WO2023155376A1 - 基于源网荷储分布式能源配网方法、装置、设备及介质 - Google Patents

基于源网荷储分布式能源配网方法、装置、设备及介质 Download PDF

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WO2023155376A1
WO2023155376A1 PCT/CN2022/106597 CN2022106597W WO2023155376A1 WO 2023155376 A1 WO2023155376 A1 WO 2023155376A1 CN 2022106597 W CN2022106597 W CN 2022106597W WO 2023155376 A1 WO2023155376 A1 WO 2023155376A1
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distribution network
load
distributed
model
source
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PCT/CN2022/106597
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French (fr)
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张聪
宋丹阳
庞海天
樊小毅
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深圳江行联加智能科技有限公司
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06315—Needs-based resource requirements planning or analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B10/00—Integration of renewable energy sources in buildings
    • Y02B10/10—Photovoltaic [PV]

Definitions

  • the present application relates to the field of source-network-load-storage coordinated distribution network, and in particular to a method, device, equipment and medium for a distributed energy distribution network based on source-network-load-storage.
  • DG Distributed Generators
  • the main purpose of this application is to provide a distributed energy distribution method based on source-grid-load-storage, which aims to solve the technical problems that affect the economy and safety of system operation after distributed power is connected to the grid system.
  • this application provides a distributed energy distribution network based on source network, load and storage.
  • the distributed energy distribution method based on source network, load and storage includes the following steps:
  • a distribution network mode under the minimum distribution network cost is generated to distribute the target distribution network system connected to distributed energy resources.
  • the present application also provides a distributed energy distribution network device based on source network, load and storage.
  • the distributed energy distribution device based on source network, load and storage is applied to the distribution network system.
  • Load-storage distributed energy distribution network devices include:
  • a construction module configured to receive line information of the target distribution network system, and construct a distributed distribution network model according to the line information
  • a loading module configured to receive load information and power supply information connected to the target distribution network system, construct a load model according to the load information, construct a power supply model according to the power supply information, and combine the load model and The power supply model is loaded into the distributed distribution network model;
  • the output module is used to generate the distribution network mode under the minimum distribution network cost according to the minimum distribution network cost of the distributed distribution network model, so as to distribute the target distribution network system connected to the distributed energy source. net.
  • the present application also provides a distributed energy distribution network equipment based on source network load storage.
  • the distributed energy distribution network equipment based on source network load storage includes: a memory, a processor, and a A source-network-load-storage distributed energy distribution network program that can run on the processor.
  • the source-network-load-storage distributed energy distribution program is executed by the processor, the above-mentioned source-network-based The steps of the load-storage distributed energy distribution network method.
  • the present application also provides a readable storage medium, the readable storage medium stores a distributed energy distribution network program based on source network load storage, and the distributed energy distribution network program based on source network load storage
  • the network program is executed by the processor, the steps of the above-mentioned source-network-load-storage distributed energy distribution network method are realized.
  • a distributed energy distribution network method based on source-network-load-storage proposed in the embodiment of this application by obtaining line information, load information and power supply information in the target distribution network system, constructs an equivalent distributed distribution network of the target distribution network system
  • the model takes network loss power as the objective function, uses the distribution network system's power flow equation constraints, distributed power supply constraints, line node voltage constraints, line node current constraints, and distribution network radiation constraints as the constraints of the objective function, and uses artificial intelligence algorithms to solve
  • the distribution network mode with the minimum value of the objective function is the optimal distribution network mode.
  • the target distribution network system is operated with segmental switches and tie switches to maintain the economical and economical operation of the power grid system after accessing distributed power sources. stability.
  • Fig. 1 is a schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the present application
  • Fig. 2 is a schematic flow diagram of the first embodiment of the distributed energy distribution network method based on the source network load storage of the present application;
  • Fig. 3 is a schematic flow diagram of the second embodiment of the distributed energy distribution method based on the source-network-load-storage of the present application;
  • Fig. 4 is a system diagram of the ieee-33 node standard distribution network in the application based on the source network load storage distributed energy distribution network method.
  • the main solution of the embodiment of the present application is: by obtaining the line information, load information and power supply information in the target distribution network system, constructing an equivalent distributed distribution network model of the target distribution network system, taking the network loss power as the objective function, Taking the power flow equation constraints of the distribution network system, distributed power supply constraints, line node voltage constraints, line node current constraints, and distribution network radiation constraints as the constraints of the objective function, the distribution network method that uses artificial intelligence algorithms to solve the minimum value of the objective function is the most Best distribution network mode, according to the best distribution network mode, perform segment switch and tie switch operation on the target distribution network system.
  • DG Distributed Generators
  • This application provides a solution to maintain the economy and stability of the power grid system operation after accessing distributed power sources through distribution network reconfiguration.
  • FIG. 1 is a schematic diagram of a device structure of a hardware operating environment involved in the solution of the embodiment of the present application.
  • the device in this embodiment of the application may be a server, or an electronic terminal device such as a PC that has data reception, data processing, and data output.
  • the device may include: a processor 1001 , such as a CPU, a network interface 1004 , a user interface 1003 , a memory 1005 , and a communication bus 1002 .
  • the communication bus 1002 is used to realize connection and communication between these components.
  • the user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface.
  • the network interface 1004 may include a standard wired interface and a wireless interface (such as a WI-FI interface).
  • the memory 1005 can be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a disk memory.
  • the memory 1005 may also be a storage device independent of the aforementioned processor 1001 .
  • the device may also include a camera, an RF (Radio Frequency, radio frequency) circuit, a sensor, an audio circuit, a WiFi module, and the like.
  • sensors such as light sensors, motion sensors and other sensors.
  • the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the display screen according to the brightness of the ambient light, and the proximity sensor may turn off the display screen and/or backlight.
  • the gravitational acceleration sensor can detect the magnitude of acceleration in various directions (generally three axes), and can detect the magnitude and direction of gravity when it is stationary, and can be used for applications that recognize the posture of mobile terminals (such as horizontal and vertical screen switching, Related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tap), etc.; of course, the mobile terminal can also be equipped with other sensors such as gyroscope, barometer, hygrometer, thermometer, infrared sensor, etc. No longer.
  • FIG. 1 does not constitute a limitation to the device, and may include more or less components than shown in the figure, or combine some components, or arrange different components.
  • the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and a distributed energy distribution network program based on source, network, load, and storage.
  • the network interface 1004 is mainly used to connect the background server and carry out data communication with the background server;
  • the user interface 1003 is mainly used to connect the client (client) and carry out data communication with the client;
  • the processor 1001 can be used to call the source-grid-load-storage distributed energy distribution network program stored in the memory 1005, and perform the following operations:
  • a distribution network mode under the minimum distribution network cost is generated to distribute the target distribution network system connected to distributed energy resources.
  • the processor 1001 can call the source-grid-load-storage based distributed energy distribution network program stored in the memory 1005, and also perform the following operations:
  • the step of generating a distribution network mode under the minimum distribution network cost according to the minimum distribution network cost of the distributed distribution network model, so as to distribute the target distribution network system connected to distributed energy resources include:
  • the distribution network mode of the distributed distribution network model is used as the minimum cost distribution network mode
  • the target distribution network system is distributed according to the minimum cost distribution method.
  • the processor 1001 can call the source-grid-load-storage based distributed energy distribution network program stored in the memory 1005, and also perform the following operations:
  • the step of using the distribution network mode of the distributed distribution network model as the minimum cost distribution network mode includes:
  • the distribution network mode of the distributed distribution network model is used as the minimum cost distribution network mode.
  • the processor 1001 can call the source-grid-load-storage based distributed energy distribution network program stored in the memory 1005, and also perform the following operations:
  • the constraint information includes at least one of power flow equation constraints, distributed power supply constraints, line node voltage constraints, line node current constraints, and distribution network radiation constraints, and receiving the constraint information of the target distribution network system, according to the
  • the step of generating a constraint function from constraint information includes at least one of the following:
  • the distribution network radiation constraint is received, and a distribution network radiation constraint function is generated according to the distribution network radiation constraint.
  • the processor 1001 can call the source-grid-load-storage based distributed energy distribution network program stored in the memory 1005, and also perform the following operations:
  • the equivalent load demand of the corresponding stage is obtained, and after the power output of each stage is unified, the equivalent power output of the corresponding stage is obtained;
  • the equivalent load demand of each stage is taken as the equivalent output result of the corresponding stage of the load model in the distributed distribution network model, and the equivalent power supply output of each stage is taken as the equivalent output result of the power supply model in the distributed distribution network model.
  • the equivalent output results of the corresponding stages in the distributed distribution network model are taken as the equivalent load demand of each stage.
  • the processor 1001 can call the source-grid-load-storage based distributed energy distribution network program stored in the memory 1005, and also perform the following operations:
  • the step of generating a distribution network mode under the minimum distribution network cost according to the minimum distribution network cost of the distributed distribution network model, so as to distribute the target distribution network system connected to distributed energy resources also includes:
  • the distribution network mode under the minimum distribution network cost of each stage is generated
  • the loss reduction income after the distribution network reconstruction of each stage is generated
  • the reconstruction cost after the distribution network reconfiguration in each stage is generated
  • the distribution network mode after the reconstruction is used as the optimal distribution network mode of the target distribution network system
  • the distribution network mode before reconstruction is taken as the optimal network distribution mode of the target distribution network system.
