Shared energy storage configuration method and device for flexibility mutual aid among multi-energy micro-grids and medium

Abstract

The invention belongs to the technical field of energy management and optimization, and discloses a shared energy storage configuration method and device for flexibility mutual aid among multi-energy microgrids and a medium, and the method comprises the steps: obtaining planning target data, and the configuration parameters of a conventional power supply comprise the installed capacity and operation parameters of power generation equipment; constructing an alliance model of the micro-grid and the energy storage power station by taking the optimal comprehensive cost of energy storage configuration and micro-grid operation as a target; based on the alliance model, iteratively solving the transaction electric quantity and the flexibility support quantity; and calculating the bargaining capability of each main body in the alliance model based on the transaction electric quantity and the flexibility support quantity, calculating the cost and the income of each micro-grid by taking exceeding the maximum income before cooperation as a target, and outputting an energy storage configuration result and micro-grid interaction power. The method provides important guarantee for efficient, stable and sustainable operation of an energy system.

Description

Technical Field

[0001] The present invention relates to the field of energy management and optimization technology, and more specifically, to a method, device and medium for configuring shared energy storage with flexible mutual assistance among multi-energy microgrids. Background Art

[0002] Energy demand and environmental issues have promoted the development of renewable energy technology, but have also caused problems with the safety and stability of the power system. The penetration rate of distributed renewable energy has gradually increased, and the lack of carrying capacity and flexibility of local power grids that mainly absorb new energy has become increasingly prominent. The configuration of energy storage devices can achieve the temporal and spatial migration of energy and improve the flexibility of microgrids.

[0003] Existing energy storage configurations are often only carried out for a single problem (such as smoothing wind power fluctuations and improving peak load capacity), and there are problems with single energy storage functions and low utilization. The shared energy storage model uses time-sharing reuse to effectively share energy storage costs, avoid investment redundancy, increase energy storage benefits for producers and consumers, and achieve a win-win situation for all parties. The operation strategy and capacity configuration of shared energy storage are also quite different from conventional energy storage.

[0004] The operation mode of shared energy storage can be divided into capacity allocation mode and power trading mode. The capacity allocation mode may lead to redundant capacity configuration. Although the power trading mode avoids capacity waste, relevant research pays less attention to the energy storage operation mode that makes energy storage inefficient, and flexibility in microgrids should be used to its full potential as a scarce resource.

[0005] When shared energy storage conducts electricity transactions with microgrids, it needs to bear the risk of exceeding the power capacity limit, and the situation of insufficient energy storage flexibility may occur. Increasing the configuration capacity and power of energy storage can alleviate this problem, but it is accompanied by a sharp increase in costs.

[0006] Therefore, the defects existing in the prior art are mainly:

[0007] (1) Ignoring the role of flexibility market transactions in optimizing system operation: Existing energy storage configuration methods do not fully consider the importance of flexibility market transactions in optimizing system operation, resulting in low efficiency in the use of flexibility resources and failure to maximize the overall benefits of the system.

[0008] (2) Failure to fully solve the problems of insufficient energy storage flexibility and cost allocation: Traditional energy storage configuration methods often ignore the dynamic adjustment capabilities of flexible resources and fail to effectively solve the problem of insufficient flexibility of energy storage systems. At the same time, the lack of a reasonable cost allocation mechanism leads to excessively high investment and operating costs of energy storage systems.

[0009] (3) The energy mutual assistance and regulation capacity sharing mechanism among multiple microgrids is not perfect: In the existing technology, the energy mutual assistance and regulation capacity sharing mechanism among multiple microgrids is not perfect, and effective coordination and resource sharing among multiple microgrids cannot be achieved, resulting in low overall system operation efficiency and stability. Summary of the invention

[0010] The purpose of the present invention is to provide a method, device and medium for configuring shared energy storage with flexible mutual assistance among multi-energy microgrids, so as to optimize the energy storage configuration and operation cost of energy storage power station-microgrid alliance, realize flexible mutual assistance among multiple microgrids, thereby reducing the overall cost of the system and reasonably distributing the benefits of each subject. Specifically, the purpose of the present invention includes at least one of the following:

[0011] (1) Improve the utilization rate and economic benefits of energy storage systems: Through overselling strategies and flexible market trading mechanisms, efficient utilization of energy storage systems between expected demand and actual use can be achieved, thereby improving economic benefits.

