An optimization configuration method for a park microgrid shared energy storage wind and solar power generation system

Abstract

The present invention discloses a method for optimizing the configuration of a park microgrid shared energy storage wind and photovoltaic power generation system, which belongs to the field of shared energy storage and new energy power generation technology, including: constructing an objective function based on the first cost of the park purchasing electricity from the main power grid and the second cost of investing in shared energy storage, wind power generation and photovoltaic power generation systems as targets; based on the objective function, by setting constraints, optimizing the capacity and power of the park's microgrid shared energy storage system, and the power of the wind and photovoltaic power generation systems. The present invention realizes the joint operation of industrial parks through a shared energy storage system, effectively shares excess energy, reduces the waste of wind and photovoltaic power generation, and greatly reduces the demand for industrial parks to purchase electricity from the power grid, thereby reducing the power supply cost of industrial parks, while improving the reliability of energy supply, bringing greater economic benefits to industrial parks.

Description

Technical Field

[0001] The present invention relates to the field of shared energy storage and renewable energy power generation technology, and in particular to a method and system for optimizing the configuration of a park microgrid shared energy storage wind and solar power generation system. Background Art

[0002] With the rapid growth of global energy demand and increasing concerns about environmental issues, the development of renewable energy has become a top priority. Wind power (WP) and photovoltaic power (PV), as major renewable energy sources, provide clean and abundant alternatives to traditional fossil fuels. However, their natural intermittent and variability pose challenges to stable and reliable energy supply. To address this issue, we can make full use of the complementarity of wind, solar and energy storage systems by optimizing their capacity and power levels. This helps ensure more stable power output and reduce the impact of fluctuations on the power grid.

[0003] Industrial parks, which consume a lot of energy due to the concentration of industrial activities, provide an ideal environment for distributed generation systems. These parks have always relied heavily on centralized power grids for power supply, resulting in high energy costs and increased carbon emissions. Therefore, coordinated planning of centralized shared energy storage systems (CSESS) and distributed generation (DG) systems in industrial remote areas is crucial to promoting the sustainable use of energy and achieving environmental protection goals. Most existing technologies optimize energy storage or distributed generation systems separately to save costs or maximize the use of renewable energy. However, treating each industrial park as its own system often leads to poor resource utilization and excessive energy storage costs. A better approach is to have multiple industrial parks work together. By sharing a centralized energy storage system and coordinating power generation, the park can use resources more efficiently, better manage energy fluctuations, and reduce overall costs. Furthermore, the present invention proposes a mode for optimizing shared energy storage and distributed generation in multiple parks. Summary of the invention

[0004] In order to solve the above problems, the purpose of the present invention is to provide a park microgrid shared wind, solar and storage coordinated optimization configuration technology, which aims to determine the optimal capacity and rated power of the shared energy storage system and the wind and solar power generation systems, and provide technical inspiration for shared resource management for the design and operation of industrial park energy systems, thereby improving overall efficiency and reducing overall costs.

[0005] In order to achieve the above technical objectives, the present application provides a method for optimizing the configuration of a park microgrid shared energy storage wind and solar power generation system, comprising the following steps:

[0006] The objective function is constructed based on the first cost of the park purchasing electricity from the main grid and the second cost of investing in a shared energy storage system and wind power generation and photovoltaic power generation systems;

[0007] Based on the objective function, the microgrid of the park is optimized by setting constraints, wherein the constraints include power balance constraints, operation constraints of the shared energy storage system, operation constraints of the wind power generation and photovoltaic power generation systems, and capacity and power configuration ratio constraints of the shared energy storage system and the wind power generation and photovoltaic power generation systems.

[0008] Preferably, in the process of constructing the objective function, the objective function is expressed as:

[0009]

[0010]

[0011]

[0012] in, is the total cost of electricity purchased from the main grid by all industrial parks every day; , and They are the investment costs of the shared energy storage system, photovoltaic power generation and wind power generation systems in all industrial parks; Indicates time period All industrial parks purchase electricity from the main grid. and is the configured rated power and capacity of the shared energy storage system; and Industrial Park The configuration rated power of photovoltaic power generation system and wind power generation system, and Configure prices for unit power and unit capacity of the shared energy storage system, and are the unit power configuration prices of wind power generation system and photovoltaic power generation system respectively, , and are the expected operating life of the shared energy storage system, wind power generation system and photovoltaic power generation system, respectively. Represents the total number of days in a year. is the number of industrial parks participating in the joint operation, is the total period of optimization operation, and are two slack variables.

