A virtual power plant and distribution network collaboration method and system based on congestion management

Abstract

The present invention relates to the technical field of virtual power plants, and discloses a method and system for coordinating virtual power plants and distribution networks based on congestion management, wherein the method comprises the following steps: predicting the initial time-of-use electricity price based on historical information data of the distribution network; formulating a purchase and sale interactive power plan based on the time-of-use electricity price and the power sharing mode of producers and consumers; constructing a scheduling optimization model for the access of virtual power plants to the distribution network; and updating the time-of-use electricity price and issuing it to the virtual power plant. The present invention formulates a purchase and sale interactive power plan for virtual power plants and distribution networks based on the time-of-use electricity price and the power sharing mode of producers and consumers, constructs a scheduling optimization model for the access of virtual power plants to the distribution network, calculates the supply and demand balance price and the congestion price based on the scheduling optimization model of the distribution network, updates the time-of-use electricity price using the supply and demand balance price and the congestion price, adjusts the interactive power between the virtual power plant and the distribution network, reduces the electricity cost of the virtual power plant, and improves the economic benefits of the virtual power plant.

Description

Technical Field

[0001] The present invention specifically relates to the technical field of virtual power plants, and in particular to a method for coordinating virtual power plants and distribution networks based on congestion management. Background Art

[0002] A virtual power plant (VPP) is a power coordination management system that uses advanced information and communication technologies and software systems to achieve aggregation and coordinated optimization of DERs such as DG, energy storage systems, controllable loads, and electric vehicles, so as to participate in the power market and grid operation as a special power plant. The core of the concept of a virtual power plant can be summarized as "communication" and "aggregation". The key technologies of a virtual power plant mainly include coordinated control technology, smart metering technology, and information and communication technology.

[0003] A virtual power plant is an aggregation of multiple distributed resources. Through advanced control, communication, and metering technologies, it can aggregate a number of adjustable resources such as distributed power sources, energy storage, and flexible loads, and participate in the unified dispatch of the power grid as a whole, making full use of the coordination and complementarity of the distributed resource regulation characteristics to achieve reasonable optimization and utilization of resources. The virtual power plant operates as a special power plant to the outside world, presenting the overall functions and effects of a traditional power plant. It can be controlled and managed like a traditional power plant, including submitting power generation plans to the power grid, participating in power market transactions, and providing auxiliary services such as peak load regulation and frequency regulation. Internally, as a comprehensive energy management system, it has multiple functions such as self-coordination, self-management, and self-control.

[0004] When the power transmission requirement of the distribution network is greater than the actual transmission requirement, distribution network congestion will occur, affecting the normal power trading plan of users and undermining the safe and efficient operation of the distribution network. Therefore, how to manage distribution network congestion is crucial to achieving the safe and economical operation of VPP. VPP can aggregate the distributed power sources on the distribution network side and provide fast-response auxiliary services. Therefore, it is of practical value to use VPP to study how to eliminate the problem of distribution network congestion. Summary of the invention

[0005] The purpose of the present invention is to provide a virtual power plant and distribution network collaboration method based on congestion management to solve the problem of how to perform distribution network congestion management raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A method for coordinating a virtual power plant and a distribution network based on congestion management comprises the following steps:

[0008] S10, predicting the initial time-of-use electricity price based on historical information data of the distribution network;

[0009] S20, formulate a purchase and sale interactive power plan based on the time-of-use electricity price and the power sharing mode of the prosumers. The prosumers are entity objects in the virtual power plant that share power point-to-point in a distributed management manner, mainly including residential objects, office park objects and commercial park objects. The distributed resources managed by each prosumer include photovoltaic (PV), wind power (WP), electric vehicle (EV), household energy storage, industrial power generation equipment and commercial power load, etc. In this embodiment, the minimum total operating cost is taken as the goal, and the objective function of the virtual power plant is:

[0010] ;

[0011] in, is the dispatch cost of the gas-fired units in the virtual power plant, is the number of prosumers, To exchange power with the distribution network, is the uncontrollable distributed resource cost. In the embodiment of the present invention, the uncontrollable distributed resource cost is the wind and photovoltaic power generation abandonment cost;

[0012] It should be noted that the cost of interactive purchase and sale of power with the distribution network The calculation formula is:

[0013] ;

[0014] in, and for The time-of-day purchase and sale prices of the distribution network during the period, and for The power purchased and sold between the virtual power plant and the distribution network during the period is collectively referred to as the interactive power with the distribution network.