[0012] (2) Reduce energy storage configuration and operating costs: Through shared energy storage models and flexibility market transactions, multiple microgrids share the construction and operating costs of the energy storage system, reducing the high investment of individual users.

[0013] (3) Enhance system flexibility and reliability: The flexibility mutual assistance mechanism and secondary market trading mechanism between multi-energy microgrids ensure the dynamic adjustment and stable operation of the system between different energy units.

[0014] (4) Promote the consumption and utilization of renewable energy: By rationally configuring energy storage systems and optimizing flexibility resources, the microgrid’s capacity to carry renewable energy can be improved, thus promoting the efficient use of renewable energy.

[0015] (5) Achieve a win-win benefit distribution mechanism for all parties: The energy storage service pricing mechanism based on the Nash bargaining model makes the benefit distribution between the energy storage system and the microgrid more fair and reasonable, promoting win-win and mutually beneficial cooperation among all parties.

[0016] (6) Supporting the integrated development of power generation, grid, load and storage: The multi-microgrid flexibility mutual assistance and shared energy storage configuration method of the present invention complies with the policy orientation of “integration of power generation, grid, load and storage” and promotes the integration and optimization of distributed energy systems.

[0017] In order to achieve the above object, the present invention adopts the following technical solution:

[0018] According to a first aspect of the present invention, a method for configuring shared energy storage with mutual flexibility among multi-energy microgrids is provided, the method comprising:

[0019] Acquire planning target data, wherein the planning target data includes renewable energy power generation capacity data of each microgrid, power load data of each microgrid, and configuration parameters of conventional power sources; wherein the renewable energy power generation capacity data of each microgrid includes installed capacity and expected power generation of wind power and photovoltaic power, and the configuration parameters of conventional power sources include installed capacity and operating parameters of power generation equipment;

[0020] With the goal of optimizing the comprehensive cost of energy storage configuration and microgrid operation, an alliance model of microgrids and energy storage power stations is constructed;

[0021] Based on the alliance model, iteratively solve the transaction power and flexibility support amount;

[0022] The bargaining power of each subject in the alliance model is calculated based on the transaction power and flexibility support, and the cost and benefit of each microgrid are calculated with the goal of exceeding the maximum benefit before cooperation, and the energy storage configuration result and microgrid interaction power are output.

[0023] According to a second aspect of the present invention, a shared energy storage configuration device for flexible mutual assistance among multi-energy microgrids is provided, the device comprising:

[0024] A data acquisition module is configured to acquire planning target data, wherein the planning target data includes renewable energy power generation capacity data of each microgrid, power load data of each microgrid, and configuration parameters of conventional power sources; wherein the renewable energy power generation capacity data of each microgrid includes installed capacity and expected power generation of wind power and photovoltaic power, and the configuration parameters of conventional power sources include installed capacity and operating parameters of power generation equipment;

[0025] The model building module is configured to build an alliance model of microgrids and energy storage power stations with the goal of optimizing the comprehensive cost of energy storage configuration and microgrid operation;

[0026] A first solving module is configured to iteratively solve the transaction power and flexibility support amount based on the alliance model;

[0027] The second solution module is configured to calculate the bargaining power of each entity in the alliance model based on the transaction power and flexibility support, calculate the cost and benefit of each microgrid with the goal of exceeding the maximum benefit before cooperation, and output the energy storage configuration result and microgrid interaction power.

[0028] According to a third aspect of the present invention, there is provided a readable storage medium storing one or more programs, wherein the one or more programs can be executed by one or more processors to implement the method as described above.