  • the processor 1001 can call the source-grid-load-storage based distributed energy distribution network program stored in the memory 1005, and also perform the following operations:
  • the steps of receiving the line information of the target distribution network system and constructing a distributed distribution network model according to the line information include:
  • the line information of the target distribution network system obtain the electrical components in the target distribution network system and the connection relationship corresponding to the electrical components;
  • the distributed distribution network model of the target distribution network system is constructed.
  • this application is based on the first embodiment of the source-network-load-storage distributed energy distribution network method, and the source-network-load-storage distributed energy distribution network method includes:
  • Step S10 receiving line information of the target distribution network system, and constructing a distributed distribution network model according to the line information;
  • the grid structure of the existing power grid is mainly adjusted through branch switches and tie switches so as to achieve the effect of reducing network loss and improving the economical operation level.
  • the electrical components in the target distribution network system and the connection relationship corresponding to the electrical components are obtained; based on the electrical components and the connection relationship, the target The distributed distribution network model of the distribution network system.
  • the line-related information of the target distribution network system will be used to construct a basic distribution network topology model (that is, an equivalent distributed distribution network model) including electrical components and connection relationships between electrical components.
  • the line information includes each electrical component in the target distribution network system and the connection relationship between each electrical component, and then generates a distribution network topology diagram composed of lines and nodes, where the line indicates that the circuit breaker has the function of opening and closing the circuit
  • the switchgear, the node represents the electrical component
  • the electrical component includes: busbar, generator, synchronous motor, load point and other components.
  • the ieee (Institute of Electrical and Electronics Engineers, Institute of Electrical and Electronics Engineers)-33 node standard distribution network system is used for illustration, as shown in Figure 4, the system has a total of 33 nodes, 32 initial closed branches and 5 contact lines, and the solid line between nodes in Fig. 4 is the initial closed branch, and the dotted line between nodes is the contact line.
  • Step S20 receiving the load information connected to the target distribution network system and the connected power source information, constructing a load model according to the load information, constructing a power source model according to the power source information, and combining the load model with the The power supply model is loaded into the distributed distribution network model;
  • the solution in this embodiment is mainly aimed at the problem that the distributed power supply will affect the system economy and stability after it is connected to the existing power grid. Therefore, the objects of the power supply information are mainly those connected to the target distribution network system.
  • Distributed power generation where distributed power generation can include: renewable energy wind power generation, photovoltaic power generation, etc., as well as fuel cells or small gas turbines using fossil fuels. Compared with large thermal power plants and large hydropower plants, this type of distributed power generation has the characteristics of small capacity, intermittent, randomness or volatility, which cause impact on the operation of the power grid.
  • the above power information includes the total installed capacity of distributed power sources such as photovoltaic or wind power connected to the target distribution network system, the type of distributed power generation equipment, the access point connected to the target distribution network system, and the history of the target distribution network system. Natural condition information such as light and wind speed and the output of distributed power sources under natural conditions.
  • the above load information includes the historical power consumption of the target distribution network system and the characteristics of power consumption, such as the target distribution network system. Changes in ambient temperature cause load changes, or changes in loads caused by people's activities.
  • the above-mentioned construction of the power supply model based on the power supply information is to generate a mathematical model of the output of wind power and photovoltaic power sources according to the distributed power supply equipment model and the total installed capacity, and based on the natural condition information such as the historical illumination and wind speed of the target distribution network system and The output of each distributed power source corresponding to natural conditions uses big data analysis to correct the output mathematical model of each power source above.
  • the load model constructed based on the load information is based on the historical power consumption of the target distribution network system Big data analysis is used to generate a load model, and the above power source model and load model are used to predict the power output and load demand of the target distribution network system.
  • the distributed distribution network model constructed by the target distribution network system is an ieee-33 node model
  • the above power supply model and load model are loaded to the above ieee-33 node standard according to the access points of the power supply and load in the target distribution network system
  • the power supply model and the load model respectively output the power output and load demand predicted by the target distribution network system, so that the operation of the distributed distribution network model is consistent with the target distribution network system.
  • Step S30 according to the minimum distribution network cost of the distributed distribution network model, generate a distribution network mode under the minimum distribution network cost, so as to distribute the target distribution network system connected to distributed energy resources.
  • an objective function is constructed with the minimum distribution network cost of the distributed distribution network model as the goal; when the function value of the objective function is the minimum value, the distribution network mode of the distributed distribution network model is used as The minimum cost network distribution method: the target distribution network system is distributed according to the minimum cost distribution network method.
  • the above-mentioned aiming at the minimum distribution network cost of the distributed distribution network model is specifically based on the output predicted by the power supply model.
  • the above objective function is the network loss function, and the specific network loss function formula is:
  • P loss is the active power loss of the distribution network system
  • t is the branch label
  • P t is the active power injected by the network to the head-end node of the t-branch
  • Q t is the reactive power injected by the network to the head-end node of the t-branch
  • U t is the voltage amplitude of the node at the head end of branch t
  • R t is the resistance of branch t
  • N is the number of branches of the distributed distribution network model (if it is the standard distribution network with ieee-33 nodes above system, then N is 32).
  • the step of using the distribution network mode of the distributed distribution network model when the objective function is at a minimum value as the minimum cost distribution network mode includes receiving the constraint information of the target distribution network system, and generating a constraint function according to the constraint information ;
  • the distribution network mode of the distributed distribution network model as the minimum cost distribution network mode.
  • the constraint information includes at least one of power flow equation constraints, distributed power supply constraints, line node voltage constraints, line node current constraints, and distribution network radiation constraints; and generating a constraint function according to the constraint information includes at least receiving the power flow equation constraints, and generate a power flow equation constraint function according to the power flow equation constraints; and/or, receive the distributed power supply constraints, and generate a distributed power supply constraint function according to the distributed power supply constraints; and/or, receive the line node voltage constraints, and generate a line node voltage constraint function according to the line node voltage constraints; and/or receive the line node current constraints, and generate a line node current constraint function according to the line node current constraints; and/or , receiving the distribution network radiation constraint, and generating a distribution network radiation constraint function according to the distribution network radiation constraint.
  • t is the branch label; P t is the active power injected by the network to the head-end node of the t-branch; PDGt is the active power injected by the distributed power supply DG to the head-end node of the t-branch; Q DGt is the distributed The reactive power injected by the power source DG to the head node of the t branch; P Lt is the active load power of the head node of the t branch; Q Lt is the reactive load power of the head node of the t branch; U t1 is the head node of the t branch terminal node voltage amplitude; U t2 is the terminal node voltage amplitude of branch t; G t is the conductance between two nodes of branch t; B t is the susceptance between two nodes of branch t ; Phase angle difference between nodes.
  • P DGtmin and P DGtmax are the lower limit and upper limit of the capacity of the distributed power generation DG respectively;
  • PDGt is the active power injected by the distributed power generation DG to the head-end node of the t branch;
  • U tnmin and U tnmax are respectively the n of the t branch
  • U tn is the voltage amplitude of node n of the t branch;
  • g i is the i-th network topology structure after reconstruction
  • G is the network set that satisfies the radial topology structure.
  • an artificial intelligence algorithm is used to solve the distribution network operation model with the minimum network loss, wherein the artificial intelligence algorithm may include: artificial neural network algorithm, simulated annealing algorithm, tabu search algorithm, ant colony algorithm, particle swarm optimization Algorithm, genetic algorithm, differential evolution algorithm, etc., to solve the network topology corresponding to the minimum value of the above objective function is the optimal distribution network operation mode of the target network.
  • the equivalent distributed distribution network model of the target distribution network system is constructed by obtaining the line information, load information and power supply information in the target distribution network system, and the network loss power is used as the objective function , taking the distribution network system's power flow equation constraints, distributed power supply constraints, line node voltage constraints, line node current constraints, and distribution network radiation constraints as the constraints of the objective function, the distribution network method that uses the artificial intelligence algorithm to solve the minimum value of the objective function is The optimal distribution network mode, the target distribution network system is operated according to the optimal distribution network mode for segment switches and contact switches, and the economy and stability of the power grid system operation after accessing the distributed power supply are maintained.
  • this application is based on the second embodiment of the source-network-load-storage distributed energy distribution network method, and the source-network-load-storage distributed energy distribution network method includes:
  • Step S100 receiving line information of the target distribution network system, and constructing a distributed distribution network model according to the line information;
  • the electrical components in the target distribution network system and the connection relationship corresponding to the electrical components are obtained; based on the electrical components and the connection relationship, the target distribution network is constructed The distributed distribution network model of the system.
  • the electrical components in the target distribution network system and the connection relationship between the electrical components are generated into a distribution network topology diagram composed of lines and nodes, where the lines represent circuit breakers and other switching devices that have the function of opening and breaking circuits, and the nodes represent Electrical components. It can be understood that in this embodiment, the target distribution network system is modeled to facilitate generation of an optimal distribution network mode.