[0013] Preferably, in the process of obtaining power balance constraints, according to the time period of each industrial park Active power load All industrial parks jointly operate and purchase electricity from the main grid , photovoltaic power generation system in the period Active power output , wind power generation system in the period Active power output , shared energy storage during the period Charging power , discharge power and , generate the power balance constraint as follows:

[0014] .

[0015] Preferably, in the process of obtaining the shared energy storage system operation constraints, based on the shared energy storage system in the time period Charge and discharge power and , charging and discharging state variables and , and energy , according to the minimum and maximum state of charge allowed by the shared energy storage system and , as well as the charging and discharging efficiency and , generate its running constraints as follows:

[0016]

[0017]

[0018]

[0019] ,

[0020] .

[0021] Preferably, in the process of obtaining the operation and planning constraints of wind power generation and photovoltaic power generation systems, based on the photovoltaic power generation systems of each industrial park in the time period Active power output , wind power generation system in the period Active power output , the photovoltaic power generation system is in the period Output per unit value , the wind power generation system is in the period Output per unit value , slack variables and and the maximum power allowed for the construction of wind power generation systems and photovoltaic power generation systems in each industrial park and , the operation and planning constraints of the photovoltaic power generation system and wind power generation system are generated as follows:

[0022]

[0023]

[0024] .

[0025] Preferably, in the process of obtaining the constraint conditions, the constraint conditions also include the main grid power purchase constraint, that is, the industrial park is only allowed to purchase electricity from the main grid and the power generated by the industrial park microgrid is not allowed to be returned to the main grid, which is expressed as:

[0026]

[0027] The capacity and power configuration ratio constraints of the shared energy storage system, wind power generation and photovoltaic power generation system are expressed as:

[0028]

[0029]

[0030] in is the minimum configuration ratio of the shared energy storage system, is the minimum continuous discharge time of the shared energy storage system;

[0031] The investment payback period constraint is expressed as:

[0032]

[0033]

[0034]

[0035]

[0036] Among them, NI is the expected number of years of investment return.

[0037] Preferably, in the process of generating the shared energy storage system operation constraints, the shared energy storage system charging and discharging power constraints are linearly expressed using the Big-M method.

[0038]

[0039]

[0040]

[0041]

[0042]

[0043] in, and are two auxiliary variables, It is a value far greater than the rated power of the shared energy storage system that can be built.

[0044] Preferably, the optimization configuration system for implementing the method includes:

[0045] A function building module, used to build an objective function based on the first cost of the park purchasing electricity from the main power grid and the second cost of investing in a shared energy storage system and a wind power generation system and a photovoltaic power generation system;

[0046] The optimization configuration module is used to optimize the configuration of the microgrid of the park based on the objective function by setting constraints, wherein the constraints include power balance constraints, operation constraints of the shared energy storage system, operation constraints of the wind power generation and photovoltaic power generation systems, and capacity and power configuration ratio constraints of the shared energy storage system and the wind power generation and photovoltaic power generation systems.

[0047] The present invention discloses the following technical effects:

[0048] The present invention can significantly reduce unit power supply cost, construction cost and comprehensive cost by coordinating the joint operation of industrial parks through a shared energy storage system, thereby reducing overall investment and operating costs.

[0049] The invention minimizes the waste of wind and photovoltaic power generation by allowing the park to share excess energy and jointly operate. This resource sharing strategy can effectively solve the curtailment problem, ensure better utilization of renewable energy and reduce the demand for grid electricity.

[0050] The jointly operated shared energy storage system proposed in the present invention can provide a larger capacity, thereby smoothing the fluctuations in wind and solar energy output, thereby improving the overall reliability and efficiency of energy supply and increasing the economic benefits of the industrial park. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0052] Figure 1 It is a schematic diagram of the joint operation of the industrial park according to the present invention;

[0053] Figure 2 is the normalized power output of wind power and photovoltaic power generation in the industrial park described in the present invention;

[0054] Figure 3 This is a typical daily load power curve of the industrial park described in the present invention.