[0029] The present invention has at least the following beneficial effects:

[0030] The present invention optimizes the utilization of energy storage resources and improves the overall flexibility and reliability of the system through the flexibility market transaction mechanism and the Nash bargaining model. Its multi-energy mutual assistance mechanism improves the energy utilization efficiency of the system and further reduces the operating cost. Through a reasonable profit distribution mechanism, the interests of each entity are maximized and win-win cooperation is promoted. Therefore, the present invention not only improves the economic benefits and operating efficiency of the system, but also promotes the efficient utilization and healthy development of renewable energy. The following are the specific advantages of the present invention:

[0031] (1) Improve the utilization and economic benefits of the energy storage system: Through the overselling strategy, the energy storage system can oversell between expected demand and actual use, thereby improving the utilization of energy storage equipment. The flexibility market trading mechanism ensures that in the case of overselling, the energy storage system can make up for the shortfall by purchasing excess flexibility resources from the microgrid, thereby ensuring the stability and reliability of the system.

[0032] (2) Reduce energy storage configuration and operation costs: Through the shared energy storage model, multiple microgrids can jointly bear the construction and operation costs of the energy storage system, avoiding the high investment of a single user or microgrid. The flexibility market trading mechanism further optimizes resource allocation, allowing the energy storage system to achieve higher operating returns while reducing configuration costs.

[0033] (3) Enhance system flexibility and reliability: The flexibility mutual assistance mechanism between multi-energy microgrids enables the system to dynamically adjust and optimize allocation between different energy units, improving the stability and operating efficiency of the overall system. The establishment of a secondary flexibility trading market enables the required flexibility resources to be obtained through trading when the energy storage system is insufficiently flexible, thereby ensuring the stable operation of the system.

[0034] (4) Promote the consumption and utilization of renewable energy: As the penetration rate of distributed renewable energy continues to increase, the grid's requirements for its carrying capacity are also getting higher and higher. By rationally configuring the energy storage system and optimizing the use of flexible resources, the present invention effectively improves the microgrid's carrying capacity for renewable energy and promotes the efficient utilization and healthy development of renewable energy.

[0035] (5) A win-win benefit distribution mechanism for all parties: The energy storage service pricing mechanism based on the Nash bargaining model makes the benefit distribution between the energy storage system and the microgrid more fair and reasonable. By considering the participation of each subject and market factors, a pricing mechanism is designed to maximize the benefits of all parties, promoting win-win and mutually beneficial cooperation among all parties.

[0036] (6) Supporting the integrated development of power generation, grid, load and storage: The multi-microgrid flexibility mutual assistance and shared energy storage configuration method of the present invention complies with the policy orientation of “integration of power generation, grid, load and storage”, and is conducive to promoting the integration and optimization of distributed energy systems, and promoting the intelligent and modern development of energy systems.

[0037] In summary, the present invention realizes the resource allocation and utilization optimization between the energy storage system and the microgrid by introducing the flexibility market transaction mechanism and the Nash bargaining model. This method not only improves the utilization rate, economic benefits, flexibility and reliability of the system, but also promotes the consumption and utilization of renewable energy and promotes the development of source-grid-load-storage integration. Ultimately, it provides an important guarantee for the efficient, stable and sustainable operation of the energy system. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 A flow chart of a method for configuring shared energy storage with mutual flexibility among multi-energy microgrids according to an embodiment of the present invention is shown.

[0039] Figure 2 A diagram showing an alliance structure according to an embodiment of the present invention is shown.

[0040] Figure 3 Another flow chart of a method for configuring shared energy storage with mutual flexibility among multi-energy microgrids according to an embodiment of the present invention is shown.

[0041] Figure 4 A schematic diagram of energy storage operation status according to an embodiment of the present invention is shown.

[0042] Figure 5 A schematic diagram of transaction price results according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0043] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and specific embodiments, but are not intended to limit the present invention. For the various steps described herein, if there is no necessity for a causal relationship between each other, the order in which they are described as examples herein should not be regarded as a limitation, and those skilled in the art should know that they can be adjusted in order, as long as the logic between them is not destroyed, resulting in the inability to implement the entire process.

[0044] Inefficient configuration of energy storage will cause energy storage power station operators to face empty capacity losses. By appropriately overselling some energy storage actions, the utilization efficiency of the energy storage system can be greatly improved. However, only subjectively reducing the rated capacity will increase the risk of service default. Reasonable planning of energy storage oversold capacity and power is very important for the safe and stable operation of microgrids and energy storage power stations.