  • Step S210 receiving load information and power supply information connected to the target distribution network system, constructing a load model according to the load information, and constructing a power supply model according to the power supply information;
  • the above-mentioned load model and power supply model can predict the load of the target distribution network and the output of distributed power sources based on the prediction results of the meteorological system for natural conditions such as future sunlight and wind speed, and generate time-based Variable load and power output maps, such as predicting the trend of wind power and photovoltaic power generation connected to the target distribution network system in the next ten days or one month according to seasonal changes, or predicting the future according to the historical load growth rate of the target distribution network Ten-day or one-month load conditions.
  • Step S220 discretize the first output result of the load model and the second output result of the power supply model according to a preset division rule; generate load demands of multiple stages according to the discretized first output result, According to the second output result after discretization, multiple stages of power output are generated; the load demand of each stage is unified to obtain the equivalent load demand of the corresponding stage, and the power output of each stage is unified to obtain the corresponding Stage power output;
  • the load model or power model it has large seasonal variability. For example, the sunshine time in winter is shorter than that in summer, so the output phase of the photovoltaic power generation part in the power model will decrease in winter; while in the load model, it is usually divided into Industrial load and residential load, seasonal changes have less impact on industrial load, while residential load accounts for a small proportion of the total load in the load model, and there are heating and cooling electricity demands in winter and summer respectively, so the load in winter and summer
  • the load change predicted by the model is small, so the change of the distributed power supply and the load model is not coordinated, which will cause an impact on the operation of the power grid.
  • the first output result of the load model (that is, the prediction result) and the second output result of the power model are discretized according to the preset division rules, that is, the load and power supply conditions of the target distribution network system are considered in stages, and each The network frame structure of the stage is adjusted.
  • the preset division rules can divide the load and power output according to different seasons. Similarly, it can also be divided by month, fifteen days or by day. In addition, it can also be divided by the degree of change, such as predicting load demand or When the power output change is greater than the preset threshold, it is used as a division point of a stage. When the change is greater than the preset threshold again, it is used as a division point of a stage again.
  • the division logic can be selected according to the actual situation, and the power output and load of each stage are unified.
  • the load model and the power output of the load demand predicted by the power model in the next year are divided into four stages by quarter.
  • the model and the prediction results of the load model calculate the average load and average power output of each stage, and take the average load and average power output of each stage as the unified result of the load demand and power output of the corresponding stage (that is, the equivalent output result).
  • the load and power output are changing all the time. It is obviously unrealistic to adapt the distribution network mode to follow the load and power output all the time. High-frequency distribution network reconfiguration will Therefore, in this embodiment, the load demand and power output are staged according to their changes, and the time span of each stage can be different, and the staged actually determines the frequency of distribution network reconfiguration, and After staged load demand and power output, it is easier to weigh the benefits and costs of distribution network reconstruction.
  • Step S230 using the equivalent load demand of each stage as the equivalent output result of the load model in the corresponding stage of the distributed distribution network model, and using the equivalent power supply output of each stage as the power supply The equivalent output result of the model in the corresponding stage of the distributed distribution network model;
  • the one-year forecast results of the load model and the power supply model will be divided into four stages based on quarters.
  • the first stage will include the load demand and power output forecasted by the load model and the power supply model for three months, and the three-month
  • the average load demand and average power supply output of the first stage are respectively the equivalent output results of the load model and power supply model to the distributed distribution network model.
  • the average load demand and the average power output in the first stage are output to the distributed distribution network model. load demand output.
  • each distributed power source and load output to the node with the unified power output and load demand of each stage are distributed.
  • Step S310 according to the minimum distribution network cost of the distributed distribution network model in each stage, generate the distribution network mode under the minimum distribution network cost in each stage;
  • the calculation of the minimum distribution network cost when the distributed distribution network model is under load demand and power output in each stage is carried out, and the network loss function of each stage is also constructed Calculate the minimum value of the network loss function based on its constraint function, and the network distribution mode when the network loss function is the minimum value is the distribution network mode corresponding to the minimum network loss in each quarter.
  • Step S320 according to the distribution network mode under the minimum distribution network cost in each stage, generate the loss reduction income after the distribution network reconstruction in each stage;
  • the minimum network loss of each stage is generated respectively, which is the corresponding distribution network mode.
  • P loss is the network loss function (objective function)
  • the distribution network mode when P loss is the minimum value is It is the distribution network mode with the minimum network loss in the current stage.
  • the minimum network loss in each stage is set as Ploss1, Ploss2, Ploss3, and Ploss4.
  • the unit is MW.
  • the unified load demand and power output of each stage are respectively the first load demand and the first power output , the second load demand and the second power output, the third load demand and the third power output, the fourth load demand and the fourth power output, then the method of calculating the loss reduction income after the second stage distribution network reconstruction is:
  • the product of the duration of the second stage and Ploss2 is the network loss after the reconstruction of the second stage, and the distributed distribution network model under the condition of the second load demand and the second power output is calculated in the first stage of the minimum network loss distribution network operation. Then multiply the network loss power at the second stage by the duration of the second stage to obtain the unreconfigured network loss, and subtract the reconfigured network loss from the unreconfigured network loss to obtain the loss reduction benefit after the second stage distribution network reconfiguration.
  • the loss reduction benefits of the first, third and fourth stages can be calculated and will not be described here. It can be understood that, in the actual application process, when the prediction results of the load model and the power supply model are divided into stages, it is usually not necessary to divide each stage at one time. For example, if it is currently in the first stage, it is only necessary to The second stage is divided and the load demand and power supply output of the second stage are predicted and unified. It is understandable that the above load model and power supply need to be predicted based on the predicted natural conditions. When the time span is too long, the predicted natural The lower conditional accuracy also reduces the prediction accuracy of the load model and the source model.
  • Step S330 according to the distribution network mode before and after the distribution network reconfiguration at each stage, the reconstruction cost after the distribution network reconfiguration at each stage is generated;
  • the operation cost that is, the reconfiguration cost
  • the calculation formula of reconstruction cost is:
  • S loss is the cost of reconstruction operation
  • C t is the cost coefficient of a single switching operation of branch t
  • ⁇ t1 is the state of branch t before reconstruction
  • ⁇ t2 is the state of branch t after reconstruction.
  • the C t is generally an empirical formula and the value ranges of ⁇ t1 and ⁇ t2 are 0 and 1, where 0 and 1 are the open state and the closed state, respectively. Whether the branch is in operation can be judged by the status before and after the same branch. If the operation is performed, the value is 1 and multiplied by the single operation cost coefficient to obtain the cost of one operation. Add all operation costs to obtain the total operation cost.
  • Step S400 judging the optimal distribution mode of the target distribution network system according to the loss reduction benefit and the reconstruction cost.
  • the loss reduction benefit is greater than the reconstruction cost: if the loss reduction benefit is greater than the reconstruction cost, the reconfigured distribution network mode is used as the optimal distribution network of the target grid system mode; if the loss reduction benefit is less than or equal to the reconstruction cost, the distribution network mode before reconstruction is taken as the optimal network distribution mode of the target grid system.
  • judging the optimal distribution mode of the target distribution network system is the distribution mode with the maximum benefit after comprehensive loss reduction benefit and reconstruction cost.
  • the reconstructed distribution network mode is regarded as the best operation mode. If the loss reduction benefit brought by the reconstruction is less than or equal to the reconstruction cost, the current distribution network mode will be kept running as the optimal distribution network mode.
  • the load demand and power output predicted by the load model and power model are processed in stages, Then build a distribution network operation model that is suitable for each stage, and at the same time, add the operating cost factors generated during the distribution network reconfiguration between different stages to the judgment process of the optimal distribution network mode, so as to avoid operating problems caused by reconfiguration. Too many reconfiguration operation costs are greater than the benefits of reducing network losses, which makes the total distribution network reconfiguration cost increase and reduces the operating economy of the target distribution network system.
  • this embodiment also provides a source-network-load-storage distributed energy distribution network device.
  • the source-network-load-storage distributed energy distribution network device is applied to the distribution network system.
  • Energy distribution network devices include:
  • a construction module configured to receive line information of the target distribution network system, and construct a distributed distribution network model according to the line information
  • a loading module configured to receive load information and power supply information connected to the target distribution network system, construct a load model according to the load information, construct a power supply model according to the power supply information, and combine the load model and The power supply model is loaded into the distributed distribution network model;
  • the output module is used to generate the distribution network mode under the minimum distribution network cost according to the minimum distribution network cost of the distributed distribution network model, so as to distribute the target distribution network system connected to the distributed energy source. net.
  • the output module is also used for:
  • the distribution network mode of the distributed distribution network model is used as the minimum cost distribution network mode
  • the target distribution network system is distributed according to the minimum cost distribution method.
  • the output module is also used for:
  • the distribution network mode of the distributed distribution network model is used as the minimum cost distribution network mode.
  • the constraint information includes at least one of power flow equation constraints, distributed power supply constraints, line node voltage constraints, line node current constraints, and distribution network radiation constraints, and the output module is also used for:
  • the distribution network radiation constraint is received, and a distribution network radiation constraint function is generated according to the distribution network radiation constraint.