[0055] Figure 4 The rated power comparison of photovoltaic power generation systems and wind power generation systems in each park during independent operation and joint operation described in the present invention

[0056] Figure 5 It is the comparison of the capacity and rated power of the energy storage system during independent operation and joint operation as described in the present invention;

[0057] Figure 6 It is the operation scheme of the wind power generation system, photovoltaic power generation system and energy storage system in the case of independent operation of Industrial Park A as described in the present invention;

[0058] Figure 7 It is the operation scheme of the wind power generation system, photovoltaic power generation system and energy storage system in the case of independent operation of Industrial Park B as described in the present invention;

[0059] Figure 8 It is the operation scheme of the wind power generation system, photovoltaic power generation system and energy storage system under the condition of independent operation of C Industrial Park described in the present invention;

[0060] Fig. 9 It is the operation scheme of the wind power generation system, photovoltaic power generation system and energy storage system under the joint operation condition described in the present invention;

[0061] Fig.10 It is a comparison of the power generation and abandoned power of various energy sources in different operation modes described in the present invention;

[0062] Fig.11 It is a schematic diagram of the method flow described in the present invention. DETAILED DESCRIPTION

[0063] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0064] like Figure 1-11 As shown, the present invention provides a park microgrid shared energy storage wind and solar power generation system optimization configuration technology, which minimizes two main costs: the cost of purchasing electricity from the main power grid and the investment cost of the energy storage system and the distributed power generation system. To ensure the reliability of power supply, the present invention incorporates multiple constraints. These include power balance constraints, operation constraints of the energy storage system, operation constraints of distributed power generation systems such as wind power generation and photovoltaic power generation, and capacity and rated power constraints of the energy storage system and distributed power generation system, specifically including the following:

[0065] 1. Objective function: The objective function is the product of the amount of electricity purchased and the electricity price. The investment cost of the energy storage system is divided into two parts: the investment cost of power generation and the investment cost of rated power. Similarly, the investment cost of renewable energy power generation and photovoltaic power generation is also based on its rated power investment cost:

[0066]

[0067]

[0068]

[0069] in, is the total cost of electricity purchased from the main grid by all industrial parks every day; , and They are the investment costs of the shared energy storage system, photovoltaic power generation and wind power generation systems in all industrial parks; Indicates time period All industrial parks purchase electricity from the main grid. and is the configured rated power and capacity of the shared energy storage system; and Industrial Park The configuration rated power of photovoltaic power generation system and wind power generation system, and Configure prices for unit power and unit capacity of shared energy storage systems, and are the unit power configuration prices of wind power generation system and photovoltaic power generation system respectively, , and are the expected operating life of the shared energy storage system, wind power generation system and photovoltaic power generation system, respectively. Represents the total number of days in a year. and are two slack variables.

[0070] 2. Constraints: The model is designed for the joint operation of multiple industrial parks. Renewable energy generated by each park is used preferentially to meet local energy needs, and electricity can also be shared between parks. If the renewable energy of all parks is not enough to meet the total demand, additional electricity can be purchased from the main grid. However, the excess electricity can no longer be sold to the grid and must be discarded. The constraints of the model include power balance constraints, shared energy storage system operation constraints, operation constraints of wind power and photovoltaic power generation systems in each industrial park, grid constraints, and payback period constraints.

[0071] (1) Power balance constraints: Based on the time periods of each industrial park Active power load All industrial parks jointly operate and purchase electricity from the main grid , photovoltaic power generation system in the period Active power output , wind power generation system in the period Active power output , shared energy storage during the period Charging power , discharge power and , generate the power balance constraint as follows:

[0072] .

[0073] (2) Shared energy storage system operation constraints: Based on the shared energy storage system in the time period Charge and discharge power and , charging and discharging state variables and , and energy , according to the minimum and maximum state of charge allowed by the shared energy storage system and , as well as the charging and discharging efficiency and , generate its running constraints as follows:

[0074]

[0075]

[0076]

[0077] ,

[0078]

[0079] (3) Operation and planning constraints of wind power generation and photovoltaic power generation systems: Based on the photovoltaic power generation systems in various industrial parks during the period Active power output , wind power generation system in the period Active power output , the photovoltaic power generation system is in the period Output per unit value , the wind power generation system is in the period Output per unit value , slack variables and and the maximum power allowed for the construction of wind power generation systems and photovoltaic power generation systems in each industrial park and , the operation and planning constraints of the photovoltaic power generation system and wind power generation system are generated as follows:

[0080]

[0081]

[0082] .

