concrete models with different resolutions comprise: a fine-grained detailed model, a medium-grained switch function model and a coarse-grained equivalent model;
the model selection module is used for selecting power distribution network multi-dimensional resolution models with different resolutions from the power distribution network multi-dimensional resolution model to be combined with the complex active power distribution network multi-operation state simulation engine for simulation based on the power distribution network state and with the aim of minimizing simulation accumulated errors and simulation time consumption, and is also used for switching the power distribution network multi-dimensional resolution model based on the state transition of the power distribution network corresponding to the time sequence event;
the parameter inheritance module is used for initializing the initialization parameters of the switched multi-dimensional resolution model of the power distribution network when the multi-dimensional resolution model of the power distribution network is switched, and endowing the numerical values of the inheritance parameters of the multi-dimensional resolution model of the power distribution network before switching to the corresponding parameters of the switched multi-dimensional resolution model of the power distribution network; wherein the initialization parameters include: the power supply point voltage, the topological structure and the output power of each distributed power supply, wherein the inherited parameters comprise: load model, load power and inverter control strategy.
7. The system of claim 6, wherein the calculation aimed at minimizing simulation cumulative error and simulation elapsed time is as follows:
Figure 544122DEST_PATH_IMAGE001
wherein the content of the first and second substances,Foptimizing a target for the model;ra model combination selected for power distribution network simulation;
Figure 228044DEST_PATH_IMAGE002
is as followslA resolution of the individual device models;
Figure 848381DEST_PATH_IMAGE003
indicating a status of
Figure 33375DEST_PATH_IMAGE004
Transition to state
Figure 55557DEST_PATH_IMAGE005
The process of (2);
Figure 910381DEST_PATH_IMAGE006
the combination of the representation models isrTime of day state
Figure 18014DEST_PATH_IMAGE004
Transition to state
Figure 741120DEST_PATH_IMAGE005
The simulated accumulated error of the process of (1);
Figure 620738DEST_PATH_IMAGE007
the combination of the representation models isrTime of day state
Figure 177622DEST_PATH_IMAGE004
Transition to state
Figure 772551DEST_PATH_IMAGE005
The simulation of the process of (a) is time consuming;
Figure 299347DEST_PATH_IMAGE008
the combination of the representation models isrTime of day state
Figure 30543DEST_PATH_IMAGE004
Transition to state
Figure 492748DEST_PATH_IMAGE005
Of process (2)kThe calculated value of the sub-iteration calculation,
Figure 574974DEST_PATH_IMAGE009
is as followsk-1 iteration calculation value;
Figure 905461DEST_PATH_IMAGE010
the combination of the representation models isrTime of day state
Figure 632109DEST_PATH_IMAGE004
Transition to state
Figure 389849DEST_PATH_IMAGE005
Simulating the process of (a) a calculated end time,
Figure 693791DEST_PATH_IMAGE011
calculating the starting time for the simulation for one time;Uis the node voltage of the distribution network,
Figure 703336DEST_PATH_IMAGE012
is composed ofUThe lower limit of (a) is,
Figure 406194DEST_PATH_IMAGE013
is composed ofUThe upper limit of (d);
Figure 334836DEST_PATH_IMAGE014
consuming time for simulation
Figure 391653DEST_PATH_IMAGE015
The lower limit of (a) is,
Figure 673730DEST_PATH_IMAGE016
consuming time for simulation
Figure 499604DEST_PATH_IMAGE015
The upper limit of (a) is,
Figure 333568DEST_PATH_IMAGE017
accumulating errors for simulation
Figure 18627DEST_PATH_IMAGE018
The lower limit of (a) is,
Figure 229028DEST_PATH_IMAGE019
accumulating errors for simulation
Figure 909408DEST_PATH_IMAGE018
The upper limit of (3).
8. The system of claim 1, wherein the client comprises: the system comprises a graph-model library integrated system and a data visualization module;
the graph-model-library integrated system is used for associating the simulation graph with the equipment data in the preset database based on the corresponding relation with the power distribution network equipment;
and the data visualization module is used for displaying the simulation result in a visualization mode based on the simulation graph, the equipment data and the incidence relation between the simulation graph and the equipment data.
9. An off-line/on-line integrated simulation method for a power distribution network is characterized by comprising the following steps:
the method comprises the steps that a server side obtains a simulation request from a client side and obtains power distribution network parameters from a physical power grid;
the server side performs off-line/on-line continuous state simulation based on an event-driven mode by adopting a complex active power distribution network multi-operation state simulation engine and a corresponding power distribution network multi-dimensional resolution model based on the power distribution network parameters and the simulation request, and sends a simulation result to the client side;
the complex active power distribution network multi-operation state simulation engine comprises a plurality of simulation kernel algorithm engines of different levels; the power distribution network multi-dimensional resolution model comprises a plurality of power distribution network simulation models with different resolutions.
10. The method of claim 9, wherein the simulation of the off-line/on-line continuous state based on the power distribution network parameters and the simulation request by using a complex active power distribution network multi-operation state simulation engine and a corresponding power distribution network multi-dimensional resolution model comprises:
selecting a support function subsystem or an application function subsystem based on the simulation request;
calling an active power distribution network simulation model library through the support function subsystem or the application function subsystem, and selecting power distribution network simulation model combinations with different resolutions from the power distribution network multi-dimensional resolution model based on the power distribution network state and with the aim of minimizing simulation accumulated errors and simulation time consumption; calling a simulation model combination selected by a complex active power distribution network multi-operation state simulation engine based on an event, a power distribution network state and an active power distribution network simulation model library, and performing off-line/on-line continuous state simulation according to the power distribution network parameters and the simulation request to obtain the state of the power distribution network at the next moment;
the support function includes: three-phase load flow calculation, fault analysis, state estimation and reliability calculation; the application functions include: risk scanning and application reconstruction.
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Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112818606A (en) * 2021-02-09 2021-05-18 北京殷图仿真技术有限公司 Digital simulation system and method
CN113435002A (en) * 2021-05-14 2021-09-24 贵州正航众联电力建设有限公司 Big data power distribution room simulation system and method
CN113536578A (en) * 2021-07-21 2021-10-22 全球能源互联网研究院有限公司 Power grid equipment element energy information modeling and simulation analysis method
CN114038283A (en) * 2021-11-19 2022-02-11 广东电网有限责任公司 Flexible direct current distribution network steady state and transient state off-line simulation and training system
CN114142471A (en) * 2021-11-29 2022-03-04 江苏科技大学 Ship integrated power system reconstruction method considering communication faults
CN114239324A (en) * 2022-02-23 2022-03-25 南方电网数字电网研究院有限公司 Micro energy network state transition space modeling method based on hybrid automaton
CN117422427A (en) * 2023-12-19 2024-01-19 广东省建设工程质量安全检测总站有限公司 Online batch analysis method and system for low-strain data
CN117807154A (en) * 2024-02-28 2024-04-02 成都菲宇科技有限公司 Time sequence data visualization method, device and medium for display system