  • the output module is also used for:
  • the equivalent load demand of the corresponding stage is obtained, and after the power output of each stage is unified, the equivalent power output of the corresponding stage is obtained;
  • the equivalent load demand of each stage is taken as the equivalent output result of the corresponding stage of the load model in the distributed distribution network model, and the equivalent power supply output of each stage is taken as the equivalent output result of the power supply model in the distributed distribution network model.
  • the equivalent output results of the corresponding stages in the distributed distribution network model are taken as the equivalent load demand of each stage.
  • the output module is also used for:
  • the distribution network mode under the minimum distribution network cost of each stage is generated
  • the loss reduction income after the distribution network reconstruction of each stage is generated
  • the reconstruction cost after the distribution network reconfiguration in each stage is generated
  • the distribution network mode after the reconstruction is used as the optimal distribution network mode of the target distribution network system
  • the distribution network mode before reconstruction is taken as the optimal network distribution mode of the target distribution network system.
  • building blocks are also used for:
  • the line information of the target distribution network system obtain the electrical components in the target distribution network system and the connection relationship corresponding to the electrical components;
  • the distributed distribution network model of the target distribution network system is constructed.
  • the source-network-load-storage distributed energy distribution network device provided by this application adopts the source-network-load-storage distributed energy distribution network method in the above-mentioned embodiments to solve the problem of system operation economy and economical problems after the distributed power supply is connected to the grid system.
  • Technical issues of security Compared with the prior art, the beneficial effect of the source-network-load-storage distributed energy distribution network device provided by the embodiment of the present application is the same as the beneficial effect of the source-network-load-storage distributed energy distribution network method provided by the above embodiment, and Other technical features of the source-grid-load-storage distributed energy distribution network device are the same as those disclosed in the methods of the above-mentioned embodiments, and will not be repeated here.
  • this embodiment also provides a source-grid-load-storage distributed energy distribution network device based on the source-network load-storage distributed energy distribution network device, which includes: a memory, a processor, and a memory stored in the memory and can be The source-network-load-storage distributed energy distribution network program running on the processor, when the source-network-load-storage distributed energy distribution network program is executed by the processor, realizes the above-mentioned source-network-load-storage distributed energy distribution program. Steps of energy distribution grid method.
  • the specific implementation of the source-network-load-storage distributed energy distribution network equipment in this application is basically the same as the above-mentioned embodiments of the source-network-load-storage distributed energy distribution network method, and will not be repeated here.
  • this embodiment also provides a readable storage medium, on which is stored a distributed energy distribution network program based on source network, load and storage, and the distributed energy distribution program based on source network, load and storage is processed When the controller is executed, the steps of the above-mentioned source-grid-load-storage distributed energy distribution network method are realized.
  • the term “comprises”, “comprises” or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article or system comprising a set of elements includes not only those elements, It also includes other elements not expressly listed, or elements inherent in the process, method, article, or system. Without further limitations, an element defined by the phrase “comprising a " does not preclude the presence of additional identical elements in the process, method, article or system comprising that element.