[0083] (4) Main grid power purchase constraint: that is, the industrial park is only allowed to purchase electricity from the main grid, and the power generated by the industrial park microgrid is not allowed to be returned to the main grid, which can be expressed as:

[0084]

[0085] (5) The capacity and power configuration ratio constraints of the shared energy storage system, wind power generation and photovoltaic power generation system are expressed as:

[0086]

[0087]

[0088] in is the minimum configuration ratio of the shared energy storage system, is the minimum continuous discharge time of the shared energy storage system;

[0089] (6) Investment payback period constraint, expressed as:

[0090]

[0091]

[0092] .

[0093] Among them, NI is the expected number of years of investment return.

[0094] 3. Solution method:

[0095] In the shared energy storage system operation constraints, due to , and They are all optimization variables, so the two constraints of the upper limit of charge and discharge power are nonlinear constraints and need to be linearized. The present invention adopts the Big-M method to deal with this problem. For each charging power constraint, an auxiliary variable and two auxiliary constraints are introduced, and for each discharge power constraint, an auxiliary variable and two auxiliary constraints are introduced, as shown below:

[0096]

[0097]

[0098]

[0099]

[0100]

[0101] in, and are two auxiliary variables, It is a value far greater than the rated power of the shared energy storage system that can be built.

[0102] The constraints are:

[0103] ,

[0104] Replace with the following constraints:

[0105]

[0106] As for the value of M, since M is equal to the rated charge or discharge power when the charge or discharge state is 1, it can be determined according to the maximum possible value of the rated charge or discharge power.

[0107] The proposed model is a mixed integer linear programming (MILP) problem. Various commercial mathematical optimization solvers, such as CPLEX, MOSEK, and Gurobi, can be used to solve MILP problems. The optimization process of the present invention mainly uses the Gurobi solver.

[0108] Examples: This section will study several cases to demonstrate the effectiveness and advantages of the proposed planning model. Figure 1As shown in the figure, consider three industrial park microgrids, each of which is independently connected to the main grid. Each park has its own photovoltaic power generation, renewable energy power generation system and load. The three parks share a storage system. The energy storage system uses lithium iron phosphate batteries with a power unit price of 800 yuan / kW and an energy unit price of 1,800 yuan / kWh. The state of charge (SOC) ranges from 10% to 90%, the charge and discharge efficiency is 95%, and the operating life is 10 years. The construction costs of the wind power generation system and the photovoltaic power generation system are 3,000 yuan / kW and 2,500 yuan / kW respectively, and the operating life is 10 years. Figure 2 The typical daily normalized power of wind turbines and photovoltaic power generation in the park is shown in Figure 1. The typical daily load curve of each park is shown in Figure 2. Figure 3 The payback period is 5 years. Based on the above parameters, two case studies were conducted.

[0109] Two case studies were conducted in the simulation:

[0110] Case 1: Study the optimal configuration of wind power generation system, photovoltaic power generation system and energy storage system when each industrial park operates independently.

[0111] Case 2: Study the optimal configuration of wind power generation system, photovoltaic power generation system and energy storage system when they jointly operate in a park and share a centralized energy storage system.

[0112] All case studies were programmed using the MATLAB 2019b platform with the YALMIP toolbox and solved using the Gurobi 10.0.2 optimization solver. Through the simulation experiments of Case 1 and Case 2, the optimal capacity allocation scheme and operation strategy of wind power generation system, photovoltaic power generation system and energy storage system in each industrial park under independent operation and joint operation modes were obtained.

[0113] Analysis of operation plan results Table 1 shows the optimal capacity and power configuration of the three industrial parks under independent operation and joint operation modes. Figure 4 A comparison of the rated powers of photovoltaic and wind power generation systems in each park is shown. Figure 5 A comparison of energy storage system capacities and power ratings is shown.

[0114] Table 1

[0115]

[0116] As shown in Table 1 and Figure 4As shown, in the independent operation mode, Industrial Park A has the highest photovoltaic power generation of 736.7kW, followed by Industrial Park C with 518.7kW and Industrial Park B with 266.9kW. The total photovoltaic power generation capacity is 1522.3 kW. In the joint operation mode, the photovoltaic power generation is redistributed: now, Park B has the largest capacity of 653.5kW, Park A with 376.8kW, and Park C with 302.9kW. Industrial Park B has the largest capacity because it has better solar resources and a more efficient photovoltaic power plant ( Figure 2 ). The total power generation capacity of the joint mode is 1333.2 kW, which is 189.1 kW less than that of the independent mode. Less capacity means lower investment cost.