[0015] S30, constructing a dispatch optimization model for accessing a virtual power plant to a distribution network, and calculating a supply-demand balance price and a congestion price based on the dispatch optimization model of the distribution network;

[0016] S40, updating the time-of-use electricity price and sending it to the virtual power plant, wherein the time-of-use electricity price is the sum of the supply-demand balance price and the congestion price.

[0017] As a further solution of the present invention: in step S10, the method for predicting the initial time-of-use electricity price based on the historical price information of the distribution network includes the following steps:

[0018] S11, acquiring historical information data of the distribution network within the target area according to a preset sampling time interval, wherein the historical information data at least includes wind speed historical information data, light intensity historical information data and electricity price historical information data;

[0019] S12, preprocessing the historical information data, and performing clustering processing by a preset density peak clustering algorithm according to a preset sampling time interval, to obtain a plurality of clusters corresponding to the preset sampling time interval;

[0020] S13, fitting the historical information data in each cluster according to a preset correlation function, and determining the optimal connection mode and corresponding correlation coefficient between the correlation functions of each cluster;

[0021] S14, inputting the historical information data and the corresponding correlation coefficient into a pre-built prediction model for training, and outputting the electricity price in the future; and judging whether the prediction accuracy of the trained prediction model meets the preset accuracy threshold, if not, re-determining the optimal connection mode and the corresponding correlation coefficient between the correlation functions of each cluster, and updating the prediction model according to the re-determined correlation coefficient until the preset accuracy threshold is met, and outputting the final prediction model;

[0022] S15. Predicting the time-of-use electricity price according to the final prediction model to obtain a final time-of-use electricity price prediction result.

[0023] As a further solution of the present invention: in step S20, a method for formulating a purchase and sale interactive power plan based on time-of-use electricity prices and the power sharing mode of prosumers includes the following steps:

[0024] S21, obtaining the purchased and sold power of each producer and consumer and the distribution network in the virtual power plant during period t;

[0025] S22. Under the condition that the sum of the inflow and outflow of electric energy is equal among all producers and consumers in the virtual power plant, the purchase and sale power is summed up to obtain the purchase and sale interactive power plan of the virtual power plant.

[0026] As a further solution of the present invention: in step S22, the condition that the sum of the incoming and outgoing electric energy is equal includes that the producers and consumers in the virtual power plant satisfy the electric energy balance constraint and the constraint that the sum of the input and output electric energy is equal.

[0027] As a further solution of the present invention: in step S30, the method for calculating the supply-demand equilibrium price and the blocking price includes the following steps:

[0028] S31. Construct a dispatch optimization model for virtual power plants connected to distribution networks;

[0029] S32, constructing a system power balance constraint and a distribution network dispatchable equipment operation constraint based on the distribution network dispatch optimization model;

[0030] S33. Calculate the supply-demand equilibrium price and the congestion price.

[0031] As a further solution of the present invention: in step S31, the dispatch optimization model of the virtual power plant connected to the distribution network is:

[0032] ;

[0033] in, Indicates A virtual power plant connected to the distribution network, For the Virtual power plants connected to the distribution network The unit operating cost at the time, For the Virtual power plants connected to the distribution network The power generation capacity of the gth unit at the moment.

[0034] As a further solution of the present invention: in step S32, the system power balance constraint is:

[0035] ;

[0036] in: For the The load demand of a virtual power plant connected to the distribution network, For the The power generation capacity of the virtual power plant connected to the distribution network, The purchase and sale interactive power reported by the virtual power plant, is the Lagrange multiplier of the power balance constraint, which is also the supply and demand equilibrium price of the system.

[0037] As a further solution of the present invention: in step S32, the operation constraints of the dispatchable equipment in the distribution network are:

[0038] ;

[0039] in, and They are connected to the distribution network virtual power plant line The vector of upper and lower limits of the capacity, is the Lagrange multiplier of the line capacity constraint, represents the power transfer distribution factor of the virtual power plant;

[0040] The calculation method of the blocking price is: ;

[0041] in, is the Lagrange multiplier of the line capacity constraint, For line The power transmission distribution factor of the virtual power plant access node, Indicates The congestion price of a virtual power plant connected to the distribution network at time t.