[0045] Based on this, an embodiment of the present invention provides a shared energy storage configuration method for flexible mutual assistance among multi-energy microgrids. Figure 1The flowchart of the method is shown in FIG. 1. The method starts with step S1, where planning target data is obtained, and the planning target data includes renewable energy generation capacity data of each microgrid, power load data of each microgrid, and configuration parameters of conventional power sources; wherein the renewable energy generation capacity data of each microgrid includes installed capacity and expected power generation of wind power and photovoltaic power, and the configuration parameters of conventional power sources include installed capacity and operating parameters of power generation equipment.

[0046] Step S2, with the goal of optimizing the comprehensive cost of energy storage configuration and microgrid operation, build an alliance model of microgrid and energy storage power station.

[0047] The system structure of hybrid energy multi-microgrid and shared energy storage alliance is as follows Figure 2 As shown. The alliance conducted two electricity market transactions. The first market transaction: when the microgrid lacks electricity or has surplus electricity, it can buy and sell electricity from the shared energy storage. The second flexibility market transaction: when the rated capacity and power planned by the shared energy storage under the overselling strategy cannot meet the operating needs, the remaining flexibility margin distributed in the microgrid can be purchased from the microgrid. In terms of information flow, the energy storage provides services for the microgrid and the flexibility market transaction are calculated twice; in terms of the physical level, the interactive power between the microgrid and the energy storage power station is the energy flow after the two calculations. For the microgrid, there are multiple energy flows including electric energy and thermal energy flows, and CHP couples the thermal and electric energy flows together. For the shared energy storage and microgrid, only the data center interacts with the data center to ensure privacy, and the energy and flexibility are interacted through the interconnection line. At the information level, the data center needs to collect the energy interaction of each subject and summarize and merge them. It is worth noting that when the sum of the energy interacted between each microgrid and the energy storage is zero, the energy storage does not perform charging and discharging actions and only plays the role of distributing energy flow. When the interactive energy exceeds the capacity limit or rated power limit of the shared energy storage, the shared energy storage will participate in the flexibility market transaction with its own shortfall; it can meet its own operation needs by purchasing the flexibility margin of each microgrid.

[0048] In one embodiment, the process of building an alliance model between a microgrid and an energy storage power station is as follows:

[0049] Step S11: microgrid modeling.

[0050] The CHP unit operation equation model based on the convex feasible region is established as follows:

[0051]

[0052] In the formula, and Q t are the electric and thermal power of the CHP unit at time t respectively. The vertices of the feasible region of the CHP unit can be expressed as (Q s,t , P s,t) represents; namely, A(Q1, P1), B(Q2, P2), C(Q3, P3), D(Q4, P4). s,i It represents the convex combination coefficient of the unit, N is the total number of vertices, and T is the operating cycle.

[0053] The heat production and gas consumption of CHP units and gas boilers are as follows:

[0054]

[0055] in, Indicates the heat output of the gas boiler, η CHP , η GB Indicates the efficiency of the CHP unit and boiler, V CHP,CH4 、V GB,CH4 Indicates the natural gas consumption of CHP and gas boilers.

[0056] The electrical and thermal power balance constraints of the microgrid are as follows:

[0057]

[0058] in, and represents the heat load, curtailment heat load and curtailment heat load of microgrid i participating in flexibility trading. P i,t e , It represents the power load of microgrid i at time t, the power transaction with energy storage, and the power grid-connected by renewable energy. represents the electric power of the CHP unit in microgrid i at time t. The flexibility resources are divided into the flexibility to meet its own operation and the flexibility to export to the outside: It indicates the flexibility of microgrid i to provide regulation capability for energy storage power station to participate in market transactions at time t. The flexibility of microgrid i in supplying its own operation demand at time t is specifically expressed as follows:

[0059]

[0060] In the formula, They represent the transfer load and reduction load of microgrid i at time t, It indicates that microgrid i indirectly affects the flexibility of electric power output at time t by affecting the thermal demand response, which is defined as multi-energy mutual assistance in this paper.

[0061]

[0062] in, Indicates the change in electric power caused by multi-energy mutual assistance. μ chpRepresents the conversion coefficient from thermal power to electrical power. The constraints on the relevant variables corresponding to the participating demands are as follows:

[0063]

[0064] In the formula, represents the maximum value of the reduced load of microgrid i at time t, represents the maximum value of the transferred electric load of microgrid i at time t, It represents the maximum value of the reduced heat load of microgrid i at time t.