  • the methods of the above embodiments can be implemented by means of software plus a necessary general-purpose hardware platform, and of course also by hardware, but in many cases the former is better implementation.
  • the technical solution of the present application can be embodied in the form of a software product in essence or in other words, the part that contributes to the prior art, and the computer software product is stored in a storage medium (such as ROM/RAM) , magnetic disk, optical disk), including several instructions to enable a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present application.

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Abstract

本申请公开了一种基于源网荷储分布式能源配网方法、装置、设备及介质，所述基于源网荷储分布式能源配网方法包括：通过获取目标配网系统中的线路信息、负荷信息和电源信息，构建目标配网系统的等效分布式配电网模型，以网损功率为目标函数，以配网系统的潮流方程约束、分布式电源约束、线路节点电压约束、线路节点电流约束和配网辐射约束作为目标函数的约束条件，使用人工智能算法求解目标函数最小值的配网方式即最佳配网方式，按最佳配网方式对目标配网系统进行分段开关和联络开关的操作，保持接入分布式电源后电网系统运行的经济性和稳定性。

Description

基于源网荷储分布式能源配网方法、装置、设备及介质
优先权信息
本申请要求于2022年2月21日申请的、申请号为202210154996.6的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及源网荷储协同配电网领域，尤其涉及一种基于源网荷储分布式能源配网方法、装置、设备及介质。
背景技术
近年来，随着我国国民经济的迅猛发展，电力负荷逐年增加，配电网络的结构也日趋复杂，造成配电网网络损耗逐年增大。随着国民经济持续、健康的发展和人民物资文化生活水平的不断提高，对电能的需求势头见涨。可是，近几年全国各种能源的发电量远不能满足人们的需求，全国各地相继出现了拉闸限电的现象，供需矛盾日益加剧，严重影响了经济发展和人民生活。
此外，为响应国家碳达峰和碳中和的目标，新能源技术发展迅猛，以可再生能源为主的分布式电源对配电网系统带来挑战，如以风力发电和光伏发电为典型的DG(Distributed Generators，DG)往往具有间歇性、随机性、波动性等特点，从而给传统配电网的调度运行带来困难，引起不必要的运行经济损失和运行安全。
上述内容仅用于辅助理解本申请的技术方案，并不代表承认上述内容是现有技术。
发明内容
本申请的主要目的在于提供一种基于源网荷储分布式能源配网方法，旨在解决分布式电源接入电网系统后影响系统运行经济性和安全性的技术问题。
为实现上述目的，本申请提供一种基于源网荷储分布式能源配网方，所述基于源网荷储分布式能源配网方法包括以下步骤：
接收目标配电网系统的线路信息，根据所述线路信息构建分布式配电网模型；
接收所述目标配电网系统接入的负荷信息和接入的电源信息，根据所述负荷信息构建负荷模型，根据所述电源信息构建电源模型，并将所述负荷模 型和所述电源模型加载至所述分布式配电网模型；
依据所述分布式配电网模型的最小配网代价，生成所述最小配网代价下的配网方式，以对接入分布式能源的所述目标配电网系统进行配网。
此外，为实现上述目的，本申请还提供一种基于源网荷储分布式能源配网装置，所述基于源网荷储分布式能源配网装置应用于配电网系统，所述基于源网荷储分布式能源配网装置包括：
构建模块，用于接收目标配电网系统的线路信息，根据所述线路信息构建分布式配电网模型；
加载模块，用于接收所述目标配电网系统接入的负荷信息和接入的电源信息，根据所述负荷信息构建负荷模型，根据所述电源信息构建电源模型，并将所述负荷模型和所述电源模型加载至所述分布式配电网模型；
输出模块，用于依据所述分布式配电网模型的最小配网代价，生成所述最小配网代价下的配网方式，以对接入分布式能源的所述目标配电网系统进行配网。
此外，为实现上述目的，本申请还提供一种基于源网荷储分布式能源配网设备，所述基于源网荷储分布式能源配网设备包括：存储器、处理器及存储在所述存储器上并可在所述处理器上运行的基于源网荷储分布式能源配网程序，所述基于源网荷储分布式能源配网程序被所述处理器执行时实现如上述的基于源网荷储分布式能源配网方法的步骤。
此外，为实现上述目的，本申请还提供一种可读存储介质，所述可读存储介质上存储有基于源网荷储分布式能源配网程序，所述基于源网荷储分布式能源配网程序被处理器执行时实现如上述的基于源网荷储分布式能源配网方法的步骤。
本申请实施例提出的一种基于源网荷储分布式能源配网方法，通过获取目标配网系统中的线路信息、负荷信息和电源信息，构建目标配网系统的等效分布式配电网模型，以网损功率为目标函数，以配网系统的潮流方程约束、分布式电源约束、线路节点电压约束、线路节点电流约束和配网辐射约束作为目标函数的约束条件，使用人工智能算法求解目标函数最小值的配网方式即最佳配网方式，按最佳配网方式对目标配网系统进行分段开关和联络开关的操作，保持接入分布式电源后电网系统运行的经济性和稳定性。
附图说明
图1是本申请实施例方案涉及的硬件运行环境的设备结构示意图；
图2为本申请基于源网荷储分布式能源配网方法第一实施例的流程示意图；
图3为本申请基于源网荷储分布式能源配网方法第二实施例的流程示意图；
图4为本申请基于源网荷储分布式能源配网方法中ieee-33节点标准配电网系统图。
本申请目的的实现、功能特点及优点将结合实施例，参照附图做进一步说明。
具体实施方式
应当理解，此处所描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
本申请实施例的主要解决方案是：通过获取目标配网系统中的线路信息、负荷信息和电源信息，构建目标配网系统的等效分布式配电网模型，以网损功率为目标函数，以配网系统的潮流方程约束、分布式电源约束、线路节点电压约束、线路节点电流约束和配网辐射约束作为目标函数的约束条件，使用人工智能算法求解目标函数最小值的配网方式即最佳配网方式，按最佳配网方式对目标配网系统进行分段开关和联络开关的操作。
由于目前为响应国家碳达峰和碳中和的目标，新能源技术发展迅猛，以可再生能源为主的分布式电源对配电网系统带来挑战，如以风力发电和光伏发电为典型的DG(Distributed Generators，DG)往往具有间歇性、随机性、波动性等特点，从而给传统配电网的调度运行带来困难，引起不必要的运行经济损失和运行安全。
本申请提供一种解决方案，通过配网重构保持接入分布式电源后电网系统运行的经济性和稳定性。
如图1所示，图1是本申请实施例方案涉及的硬件运行环境的设备结构示意图。
本申请实施例设备可以是服务器，也可以是PC等具有数据接收、数据处理和数据输出的电子终端设备。
如图1所示，该设备可以包括：处理器1001，例如CPU，网络接口1004， 用户接口1003，存储器1005，通信总线1002。其中，通信总线1002用于实现这些组件之间的连接通信。用户接口1003可以包括显示屏(Display)、输入单元比如键盘(Keyboard)，可选用户接口1003还可以包括标准的有线接口、无线接口。网络接口1004可选的可以包括标准的有线接口、无线接口(如WI-FI接口)。存储器1005可以是高速RAM存储器，也可以是稳定的存储器(non-volatile memory)，例如磁盘存储器。存储器1005可选的还可以是独立于前述处理器1001的存储装置。
可选地，设备还可以包括摄像头、RF(Radio Frequency，射频)电路，传感器、音频电路、WiFi模块等等。其中，传感器比如光传感器、运动传感器以及其他传感器。具体地，光传感器可包括环境光传感器及接近传感器，其中，环境光传感器可根据环境光线的明暗来调节显示屏的亮度，接近传感器可在移动终端移动到耳边时，关闭显示屏和/或背光。作为运动传感器的一种，重力加速度传感器可检测各个方向上(一般为三轴)加速度的大小，静止时可检测出重力的大小及方向，可用于识别移动终端姿态的应用(比如横竖屏切换、相关游戏、磁力计姿态校准)、振动识别相关功能(比如计步器、敲击)等；当然，移动终端还可配置陀螺仪、气压计、湿度计、温度计、红外线传感器等其他传感器，在此不再赘述。
本领域技术人员可以理解，图1中示出的设备结构并不构成对设备的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。
如图1所示，作为一种计算机存储介质的存储器1005中可以包括操作系统、网络通信模块、用户接口模块以及基于源网荷储分布式能源配网程序。
在图1所示的设备中，网络接口1004主要用于连接后台服务器，与后台服务器进行数据通信；用户接口1003主要用于连接客户端(用户端)，与客户端进行数据通信；而处理器1001可以用于调用存储器1005中存储的基于源网荷储分布式能源配网程序，并执行以下操作：
接收目标配电网系统的线路信息，根据所述线路信息构建分布式配电网模型；
接收所述目标配电网系统接入的负荷信息和接入的电源信息，根据所述负荷信息构建负荷模型，根据所述电源信息构建电源模型，并将所述负荷模 型和所述电源模型加载至所述分布式配电网模型；
依据所述分布式配电网模型的最小配网代价，生成所述最小配网代价下的配网方式，以对接入分布式能源的所述目标配电网系统进行配网。
进一步地，处理器1001可以调用存储器1005中存储的基于源网荷储分布式能源配网程序，还执行以下操作：
所述依据所述分布式配电网模型的最小配网代价，生成所述最小配网代价下的配网方式，以对接入分布式能源的所述目标配电网系统进行配网的步骤包括：
以所述分布式配电网模型的最小配网代价为目标构建目标函数；