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080262820A1 (en) * 2006-07-19 2008-10-23 Edsa Micro Corporation Real-time predictive systems for intelligent energy monitoring and management of electrical power networks
CN103455948A (en) * 2013-08-06 2013-12-18 国家电网公司 Power distribution system multi-dimensional multi-resolution modeling and analysis method
CN104504199A (en) * 2014-12-22 2015-04-08 国家电网公司 Workflow engine-based multi-time scale active distribution network interactive simulation method
CN104537908A (en) * 2014-12-17 2015-04-22 国电南瑞科技股份有限公司 Multi-stage scheduling integrated simulation system based on model sharing and method
CN105205231A (en) * 2015-09-06 2015-12-30 中国电力科学研究院 DCOM (distributed component object model)-based digital simulation system for distribution network
CN106340968A (en) * 2016-10-21 2017-01-18 国网山东省电力公司电力科学研究院 Integrated support system and method for management and control of power distribution network

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080262820A1 (en) * 2006-07-19 2008-10-23 Edsa Micro Corporation Real-time predictive systems for intelligent energy monitoring and management of electrical power networks
CN103455948A (en) * 2013-08-06 2013-12-18 国家电网公司 Power distribution system multi-dimensional multi-resolution modeling and analysis method
CN104537908A (en) * 2014-12-17 2015-04-22 国电南瑞科技股份有限公司 Multi-stage scheduling integrated simulation system based on model sharing and method
CN104504199A (en) * 2014-12-22 2015-04-08 国家电网公司 Workflow engine-based multi-time scale active distribution network interactive simulation method
CN105205231A (en) * 2015-09-06 2015-12-30 中国电力科学研究院 DCOM (distributed component object model)-based digital simulation system for distribution network
CN106340968A (en) * 2016-10-21 2017-01-18 国网山东省电力公司电力科学研究院 Integrated support system and method for management and control of power distribution network

Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112818606A (en) * 2021-02-09 2021-05-18 北京殷图仿真技术有限公司 Digital simulation system and method
CN113435002A (en) * 2021-05-14 2021-09-24 贵州正航众联电力建设有限公司 Big data power distribution room simulation system and method
CN113536578A (en) * 2021-07-21 2021-10-22 全球能源互联网研究院有限公司 Power grid equipment element energy information modeling and simulation analysis method
CN114038283A (en) * 2021-11-19 2022-02-11 广东电网有限责任公司 Flexible direct current distribution network steady state and transient state off-line simulation and training system
CN114142471A (en) * 2021-11-29 2022-03-04 江苏科技大学 Ship integrated power system reconstruction method considering communication faults
CN114142471B (en) * 2021-11-29 2023-08-18 江苏科技大学 Ship comprehensive power system reconstruction method considering communication faults
CN114239324A (en) * 2022-02-23 2022-03-25 南方电网数字电网研究院有限公司 Micro energy network state transition space modeling method based on hybrid automaton
CN117422427A (en) * 2023-12-19 2024-01-19 广东省建设工程质量安全检测总站有限公司 Online batch analysis method and system for low-strain data
CN117422427B (en) * 2023-12-19 2024-03-15 广东省建设工程质量安全检测总站有限公司 Online batch analysis method and system for low-strain data
CN117807154A (en) * 2024-02-28 2024-04-02 成都菲宇科技有限公司 Time sequence data visualization method, device and medium for display system
CN117807154B (en) * 2024-02-28 2024-04-30 成都菲宇科技有限公司 Time sequence data visualization method, device and medium for display system

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