[0042] As a further solution of the present invention: in step S40, the method for updating the time-of-use electricity price and sending it to the virtual power plant includes the following steps:

[0043] S41, obtaining a supply-demand balance price and a congestion price of the system, summing the supply-demand balance price and the congestion price to obtain a time-of-use electricity price, and replacing the initial time-of-use electricity price with the time-of-use electricity price to update the time-of-use electricity price;

[0044] S42: Send the updated time-of-use electricity price to the virtual power plant. The virtual power plant repeats steps S20-S40 based on the updated time-of-use electricity price to adjust the interactive power with the distribution network.

[0045] A virtual power plant and distribution network coordination system based on congestion management includes at least one virtual power plant connected to the distribution network and a coordination management platform, wherein:

[0046] Virtual power plants are used to predict initial TOU electricity prices based on historical information data of the distribution network; they are also used to formulate interactive power purchase and sales plans based on TOU electricity prices and the power sharing method of prosumers;

[0047] The collaborative management platform is used to construct a dispatch optimization model for virtual power plants to access the distribution network, calculate the supply and demand balance price and the congestion price based on the dispatch optimization model of the distribution network; and update the time-of-use electricity price and send it to the virtual power plant.

[0048] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention formulates a power purchase and sale interactive plan between the virtual power plant and the distribution network according to the time-of-use electricity price and the electricity sharing method of the producers and consumers, constructs a scheduling optimization model for the virtual power plant to access the distribution network, calculates the supply and demand balance price and the congestion price according to the scheduling optimization model of the distribution network, updates the time-of-use electricity price using the supply and demand balance price and the congestion price, adjusts the interactive power between the virtual power plant and the distribution network, reduces the electricity cost of the virtual power plant, and improves the economic benefits of the virtual power plant. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 The flowchart of the virtual power plant and distribution network collaboration method based on congestion management.

[0050] Figure 2 This is a flowchart of step S10 in the virtual power plant and distribution network collaboration method based on congestion management.

[0051] Figure 3 This is a flowchart of step S30 in the virtual power plant and distribution network collaboration method based on congestion management.

[0052] Figure 4This is a flowchart of step S40 in the virtual power plant and distribution network collaboration method based on congestion management.

[0053] Figure 5 This is a structural block diagram of the virtual power plant and distribution network collaborative system based on congestion management. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0055] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, it should be understood by those skilled in the art that an aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number of aspects described herein may be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein may be used to implement this device and / or practice this method.

[0056] It should be understood that although the terms first, second, etc. may be used to describe various information in the embodiments of the present invention, the information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other.

[0057] A virtual power plant is an aggregation of multiple distributed resources. Through advanced control, communication, and metering technologies, it can aggregate a number of adjustable resources such as distributed power sources, energy storage, and flexible loads, and participate in the unified dispatch of the power grid as a whole, making full use of the coordination and complementarity of the distributed resource regulation characteristics to achieve reasonable optimization and utilization of resources. The virtual power plant operates as a special power plant to the outside world, presenting the overall functions and effects of a traditional power plant. It can be controlled and managed like a traditional power plant, including submitting power generation plans to the power grid, participating in power market transactions, and providing auxiliary services such as peak load regulation and frequency regulation. Internally, as a comprehensive energy management system, it has multiple functions such as self-coordination, self-management, and self-control.

[0058] When the power transmission requirement of the distribution network is greater than the actual transmission requirement, distribution network congestion will occur, affecting the normal power trading plan of users and undermining the safe and efficient operation of the distribution network. Therefore, how to manage distribution network congestion is crucial to achieving the safe and economical operation of VPP. VPP can aggregate the distributed power sources on the distribution network side and provide fast-response auxiliary services. Therefore, it is of practical value to use VPP to study how to eliminate the problem of distribution network congestion.

[0059] Based on this, see Figures 1 to 4 In an embodiment of the present invention, a virtual power plant and distribution network collaboration method based on congestion management includes the following steps:

[0060] S10, predicting the initial time-of-use electricity price based on historical information data of the distribution network;

[0061] S20. Formulate a power purchase and sale interactive plan based on time-of-use electricity prices and the power sharing method of producers and consumers;

[0062] S30, constructing a dispatch optimization model for accessing a virtual power plant to a distribution network, and calculating a supply-demand balance price and a congestion price based on the dispatch optimization model of the distribution network;

[0063] S40, updating the time-of-use electricity price and sending it to the virtual power plant, wherein the time-of-use electricity price is the sum of the supply-demand balance price and the congestion price.