当所述目标函数的函数值为最小值时，将所述分布式配电网模型的配网方式作为最小代价配网方式；
将所述目标配电网系统按所述最小代价配网方式进行配网。
进一步地，处理器1001可以调用存储器1005中存储的基于源网荷储分布式能源配网程序，还执行以下操作：
所述当所述目标函数的函数值为最小值时，将所述分布式配电网模型的配网方式作为最小代价配网方式的步骤包括：
接收所述目标配电网系统的约束信息，根据所述约束信息生成约束函数；
当所述目标函数在所述约束函数约束下处于最小值时，将所述分布式配电网模型的配网方式作为所述最小代价配网方式。
进一步地，处理器1001可以调用存储器1005中存储的基于源网荷储分布式能源配网程序，还执行以下操作：
所述约束信息至少包括潮流方程约束、分布式电源约束、线路节点电压约束、线路节点电流约束和配网辐射约束中一种，所述接收所述目标配电网系统的约束信息，根据所述约束信息生成约束函数的步骤至少包括以下一种：
接收所述潮流方程约束，并根据所述潮流方程约束生成潮流方程约束函数；和/或
接收所述分布式电源约束，并根据所述分布式电源约束生成分布式电源约束函数；和/或
接收所述线路节点电压约束，并根据所述线路节点电压约束生成线路节点电压约束函数；和/或
接收所述线路节点电流约束，并根据所述线路节点电流约束生成线路节点电流约束函数；和/或
接收所述配网辐射约束，并根据所述配网辐射约束生成配网辐射约束函数。
进一步地，处理器1001可以调用存储器1005中存储的基于源网荷储分布式能源配网程序，还执行以下操作：
在所述将所述负荷模型和所述电源模型加载至所述分布式配电网模型的步骤之后，包括：
根据预设划分规则将所述负荷模型的第一输出结果和所述电源模型的第二输出结果离散化；
根据离散化后的所述第一输出结果生成多个阶段的负荷需求，根据离散化后的所述第二输出结果生成多个阶段的电源出力；
将各阶段的所述负荷需求经统一化后得到对应阶段的等效负荷需求，将各阶段的所述电源出力经统一化后得到对应阶段的等效电源出力；
将各阶段的所述等效负荷需求作为所述负荷模型在所述分布式配电网模型中对应阶段的等效输出结果，将各阶段的所述等效电源出力作为所述电源模型在所述分布式配电网模型中对应阶段的等效输出结果。
进一步地，处理器1001可以调用存储器1005中存储的基于源网荷储分布式能源配网程序，还执行以下操作：
所述依据所述分布式配电网模型的最小配网代价，生成所述最小配网代价下的配网方式，以对接入分布式能源的所述目标配电网系统进行配网的步骤还包括：
依据各阶段下的分布式配电网模型的最小配网代价，生成各阶段最小配网代价下的配网方式；
根据所述各阶段最小配网代价下的配网方式，生成各阶段配网重构后的降损收益；
根据各阶段配网重构前后的配网方式，生成各阶段配网重构后的重构代价；
判断所述降损收益是否大于所述重构代价：
若所述降损收益大于所述重构代价，则将重构后的配网方式作为所述目 标配电网系统的最佳配网方式；
若所述降损收益小于或者等于所述重构代价，则将重构前的配网方式作为所述目标配电网系统的最佳配网方式。
进一步地，处理器1001可以调用存储器1005中存储的基于源网荷储分布式能源配网程序，还执行以下操作：
所述接收目标配电网系统的线路信息，根据所述线路信息构建分布式配电网模型的步骤包括：
根据所述目标配电网系统的线路信息，获取所述目标配电网系统中的电气元件以及所述电气元件对应的连接关系；
基于所述电气元件和所述连接关系，构建目标配电网系统的所述分布式配电网模型。
参照图2，本申请基于源网荷储分布式能源配网方法中的第一实施例，所述基于源网荷储分布式能源配网方法包括：
步骤S10，接收目标配电网系统的线路信息，根据所述线路信息构建分布式配电网模型；
可以理解的是，在本实施例主要是通过支路开关和联络开关对现有电网的网架结构进行调整从而达到降低网损、提高经济运行水平的效果。
进一步的，根据所述目标配电网系统的线路信息，获取所述目标配电网系统中的电气元件以及所述电气元件对应的连接关系；基于所述电气元件和所述连接关系，构建目标配电网系统的所述分布式配电网模型。
具体的，目标配电网系统的线路相关信息将用于构建包括电气元件以及连接电气元件之间连接关系的基本配网拓扑模型(即等效分布式配电网模型)，首先接收线路信息，线路信息包括目标配电网系统中的各电气元件以及各电气元件之间的连接关系，并以此生成由线和节点组成的配电网拓扑图，其中线表示断路器等具有开断路的功能的开关设备，节点表示电气元件，所述电气元件包括：母线、发电机、同步电动机、负荷点等元件。将上述获取到的电气元件按目标配电网系统的连接关系组合生成分布式配电网模型。为清楚的说明所述分布式配电网模型，以ieee(Institute of Electrical and Electronics Engineers，电气和电子工程师协会)-33节点标准配电网系统进行说明，如图4所示，该系统共有33个节点、32条初始闭合支路以及5条联络线，且图4 中节点与节点之间的实线为初始闭合支路，节点与节点之间的虚线为联络线。
步骤S20，接收所述目标配电网系统接入的负荷信息和接入的电源信息，根据所述负荷信息构建负荷模型，根据所述电源信息构建电源模型，并将所述负荷模型和所述电源模型加载至所述分布式配电网模型；
可以理解的是，本实施例方案主要是针对分布式电源接入现有电网后对系统经济性和稳定性造成影响的问题，因此所述电源信息的对象主要为接入目标配电网系统的分布式电源，其中分布式电源可以包括：可再生能源的风力发电、光伏发电等，同时也包括使用化石燃料的燃料电池或者小型燃气轮机等。相比大型火电厂的和大型水电厂该类分布式电源具有容量小、间歇性、随机性或者波动性等特点造成对电网运行冲击。其中，上述电源信息包括目标配电网系统接入的光伏或者风电等分布式电源的装机总量、分布式电源设备型号、接入目标配电网系统的接入点、目标配电网系统历史光照和风速等自然条件信息以及自然条件对应下各分布式电源的出力情况，上述负荷信息包括目标配电网系统历史用电量的情况，以及用电量的特点，如目标配电网系统的环境温度变化引起负荷变换，或者，人们活动规律引起负荷发生变化等。此外，上述根据所述电源信息构建电源模型为，根据分布式电源设备型号以及装机总量生成风电和光伏等电源的出力数学模型，并基于目标配电网系统历史光照和风速等自然条件信息以及自然条件对应下各分布式电源的出力情况运用大数据分析对上述各电源的出力数学模型进行修正，同理，根据所述负荷信息构建负荷模型为基于目标配电网系统历史用电量的情况使用大数据分析生成负荷模型，上述电源模型和负荷模型用于对目标配电网系统的电源输出和负荷需求的预测。可理解的是目前存在较为成熟的建模和大数据分析技术，尤其是对风力发电和光伏发电等基于自然环境变化进行发电的电源，生成的电源出力预测模型较为准确，而使用化石燃料的燃料电池或者小型燃气轮机其稳定性相比于光伏和风电较好，其有功出力可人为控制，因此上述电源模型和负荷模型的生成过程在此处不再赘述。如目标配电网系统构建的分布式配电网模型为ieee-33节点模型，将上述电源模型和负荷模型按目标配电网系统中电源和负荷的接入点加载至上述ieee-33节点标准配电网系统中，电源模型和负荷模型分别输出对目标配电网系统预测的电源出力和负荷需求，使得分布式配电网模型运行情况与目标配电网系统保持一致。
步骤S30，依据所述分布式配电网模型的最小配网代价，生成所述最小配网代价下的配网方式，以对接入分布式能源的所述目标配电网系统进行配网。
进一步的，以所述分布式配电网模型的最小配网代价为目标构建目标函数；当所述目标函数的函数值为最小值时，将所述分布式配电网模型的配网方式作为最小代价配网方式；将所述目标配电网系统按所述最小代价配网方式进行配网。
上述以分布式配电网模型最小配网代价为目标具体为基于电源模型预测的出力情况通过对当前分布式配电网模型的网络架构进行重构，使得在满足负荷模型预测的负荷需求条件下电力在线路输送过程中损耗最小，以此损耗最小为目标构建目标函数。
上述目标函数即为网损函数，具体的网损函数公式为：
Figure PCTCN2022106597-appb-000001
其中，P loss为配网系统的有功损耗；t为支路标号；P t为网络向t支路的首端节点注入的有功功率；Q t为网络向t支路的首端节点注入的无功功率；U t为t支路首端节点的电压幅值；R t为t支路的电阻；N为分布式配电网模型的支路数(若为上述ieee-33节点标准配电网系统，则N为32)。
基于图4，若节点3和4之间标号为支路3，电流由节点3流向节点4则P 3为网络向节点3注入的有功功率，同理，Q 3为网络向节点3注入的无功功率，U 3为节点3的电压幅值。将各支路的电力运输损耗相加则为整个系统的线路损耗。
进一步的，将目标函数处于最小值时分布式配电网模型的配网方式作为最小代价配网方式的步骤包括，接收所述目标配电网系统的约束信息，根据所述约束信息生成约束函数；当所述目标函数在所述约束函数约束下处于最小值时，将所述分布式配电网模型的配网方式作为所述最小代价配网方式。其中，所述约束信息至少包括潮流方程约束、分布式电源约束、线路节点电压约束、线路节点电流约束和配网辐射约束中一种；而根据所述约束信息生成约束函数至少包括接收所述潮流方程约束，并根据所述潮流方程约束生成潮流方程约束函数；和/或，接收所述分布式电源约束，并根据所述分布式电源约束生成分布式电源约束函数；和/或，接收所述线路节点电压约束，并根 据所述线路节点电压约束生成线路节点电压约束函数；和/或，接收所述线路节点电流约束，并根据所述线路节点电流约束生成线路节点电流约束函数；和/或，接收所述配网辐射约束，并根据所述配网辐射约束生成配网辐射约束函数。
具体的，上述潮流约束函数为：
Figure PCTCN2022106597-appb-000002
Figure PCTCN2022106597-appb-000003
其中，t为支路标号；P t为网络向t支路的首端节点注入的有功功率；P DGt为分布式电源DG向t支路的首端节点注入的有功功率；Q DGt为分布式电源DG向t支路的首端节点注入的无功功率；P Lt为t支路首端节点有功负荷功率；Q Lt为t支路首端节点无功负荷功率；U t1为t支路首端节点电压幅值；U t2为t支路末端节点电压幅值；G t为支路t两节点间的电导；B t为支路t两节点间的电纳；θ t为支路t两节点间的相角差。
上述分布式电源约束函数、线路节点电压约束函数、线路节点电流约束函分别为：
P DGtmin≤P DPt≤P DGtmax
U tnmin≤U tn≤U tnmax
I t≤I tmax
其中，P DGtmin和P DGtmax分别为分布式电源DG容量的下限和上限；P DGt为分布式电源DG向t支路的首端节点注入的有功功率；U tnmin和U tnmax分别为t支路n节点的电压幅值下限和上限；为U tn为t支路n节点电压幅值；I tmax为t支路的最大电流；I t为t支路电流。