[0117] As for the wind farms, the wind farm capacity of all parks was high when operating independently. When operating jointly, the wind power capacity of Industrial Park A decreased slightly, while that of Industrial Parks B and C remained unchanged ( Figure 5 The reason for this is that the wind power generation capacity of Industrial Park A is highest at night when demand is lower, resulting in more energy waste. By reducing the wind power generation capacity of Industrial Park A, power waste can be minimized. When operating jointly, other parks can supply power to Park A, ensuring that there is no power shortage.

[0118] In terms of energy storage systems, in standalone mode, Industrial Park B has the largest capacity (1274.4 kWh), followed by Industrial Park C (424.6 kWh) and Industrial Park A (298.2 kWh). In joint mode, the industrial parks share a system with a total capacity of 2210.5 kWh. Shared energy storage enables the system to operate more flexibly and efficiently in balancing energy supply and demand. Results Analysis Figure 4-6 The operation scheme of Industrial Park A, Industrial Park B and Industrial Park C when they operate independently is shown. Figure 7 The operation scheme of the joint operation is shown. Figure 4 It can be seen from the figure that when operating independently, Industrial Park A has a large amount of photovoltaic and wind power abandoned in the afternoon and evening. This is because Industrial Park A has more wind power output when the wind conditions are good at night, and the local load is not enough to absorb so much electricity, so it has to abandon the wind. For the same reason, if Figure 6 As shown, Park C has photovoltaic and wind power abandonment in the morning and noon periods.

[0119] Since the power curves of wind power and photovoltaic power are obviously complementary, and the load curve of Park B is relatively smooth with little difference between peaks and valleys, the park is able to absorb renewable energy electricity well without any wind or solar power abandonment.

[0120] Figure 6-8 It shows the operation status of Park A, Park B and Park C when they are running independently. Figure 8 shows how they perform when run jointly. Figure 6 In the example, Park A will have a lot of photovoltaic and wind energy wasted in the afternoon and evening. This is because the wind energy output is higher at night, but the local demand is too low to use all the energy, resulting in waste. Similarly, Park C ( Figure 6 ) also results in energy waste in the morning and midday when PV generation is high but demand is low. However, Industrial Park B ( Figure 7 ) The load is stable throughout the day, and there is little difference between the peak demand period and the trough demand period. Therefore, it can utilize most of the renewable energy and avoid waste.

[0121] exist Figure 8 In the joint operation, the waste of photovoltaic and wind energy in all parks is reduced. Fig. 9 The energy outputs in stand-alone and combined operation were compared. In stand-alone mode, 6892.96 kWh of wind energy and 2647.94 kWh of photovoltaic energy were wasted.

[0122] In the joint mode, waste is reduced by 60% and 87.3% respectively. This is because the parks can share energy and utilize each other's excess output. Joint operation not only reduces waste, but also reduces the need to purchase energy from the grid, reducing overall costs. Combined with Table 1, joint operation can save investment and energy costs for the park.

[0123] In order to analyze the economic feasibility of independent operation and joint operation modes, we calculated the average unit power supply cost and the average unit investment cost, as shown in Table 2. The calculation formula is as follows

[0124]

[0125]

[0126] Table 2

[0127]

[0128] Compared with the independent construction of energy storage systems in each park, the coordinated planning scheme of centralized shared energy storage and distributed power generation systems proposed for jointly operated industrial parks reduces the unit power supply cost, unit construction cost and unit comprehensive cost. This shows that the coordinated optimization scheme not only saves construction costs, but also reduces electricity purchase expenses and improves the economic benefits of the park. This is because, under the joint operation mode, resource sharing and energy complementarity solve the reduction problem caused by the mismatch between park load and wind / solar power generation. In addition, the shared energy storage system has a larger capacity and can better smooth the fluctuations in wind and solar power generation output, thereby improving the power supply reliability of the system.