[0064] In step S10 of the embodiment of the present invention, the method for predicting the initial time-of-use electricity price based on the historical price information of the distribution network includes the following steps:

[0065] S11, acquiring historical information data of the distribution network within the target area according to a preset sampling time interval, wherein the historical information data at least includes wind speed historical information data, light intensity historical information data and electricity price historical information data;

[0066] S12, preprocessing the historical information data, and performing clustering processing by a preset density peak clustering algorithm according to a preset sampling time interval, to obtain a plurality of clusters corresponding to the preset sampling time interval;

[0067] S13, fitting the historical information data in each cluster according to a preset correlation function, and determining the optimal connection mode and corresponding correlation coefficient between the correlation functions of each cluster;

[0068] S14, inputting the historical information data and the corresponding correlation coefficient into a pre-built prediction model for training, and outputting the electricity price in the future; and judging whether the prediction accuracy of the trained prediction model meets the preset accuracy threshold, if not, re-determining the optimal connection mode and the corresponding correlation coefficient between the correlation functions of each cluster, and updating the prediction model according to the re-determined correlation coefficient until the preset accuracy threshold is met, and outputting the final prediction model;

[0069] S15. Predicting the time-of-use electricity price according to the final prediction model to obtain a final time-of-use electricity price prediction result.

[0070] In the embodiment of the present invention, the prosumer is an entity object in the virtual power plant that performs point-to-point power sharing in a distributed management manner, mainly including residential objects, office park objects and commercial park objects. The distributed resources managed by each prosumer include photovoltaic (PV), wind power (WP), electric vehicle (EV), household energy storage, industrial power generation equipment and commercial power load, etc. In this embodiment, the objective is to minimize the total operating cost, and the objective function of the virtual power plant is:

[0071] ;

[0072] in, is the dispatch cost of the gas-fired units in the virtual power plant, is the number of prosumers, To exchange power with the distribution network, is the uncontrollable distributed resource cost. In the embodiment of the present invention, the uncontrollable distributed resource cost is the wind and photovoltaic power generation abandonment cost;

[0073] It should be noted that the cost of interactive purchase and sale of power with the distribution network The calculation formula is:

[0074] ;

[0075] in, and for The time-of-day purchase and sale prices of the distribution network during the period, and for The power purchased and sold between the virtual power plant and the distribution network during the period is collectively referred to as the interactive power with the distribution network.

[0076] Furthermore, in step S20 of the embodiment of the present invention, the method for formulating a purchase and sale interactive power plan based on the time-of-use electricity price and the power sharing mode of the prosumers includes the following steps:

[0077] S21, obtaining the purchased and sold power of each producer and consumer and the distribution network in the virtual power plant during period t;

[0078] S22, summing the purchase and sale power under the condition that the sum of the inflow and outflow of electric energy between all producers and consumers in the virtual power plant is equal, thus obtaining the purchase and sale interactive power plan of the virtual power plant;

[0079] Furthermore, in step S22 of the embodiment of the present invention, the condition that the sum of the inflowing and outflowing electric energies is equal includes that the prosumers in the virtual power plant satisfy the electric energy balance constraint and the constraint that the sum of the input and output electric energies is equal.

[0080] In step S30 of the embodiment of the present invention, the method for calculating the supply-demand balance price and the blocking price includes the following steps:

[0081] S31. Construct a dispatch optimization model for virtual power plants connected to distribution networks;

[0082] S32, constructing a system power balance constraint and a distribution network dispatchable equipment operation constraint based on the distribution network dispatch optimization model;

[0083] S33. Calculate the supply-demand equilibrium price and the congestion price.

[0084] Furthermore, in step S31 in the embodiment of the present invention, the dispatch optimization model of the virtual power plant accessing the distribution network is:

[0085] ;

[0086] in, Indicates A virtual power plant connected to the distribution network, For the Virtual power plants connected to the distribution network The unit operating cost at the time, For the Virtual power plants connected to the distribution network The power generation of the g-th unit at the moment;

[0087] Furthermore, in step S32 of the embodiment of the present invention, the system power balance constraint is:

[0088] ;

[0089] in: For the The load demand of a virtual power plant connected to the distribution network, For the The power generation capacity of the virtual power plant connected to the distribution network, The purchase and sale interactive power reported by the virtual power plant, is the Lagrange multiplier of the power balance constraint, which is also the supply and demand equilibrium price of the system;

[0090] The operation constraints of the dispatchable equipment in the distribution network are: ;

[0091] in, and They are connected to the distribution network virtual power plant line The vector of upper and lower limits of the capacity, is the Lagrange multiplier of the line capacity constraint, represents the power transfer distribution factor of the virtual power plant;