上述配网辐射约束函数为：
g i∈G
其中，g i为重构后的第i个网络拓扑结构，G为满足辐射状拓结构的网络集合。
将上述五个约束函数作为目标函数Ploss的约束条件，对目标函数Ploss求解最小值，求解的最小值即为最小的线路损耗。本实施例中使用人工智能算法对上述最小网损的配网运行模型进行求解，其中所述人工智能算法可以包括：人工神经网络算法，模拟退火算法，禁忌搜索算法，蚁群算法，粒子 群优化算法和遗传算法、差分进化算法等，求解出上述目标函数最小值所对应的网络拓扑结构即为目标网络的最佳配网运行方式。
可以理解的是，在本实施例中，通过获取目标配网系统中的线路信息、负荷信息和电源信息，构建目标配网系统的等效分布式配电网模型，以网损功率为目标函数，以配网系统的潮流方程约束、分布式电源约束、线路节点电压约束、线路节点电流约束和配网辐射约束作为目标函数的约束条件，使用人工智能算法求解目标函数最小值的配网方式即最佳配网方式，对目标配网系统进行按最佳配网方式进行分段开关和联络开关的操作，保持接入分布式电源后电网系统运行的经济性和稳定性。
进一步的，参照图3，本申请基于源网荷储分布式能源配网方法中的第二实施例，所述基于源网荷储分布式能源配网方法包括：
步骤S100，接收目标配电网系统的线路信息，根据所述线路信息构建分布式配电网模型；
据所述目标配电网系统的线路信息，获取所述目标配电网系统中的电气元件以及所述电气元件对应的连接关系；基于所述电气元件和所述连接关系，构建目标配电网系统的所述分布式配电网模型。将目标配电网系统中的各电气元件以及各电气元件之间的连接关系生成由线和节点组成的配电网拓扑图，其中线表示断路器等具有开断路的功能的开关设备，节点表示电气原件。可以理解的是，本实施例中，将目标配电网系统模型化方便生成最佳的配网方式。
步骤S210，接收所述目标配电网系统接入的负荷信息和接入的电源信息，根据所述负荷信息构建负荷模型，根据所述电源信息构建电源模型；
同样的，本实施例中，上述负荷模型和电源模型可基于气象系统对未来光照和风速等自然条件的预测结果，对目标配电网的负荷以及分布式电源的出力情况进行预测，生成以时间为变量的负荷和电源出力图，如根据季节变化预测接入目标配电网系统的风力发电和光伏发电出力在未来十天或者一个月的走势，或者按照目标配电网历史负荷增长率预测未来十天或者一个月负荷情况。
步骤S220，根据预设划分规则将所述负荷模型的第一输出结果和所述电源模型的第二输出结果离散化；根据离散化后的所述第一输出结果生成多个 阶段的负荷需求，根据离散化后的所述第二输出结果生成多个阶段的电源出力；将各阶段的所述负荷需求统一化得到对应阶段的等效负荷需求，将各阶段的所述电源出力统一化得到对应阶段的电源出力；
不管的负荷模型或者电源模型，其具有较大的季节变化性，如冬季日照时间相对夏季较短，因此电源模型中光伏发电部分的出力相在冬季将会降低；而在负荷模型，通常分为工业负荷和居民负荷，季节变化对工业负荷影响较少，而居民负荷在负荷模型的总负荷中占比较少且冬季和夏季分别存在取暖和冷气的用电需求，所以就冬季和夏季而言负荷模型预测出的负荷变化幅度较小，因此，分布式电源和负荷模型的变化并不协调，也就导致其对电网运行造成冲击。对此，将负荷模型的第一输出结果(即预测结果)和电力模型的第二输出结果按预设划分规则离散化，即分阶段考虑目标配电网系统的负荷和电源情况，以对各阶段的网架结构作出调整。其中预设划分规则可按不同季节划分负荷和电源出力情况，同理，也可以按月、十五天或者按天进行划分，此外，还可以按变化程度进行划分，如将预测的负荷需求或者电源出力变化大于预设阈值时作为一个阶段的划分点，当变化再次大于预设阈值时再次作为一个阶段的划分点，通常情况下按负荷需求变化和电源出变化进行划分具有较好效果，具体的划分逻辑可根据实际情况来选择，将每个阶段的电源出力和负荷统一，如将负荷模型和电源模型预测的未来一年的负荷需求的电源出力情况按季度划分成四个阶段，根据电源模型和负荷模型的预测结果计算每个阶段的平均负荷和平均电源出力，将各阶段的平均负荷和平均电源出力作为对应阶段的负荷需求和电源出力统一的结果(即等效输出结果)。
可以理解的是，在实际电网运行过程中，负荷和电源出力时刻都在发生变化，若配网方式时刻跟随负荷和电源出力进行适配显然是不现实的，高频的进行配网重构会增加运行成本，因此，在本实施例中，将负荷需求和电源出力根据其变化情况阶段化，且每个阶段划分的时间跨度可以不同，且阶段化实际上决定配网重构的频率，而且阶段化负荷需求和电源出力后更容易权衡配网重构后的收益以及代价。
步骤S230，将各阶段的所述等效负荷需求作为所述负荷模型在所述分布式配电网模型中对应阶段的等效输出结果，将各阶段的所述等效电源出力作为所述电源模型在所述分布式配电网模型中对应阶段的等效输出结果；
基于上述例子，将依据季度将负荷模型和电源模型预测的一年结果划分成四个阶段，如第一阶段将包括负荷模型和电源模型预测三个月的负荷需求和电源出力，将三个月的平均负荷需求和平均电源出力分别作为第一阶段内负荷模型和电源模型向分布式配电网模型的等效输出结果，在第一阶段内负荷模型和电源模型分别以并保持上述第一阶段平均负荷需求和第一阶段平均电源出力向分布式配电网模型输出，即在第一阶段分布式配电网模型中各分布式电源和负荷向节点分别以第一阶段的平均电源出力和平均负荷需求输出。同理，第二、第三和第四阶段分布式配电网模型中各分布式电源和负荷向节点以各阶段统一化后的电源出力和负荷需求输出。
步骤S310，依据各阶段下的分布式配电网模型的最小配网代价，生成各阶段最小配网代价下的配网方式；
当划分出四个阶段的负荷需求和电源出力时，则进行分布式配电网模型在各阶段下负荷需求和电源出力时的最小配网代价的计算，同样的构建每个阶段的网损函数基于其约束函数计算网损函数的最小值，网损函数为最小值时的配网方式即为对应各个季度最小网损的配网方式。具体的网损函数和约束函数可参照第一实施例。
步骤S320，根据所述各阶段最小配网代价下的配网方式，生成各阶段配网重构后的降损收益；
基于上述例子当划分出四个阶段后，分别生成各个阶段的最小网损即对应的配网方式，如P loss为网损函数(目标函数)，当P loss为最小值时的配网方式即为当前阶段最小网损的配网方式，设各个阶段最小网损为Ploss1、Ploss2、Ploss3、Ploss4单位为MW，各阶段统一后的负荷需求和电源出力分别为第一负荷需求和第一电源出力、第二负荷需求和第二电源出力、第三负荷需求和第三电源出力、第四负荷需求和第四电源出力，则计算第二阶段配网重构后的降损收益的方式为：将第二阶段的时长与Ploss2的乘积得到第二阶段重构后的网损，计算在第二负荷需求和第二电源出力条件下的分布式配网模型处于第一阶段最小网损配网方式运行时的网损功率再与第二阶段时长相乘得到未重构网损，将未重构网损减去重构后的网损即可得到第二阶段配网重构后的降损收益。同样的方式，可以计算第一、第三和第四阶段的降损收益此处不在赘述。可以理解的是，在实际应用过程中，将负荷模型和电源模型的预 测结果阶段化时，通常情况下无需一次性将每个阶段划分完成，如，若当前处于第一阶段，则只需要对第二阶段进行划分以及对第二阶段的负荷需求和电源出力进行预测并统一化，可以理解的，上述负荷模型和电源需基于预测的自然条件进行预测，当时间跨度过大时，预测的自然条件准确性较低，同时也会降低负荷模型和电源模型的预测的准确性。
步骤S330，根据各阶段配网重构前后的配网方式，生成各阶段配网重构后的重构代价；
在电网系统的实际运行过程中，在配网重构过程中由于网络开关的闭合与断开，切换操作的成也是不容忽视的，因此，在本实施例中将加入操作成本即重构代价，以判断目标配网系统在不同阶段的最佳配网方式。其中，重构代价的计算公式为：
Figure PCTCN2022106597-appb-000004
其中，S loss为重构操作成本；C t为t支路单次切换操作成本系数；α t1为t支路重构前的状态；α t2为t支路重构后的状态。所述C t通常为经验公式且所述α t1和α t2的取值范围为0和1，0和1分别为断开状态和闭合状态。通过同一支路的前后状态可判断出该支路是否进行操作，若进行了操作则值为1并与单次操作成本系数相乘得到一次操作的成本，将所有的操作成本相加得到总操作成本。
如基于上述例子，计算由第一阶段的最小网损配网方式重构成第二阶段最小网损配网方式时的成本，获取第一阶段最优拓扑结构和第二阶段最优拓扑结构，进行比对后得到重构操作步骤，使用上述重构代价计算公式计算得到该次重构总操作的成本。
步骤S400，根据降损收益和重构代价判断目标配电网系统最佳配网方式。
进一步的，判断所述降损收益是否大于所述重构代价：若所述降损收益大于所述重构代价，则将重构后的配网方式作为所述目标电网系统的最佳配网方式；若所述降损收益小于或者等于所述重构代价则将重构前的配网方式作为所述目标电网系统的最佳配网方式。
可以理解的是，判断目标配电网系统最佳配网方式即为综合降损收益和重构代价后的最大收益的配网方式，当重构带来的降损收益大于重构代价时，则将重构后的配网方式作为最佳运行方式。若重构带来的降损收益小于或者 等于重构代价时，则将当前运行的配网方式作为最佳配网方式保持运行。
在本实施例中，考虑到配网方式实时与目标配电网系统的负荷需求和电源处理适配是无法实现，因此将负荷模型和电源模型预测的负荷需求和电源出力进行分阶段化处理，再构建与每个阶段相适应的配电网运行模型，同时将不同阶段间进行配网重构时产生的操作成本因素加入到最优配网方式的判断过程中，从而避免因重构时操作过多出现重构操作成本大于降网损收益使得总的配网重构成本上升降低了目标配电网系统运行经济性情况。
此外，本实施例还提供一种基于源网荷储分布式能源配网装置，所述基于源网荷储分布式能源配网装置应用于配电网系统，所述基于源网荷储分布式能源配网装置包括：
构建模块，用于接收目标配电网系统的线路信息，根据所述线路信息构建分布式配电网模型；
加载模块，用于接收所述目标配电网系统接入的负荷信息和接入的电源信息，根据所述负荷信息构建负荷模型，根据所述电源信息构建电源模型，并将所述负荷模型和所述电源模型加载至所述分布式配电网模型；
输出模块，用于依据所述分布式配电网模型的最小配网代价，生成所述最小配网代价下的配网方式，以对接入分布式能源的所述目标配电网系统进行配网。
可选地，所述输出模块还用于：
以所述分布式配电网模型的最小配网代价为目标构建目标函数；
当所述目标函数的函数值为最小值时，将所述分布式配电网模型的配网方式作为最小代价配网方式；
将所述目标配电网系统按所述最小代价配网方式进行配网。
可选地，所述输出模块还用于：