[0129] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0130] In the description of the present invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0131] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for optimizing the configuration of a park microgrid shared energy storage wind and solar power generation system, characterized in that: The following steps are involved: The objective function is constructed based on the first cost of the park purchasing electricity from the main grid and the second cost of investing in a shared energy storage system and wind power generation and photovoltaic power generation systems; Based on the objective function, the microgrid of the park is optimally configured by setting constraints, wherein the constraints include power balance constraints, operation constraints of the shared energy storage system, operation constraints of the wind power generation and photovoltaic power generation systems, and capacity and power configuration ratio constraints of the shared energy storage system and the wind power generation and photovoltaic power generation systems; In the process of constructing the objective function, the objective function is expressed as: in, is the total cost of electricity purchased from the main grid by all industrial parks every day; and are the investment costs of the shared energy storage system, photovoltaic power generation and wind power generation systems in all industrial parks; P grid，t Indicates that all industrial parks purchase power from the main grid during time period t, P csess，max and E csess，max is the configuration rated power and capacity of the shared energy storage system; P pv，max，i and P wp，max，i They are the configuration rated power of the photovoltaic power generation system and wind power generation system of industrial park i, and are the unit power and unit capacity configuration prices of the shared energy storage system, c w and c pv are the unit power configuration prices of wind power generation system and photovoltaic power generation system respectively, and are the expected operating life of the shared energy storage system, wind power generation system and photovoltaic power generation system, respectively; Nd represents the total number of days in a year and are two slack variables.

2. According to claim 1, a method for optimizing the configuration of a park microgrid shared energy storage wind and solar power generation system, characterized in that: In the process of obtaining power balance constraints, according to the active power load P of each industrial park in time period t, load，i，t , All industrial parks jointly operate and purchase power Pg from the main grid rid，t , the active power output P of the photovoltaic power generation system in time period t pv，i，t , the active power output P of the wind power generation system in time period t wp，i，t , the charging power of the shared energy storage in time period t , discharge power and , generate the power balance constraint as follows: 。 3. According to claim 2, a method for optimizing the configuration of a park microgrid shared energy storage wind and solar power generation system, characterized in that: In the process of obtaining the operation constraints of the shared energy storage system, based on the charging and discharging power of the shared energy storage system in time period t and Charging and discharging state variables and , and energy E csess，t , according to the minimum and maximum state of charge SOC allowed by the shared energy storage system csess，min and SOC csess，max , and the charging and discharging efficiency η cha and η dis , generate its running constraints as follows: Ecsess,T=Ecsess,0 。 4. According to claim 3, a method for optimizing the configuration of a park microgrid shared energy storage wind and solar power generation system is characterized by: In the process of obtaining the operation and planning constraints of wind power generation and photovoltaic power generation systems, based on the active power output P of the photovoltaic power generation system in each industrial park in time period t, pv，i，t , the active power output P of the wind power generation system in time period t wp，i，t , the output per unit value μ of the photovoltaic power generation system in time period t pv，i，t , the output per unit value μ of the wind power generation system in time period t wp，i，t , slack variables and and the maximum power allowed for the construction of wind power generation systems and photovoltaic power generation systems in each industrial park and The operation and planning constraints of the photovoltaic power generation system and wind power generation system are generated as follows:

5. According to claim 4, a method for optimizing the configuration of a park microgrid shared energy storage wind and solar power generation system is characterized by: In the process of obtaining the constraint conditions, the constraint conditions also include the main grid power purchase constraint, that is, the industrial park is only allowed to purchase electricity from the main grid and the power generated by the industrial park microgrid is not allowed to be returned to the main grid, which is expressed as: The capacity and power configuration ratio constraints of the shared energy storage system, wind power generation and photovoltaic power generation system are expressed as: ， ， Where γ is the minimum configuration ratio of the shared energy storage system, is the minimum continuous discharge time of the shared energy storage system; The investment payback period constraint is expressed as: Among them, NI is the expected number of years of investment return.

6. According to claim 5, a method for optimizing configuration of a park microgrid shared energy storage wind and solar power generation system, characterized in that: In the process of generating the shared energy storage system operation constraints, the shared energy storage system charging and discharging power constraints are linearly expressed using the Big-M method: in, and are two auxiliary variables, and M is a value much larger than the rated power of the shared energy storage system that can be constructed.

7. A method for optimizing configuration of a park microgrid shared energy storage wind and solar power generation system according to any one of claims 1 to 6, characterized in that: An optimized configuration system for implementing the method includes: A function building module, used to build an objective function based on the first cost of the park purchasing electricity from the main power grid and the second cost of investing in a shared energy storage system and a wind power generation system and a photovoltaic power generation system; The optimization configuration module is used to optimize the configuration of the microgrid of the park based on the objective function by setting constraints, wherein the constraints include power balance constraints, operation constraints of the shared energy storage system, operation constraints of the wind power generation and photovoltaic power generation systems, and capacity and power configuration ratio constraints of the shared energy storage system and the wind power generation and photovoltaic power generation systems.

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