[0092] Furthermore, in step S32, the blocking price is calculated as follows:

[0093] ;

[0094] in, is the Lagrange multiplier of the line capacity constraint, For line The power transmission distribution factor of the virtual power plant access node, Indicates The congestion price of a virtual power plant connected to the distribution network at time t;

[0095] It should be noted that when the line does not exceed the limit, Both are 0, at this time, the blocking price is also 0;

[0096] In step S40 of the embodiment of the present invention, the method for updating the time-of-use electricity price and sending it to the virtual power plant includes the following steps:

[0097] S41, obtaining a supply-demand balance price and a congestion price of the system, summing the supply-demand balance price and the congestion price to obtain a time-of-use electricity price, and replacing the initial time-of-use electricity price with the time-of-use electricity price to update the time-of-use electricity price;

[0098] S42: Send the updated time-of-use electricity price to the virtual power plant. The virtual power plant repeats steps S20-S40 based on the updated time-of-use electricity price to adjust the interactive power with the distribution network.

[0099] See also Figure 5 The present invention also discloses a virtual power plant and distribution network coordination system based on congestion management, including at least one virtual power plant 100 connected to a distribution network 300 and a coordination management platform 200, wherein:

[0100] The virtual power plant 100 is used to predict the initial time-of-use electricity price based on the historical information data of the distribution network; and is also used to formulate a purchase and sale interactive power plan based on the time-of-use electricity price and the power sharing method of the prosumers;

[0101] The collaborative management platform 200 is used to construct a dispatch optimization model for the virtual power plant to access the distribution network, calculate the supply and demand balance price and the congestion price based on the dispatch optimization model of the distribution network; and update the time-of-use electricity price and send it to the virtual power plant.

[0102] In addition, some embodiments may include a storage medium having a program for executing the methods described in this specification on a computer, on which at least one instruction, at least one program, code set or instruction set is stored, and when the at least one instruction, at least one program, code set or instruction set is loaded and executed by a processor, the steps in the above-mentioned method embodiments are implemented. Examples of computer-readable recording media include hardware devices specially constructed to store and execute program commands: magnetic media such as hard disks, floppy disks and tapes, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as floppy disks, and ROMs, RAMs, flash memories, etc. Examples of program commands may include: machine language codes written by a compiler and high-level language codes executed by a computer using an interpreter, etc.

[0103] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set can be stored in a non-volatile computer-readable storage medium. When the at least one instruction, at least one program, code set or instruction set is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory.

[0104] In summary, the present invention formulates a power purchase and sale interactive plan between the virtual power plant and the distribution network according to the time-of-use electricity price and the electricity sharing method of the producers and consumers, constructs a scheduling optimization model for the virtual power plant to access the distribution network, and calculates the supply and demand balance price and the congestion price according to the scheduling optimization model of the distribution network. The supply and demand balance price and the congestion price are used to update the time-of-use electricity price, adjust the interactive power between the virtual power plant and the distribution network, reduce the electricity cost of the virtual power plant, and improve the economic benefits of the virtual power plant.

[0105] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

[0106] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A virtual power plant and distribution network collaboration method based on congestion management, characterized in that: The following steps are involved: S10, predicting the initial time-of-use electricity price based on the historical information data of the distribution network, including the following steps: S11, acquiring historical information data of the distribution network within the target area according to a preset sampling time interval, wherein the historical information data at least includes wind speed historical information data, light intensity historical information data and electricity price historical information data; S12, preprocessing the historical information data, and performing clustering processing by a preset density peak clustering algorithm according to a preset sampling time interval, to obtain a plurality of clusters corresponding to the preset sampling time interval; S13, fitting the historical information data in each cluster according to a preset correlation function, and determining the optimal connection mode and corresponding correlation coefficient between the correlation functions of each cluster; S14, inputting the historical information data and the corresponding correlation coefficient into a pre-built prediction model for training, and outputting the electricity price in the future; and judging whether the prediction accuracy of the trained prediction model meets the preset accuracy threshold, if not, re-determining the optimal connection mode and the corresponding correlation coefficient between the correlation functions of each cluster, and updating the prediction model according to the re-determined correlation coefficient until the preset accuracy threshold is met, and outputting the final prediction model; S15, predicting the time-of-use electricity price according to the final prediction model to obtain the final time-of-use electricity price prediction result; S20. Formulate a power purchase and sale interactive plan based on time-of-use electricity prices and the power sharing method of producers and consumers; S30, constructing a dispatch optimization model for accessing a virtual power plant to a distribution network, and calculating a supply-demand balance price and a congestion price based on the dispatch optimization model of the distribution network; S40, updating the time-of-use electricity price and sending it to the virtual power plant, wherein the time-of-use electricity price is the sum of the supply-demand balance price and the congestion price.