接收所述目标配电网系统的约束信息，根据所述约束信息生成约束函数；
当所述目标函数在所述约束函数约束下处于最小值时，将所述分布式配电网模型的配网方式作为所述最小代价配网方式。
可选地，所述约束信息至少包括潮流方程约束、分布式电源约束、线路节点电压约束、线路节点电流约束和配网辐射约束中一种，所述输出模块还 用于：
接收所述潮流方程约束，并根据所述潮流方程约束生成潮流方程约束函数；和/或
接收所述分布式电源约束，并根据所述分布式电源约束生成分布式电源约束函数；和/或
接收所述线路节点电压约束，并根据所述线路节点电压约束生成线路节点电压约束函数；和/或
接收所述线路节点电流约束，并根据所述线路节点电流约束生成线路节点电流约束函数；和/或
接收所述配网辐射约束，并根据所述配网辐射约束生成配网辐射约束函数。
可选地，所述输出模块还用于：
根据预设划分规则将所述负荷模型的第一输出结果和所述电源模型的第二输出结果离散化；
根据离散化后的所述第一输出结果生成多个阶段的负荷需求，根据离散化后的所述第二输出结果生成多个阶段的电源出力；
将各阶段的所述负荷需求经统一化后得到对应阶段的等效负荷需求，将各阶段的所述电源出力经统一化后得到对应阶段的等效电源出力；
将各阶段的所述等效负荷需求作为所述负荷模型在所述分布式配电网模型中对应阶段的等效输出结果，将各阶段的所述等效电源出力作为所述电源模型在所述分布式配电网模型中对应阶段的等效输出结果。
可选地，所述输出模块还用于：
依据各阶段下的分布式配电网模型的最小配网代价，生成各阶段最小配网代价下的配网方式；
根据所述各阶段最小配网代价下的配网方式，生成各阶段配网重构后的降损收益；
根据各阶段配网重构前后的配网方式，生成各阶段配网重构后的重构代价；
判断所述降损收益是否大于所述重构代价：
若所述降损收益大于所述重构代价，则将重构后的配网方式作为所述目 标配电网系统的最佳配网方式；
若所述降损收益小于或者等于所述重构代价，则将重构前的配网方式作为所述目标配电网系统的最佳配网方式。
可选地，所述构建模块还用于：
根据所述目标配电网系统的线路信息，获取所述目标配电网系统中的电气元件以及所述电气元件对应的连接关系；
基于所述电气元件和所述连接关系，构建目标配电网系统的所述分布式配电网模型。
本申请提供的基于源网荷储分布式能源配网装置，采用上述实施例中的基于源网荷储分布式能源配网方法，解决了分布式电源接入电网系统后影响系统运行经济性和安全性的技术问题。与现有技术相比，本申请实施例提供的基于源网荷储分布式能源配网装置的有益效果与上述实施例提供的基于源网荷储分布式能源配网方法的有益效果相同，且该基于源网荷储分布式能源配网装置中的其他技术特征与上述实施例方法公开的特征相同，在此不做赘述。
此外，本实施例还提供一种基于源网荷储分布式能源配网设备，所述基于源网荷储分布式能源配网设备包括：存储器、处理器及存储在所述存储器上并可在所述处理器上运行的基于源网荷储分布式能源配网程序，所述基于源网荷储分布式能源配网程序被所述处理器执行时实现如上述的基于源网荷储分布式能源配网方法的步骤。
本申请基于源网荷储分布式能源配网设备的具体实施方式与上述基于源网荷储分布式能源配网方法各实施例基本相同，在此不再赘述。
此外，本实施例还提供一种可读存储介质，所述可读存储介质上存储有基于源网荷储分布式能源配网程序，所述基于源网荷储分布式能源配网程序被处理器执行时实现如上述的基于源网荷储分布式能源配网方法的步骤。
本申请介质具体实施方式与上述基于源网荷储分布式能源配网方法各实施例基本相同，在此不再赘述。
需要说明的是，在本文中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者系统不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括 为这种过程、方法、物品或者系统所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括该要素的过程、方法、物品或者系统中还存在另外的相同要素。
上述本申请实施例序号仅仅为了描述，不代表实施例的优劣。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件，但很多情况下前者是更佳的实施方式。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在如上所述的一个存储介质(如ROM/RAM、磁碟、光盘)中，包括若干指令用以使得一台终端设备(可以是手机，计算机，服务器，或者网络设备等)执行本申请各个实施例所述的方法。
以上仅为本申请的优选实施例，并非因此限制本申请的专利范围，凡是利用本申请说明书及附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本申请的专利保护范围内。

Claims (10)

  1. 一种基于源网荷储分布式能源配网方法，其中，所述基于源网荷储分布式能源配网方法包括以下步骤：
    接收目标配电网系统的线路信息，根据所述线路信息构建分布式配电网模型；
    接收所述目标配电网系统接入的负荷信息和接入的电源信息，根据所述负荷信息构建负荷模型，根据所述电源信息构建电源模型，并将所述负荷模型和所述电源模型加载至所述分布式配电网模型；
    依据所述分布式配电网模型的最小配网代价，生成所述最小配网代价下的配网方式，以对接入分布式能源的所述目标配电网系统进行配网。
  2. 如权利要求1所述的基于源网荷储分布式能源配网方法，其中，所述依据所述分布式配电网模型的最小配网代价，生成所述最小配网代价下的配网方式，以对接入分布式能源的所述目标配电网系统进行配网的步骤包括：
    以所述分布式配电网模型的最小配网代价为目标构建目标函数；
    当所述目标函数的函数值为最小值时，将所述分布式配电网模型的配网方式作为最小代价配网方式；
    将所述目标配电网系统按所述最小代价配网方式进行配网。
  3. 如权利要求2所述的基于源网荷储分布式能源配网方法，其中，所述当所述目标函数的函数值为最小值时，将所述分布式配电网模型的配网方式作为最小代价配网方式的步骤包括：
    接收所述目标配电网系统的约束信息，根据所述约束信息生成约束函数；
    当所述目标函数在所述约束函数约束下处于最小值时，将所述分布式配电网模型的配网方式作为所述最小代价配网方式。
  4. 如权利要求3所述的基于源网荷储分布式能源配网方法，其中，所述约束信息至少包括潮流方程约束、分布式电源约束、线路节点电压约束、线路节点电流约束和配网辐射约束中一种，所述接收所述目标配电网系统的约束信息，根据所述约束信息生成约束函数的步骤至少包括以下一种：
    接收所述潮流方程约束，并根据所述潮流方程约束生成潮流方程约束函数；和/或
    接收所述分布式电源约束，并根据所述分布式电源约束生成分布式电源 约束函数；和/或
    接收所述线路节点电压约束，并根据所述线路节点电压约束生成线路节点电压约束函数；和/或
    接收所述线路节点电流约束，并根据所述线路节点电流约束生成线路节点电流约束函数；和/或
    接收所述配网辐射约束，并根据所述配网辐射约束生成配网辐射约束函数。
  5. 如权利要求1所述的基于源网荷储分布式能源配网方法，其中，在所述将所述负荷模型和所述电源模型加载至所述分布式配电网模型的步骤之后，包括：
    根据预设划分规则将所述负荷模型的第一输出结果和所述电源模型的第二输出结果离散化；
    根据离散化后的所述第一输出结果生成多个阶段的负荷需求，根据离散化后的所述第二输出结果生成多个阶段的电源出力；
    将各阶段的所述负荷需求经统一化后得到对应阶段的等效负荷需求，将各阶段的所述电源出力经统一化后得到对应阶段的等效电源出力；
    将各阶段的所述等效负荷需求作为所述负荷模型在所述分布式配电网模型中对应阶段的等效输出结果，将各阶段的所述等效电源出力作为所述电源模型在所述分布式配电网模型中对应阶段的等效输出结果。
  6. 如权利要求5所述的基于源网荷储分布式能源配网方法，其中，所述依据所述分布式配电网模型的最小配网代价，生成所述最小配网代价下的配网方式，以对接入分布式能源的所述目标配电网系统进行配网的步骤还包括：
    依据各阶段下的分布式配电网模型的最小配网代价，生成各阶段最小配网代价下的配网方式；
    根据所述各阶段最小配网代价下的配网方式，生成各阶段配网重构后的降损收益；
    根据各阶段配网重构前后的配网方式，生成各阶段配网重构后的重构代价；
    判断所述降损收益是否大于所述重构代价：
    若所述降损收益大于所述重构代价，则将重构后的配网方式作为所述目 标配电网系统的最佳配网方式；
    若所述降损收益小于或者等于所述重构代价，则将重构前的配网方式作为所述目标配电网系统的最佳配网方式。
  7. 如权利要求1所述的基于源网荷储分布式能源配网方法，其中，所述接收目标配电网系统的线路信息，根据所述线路信息构建分布式配电网模型的步骤包括：
    根据所述目标配电网系统的线路信息，获取所述目标配电网系统中的电气元件以及所述电气元件对应的连接关系；
    基于所述电气元件和所述连接关系，构建目标配电网系统的所述分布式配电网模型。
  8. 一种基于源网荷储分布式能源配网装置，其中，所述基于源网荷储分布式能源配网装置应用于配电网系统，所述基于源网荷储分布式能源配网装置包括：
    构建模块，用于接收目标配电网系统的线路信息，根据所述线路信息构建分布式配电网模型；
    加载模块，用于接收所述目标配电网系统接入的负荷信息和接入的电源信息，根据所述负荷信息构建负荷模型，根据所述电源信息构建电源模型，并将所述负荷模型和所述电源模型加载至所述分布式配电网模型；
    输出模块，用于依据所述分布式配电网模型的最小配网代价，生成所述最小配网代价下的配网方式，以对接入分布式能源的所述目标配电网系统进行配网。
  9. 一种基于源网荷储分布式能源配网设备，其中，所述基于源网荷储分布式能源配网设备包括：存储器、处理器及存储在所述存储器上并可在所述处理器上运行的基于源网荷储分布式能源配网程序，所述基于源网荷储分布式能源配网程序被所述处理器执行时实现如权利要求1至7中任一项所述的基于源网荷储分布式能源配网方法的步骤。
  10. 一种可读存储介质，其中，所述可读存储介质上存储有基于源网荷储分布式能源配网程序，所述基于源网荷储分布式能源配网程序被处理器执行时实现如权利要求1至7中任一项所述的基于源网荷储分布式能源配网方法的步骤。
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