2. The method for coordinating virtual power plants and distribution networks based on congestion management according to claim 1, characterized in that: In step S20, a method for formulating a power purchase and sale interactive plan based on the time-of-use electricity price and the power sharing mode of the prosumers includes the following steps: S21, obtaining the purchased and sold power of each producer and consumer and the distribution network in the virtual power plant during period t; S22. Under the condition that the sum of the inflow and outflow of electric energy is equal among all producers and consumers in the virtual power plant, the purchase and sale power is summed up to obtain the purchase and sale interactive power plan of the virtual power plant.

3. The method for coordinating virtual power plants and distribution networks based on congestion management according to claim 2, characterized in that: In step S22, the condition that the sum of the inflow and outflow electric energy is equal includes that the prosumers in the virtual power plant satisfy the electric energy balance constraint and the constraint that the sum of the input and output electric energy is equal.

4. The method for coordinating virtual power plants and distribution networks based on congestion management according to claim 1, characterized in that: In step S30, the method for calculating the supply-demand equilibrium price and the blocking price includes the following steps: S31. Construct a dispatch optimization model for virtual power plants connected to distribution networks; S32, constructing a system power balance constraint and a distribution network dispatchable equipment operation constraint based on the distribution network dispatch optimization model; S33. Calculate the supply-demand equilibrium price and the congestion price.

5. The method for coordinating virtual power plants and distribution networks based on congestion management according to claim 4 is characterized in that: In step S31, the dispatch optimization model of the virtual power plant connected to the distribution network is: in, Indicates A virtual power plant connected to the distribution network, For the Virtual power plants connected to the distribution network The unit operating cost at the time, For the Virtual power plants connected to the distribution network The power generation capacity of the gth unit at the moment.

6. The method for coordinating virtual power plants and distribution networks based on congestion management according to claim 5, characterized in that: In step S32, the system power balance constraint is: ; in: For the The load demand of a virtual power plant connected to the distribution network, For the The power generation capacity of the virtual power plant connected to the distribution network, The purchase and sale interactive power reported by the virtual power plant, is the Lagrange multiplier of the power balance constraint, which is also the supply and demand equilibrium price of the system.

7. The method for coordinating virtual power plants and distribution networks based on congestion management according to claim 6, characterized in that: In step S32, the operation constraints of the dispatchable equipment in the distribution network are: ;in, and They are connected to the distribution network virtual power plant line The vector of upper and lower limits of the capacity, is the Lagrange multiplier of the line capacity constraint, represents the power transfer distribution factor of the virtual power plant; The calculation method of the blocking price is: ; in, is the Lagrange multiplier of the line capacity constraint, For line Power transfer distribution factors with virtual power plant access nodes; Indicates The congestion price of a virtual power plant connected to the distribution network at time t.

8. The method for coordinating virtual power plants and distribution networks based on congestion management according to claim 1, characterized in that: In step S40, the method for updating the time-of-use electricity price and sending it to the virtual power plant includes the following steps: S41, obtaining a supply-demand balance price and a congestion price of the system, summing the supply-demand balance price and the congestion price to obtain a time-of-use electricity price, and replacing the initial time-of-use electricity price with the time-of-use electricity price to update the time-of-use electricity price; S42. Send the updated time-of-use electricity price to the virtual power plant. The virtual power plant repeats steps S20-S40 based on the updated time-of-use electricity price to adjust the interactive power with the distribution network.

9. A system corresponding to the virtual power plant and distribution network collaboration method based on congestion management according to any one of claims 1 to 8, characterized in that: It includes at least one virtual power plant connected to the distribution network and a collaborative management platform, wherein: Virtual power plants are used to predict initial TOU electricity prices based on historical information data of the distribution network; they are also used to formulate interactive power purchase and sales plans based on TOU electricity prices and the power sharing method of prosumers; The collaborative management platform is used to construct a dispatch optimization model for virtual power plants to access the distribution network, calculate the supply and demand balance price and the congestion price based on the dispatch optimization model of the distribution network; and update the time-of-use electricity price and send it to the virtual power plant.

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