[0065] Step S12: Establish a shared energy storage constraint model.

[0066] Energy storage operation needs to meet the constraints of the charge state, and the two states of charging and discharging cannot exist at the same time.

[0067]

[0068] In the formula, represents the charging and discharging power of the energy storage at time t, and formula (7) represents the constraint of the energy storage charge state, S min and S max Represent the minimum energy storage capacity and the maximum energy storage capacity respectively, S t and S t-1 They represent the state of charge of the energy storage at time t and time t-1 respectively, η+ and η- represent the energy storage charging efficiency and energy storage discharging efficiency respectively. In formula (8), P ess Indicates the maximum charging and discharging power of energy storage. The relationship between the shared energy storage charging and discharging power and the interactive power of each microgrid is as follows:

[0069]

[0070] In the formula, represents the flexibility of shared energy storage purchased from microgrid i at time t, represents the amount of electricity sold and purchased by shared energy storage to microgrid i at time t, and N represents the total number of microgrids.

[0071] The state of charge of shared energy storage oversale is expressed as follows:

[0072]

[0073] In the formula, Indicates the maximum and minimum oversold capacity of shared energy storage, represents the state of charge of shared energy storage oversale at time t, P buy,t P represents the amount of electricity purchased by the energy storage power station from the main grid at time t. sell,tRepresents the amount of electricity sold by the energy storage power station to the main grid at time t. Shared energy storage needs to summarize the power demand of each microgrid and judge the final charging and discharging status. The flexibility margin of energy storage is calculated as follows:

[0074]

[0075] In the formula, Indicates the maximum charging power of the energy storage, represents the maximum discharge power of energy storage, τ represents the energy storage capacity, F + (t,τ), F - (t,τ) represents the flexibility margin of energy storage up and down, and its value is closely related to the overselling decision of energy storage, as shown below:

[0076]

[0077] In the formula, F s (t) represents the amount of energy storage oversold at time t. The amount of energy storage using the oversold strategy is related to the regulation capacity of energy storage to purchase from the microgrid in the secondary participation flexibility market, which is specifically shown as follows:

[0078]

[0079] Among them, P buy,t It indicates the amount of electricity purchased by the energy storage power station from the main grid at time t.

[0080] Step S13: Establish an alliance cost model.

[0081] Step S131: Establish a microgrid cost model:

[0082]

[0083] In the formula, C MGi represents the total cost of microgrid i, C sharei represents the power transaction cost, represents the energy storage service cost, C DRi represents the corresponding cost of demand, C tsi Represents the cost of purchasing and selling electricity and gas from the outside, C rei represents the wind and solar power abandonment costs of microgrid i. The details of each cost are as follows.

[0084] External electricity and gas purchase costs:

[0085]

[0086] In the formula, It represents the gas price and the electricity selling price of the main grid, which adopts the form of peak and valley electricity price. Microgrid can purchase electricity from the large grid but cannot supply electricity in the reverse direction.

[0087] Energy transaction costs:

[0088]

[0089] In the formula, The energy storage represents the electricity price for the electricity service provided by i Microgrid. Represents the electricity price of microgrid i that provides flexibility.

[0090] Demand response costs:

[0091]

[0092] In the formula, and They are the compensation unit prices for electric load shifting, electric load reduction and thermal load reduction respectively.

[0093] Cost of curtailing wind and solar power:

[0094]

[0095] In the formula, and It represents the penalty coefficient for wind and solar power abandonment of microgrid i and the predicted value of renewable energy of microgrid i at time t.

[0096] Step S132: Establish a shared energy storage cost model.

[0097] The cost of energy storage power stations is divided into two parts. The first is the planning cost of energy storage capacity and power, which can be regarded as a one-time investment. The second is the maintenance and operation cost of energy storage power stations, which mainly refers to the cost of energy storage when providing services for microgrids.

[0098] Energy storage operation and maintenance costs:

[0099]

[0100] In the formula, Ω s ,Ω p It indicates the unit price of operating cost per unit power of the energy storage power station and the unit price of maintenance cost per unit power and capacity. and It represents the price of the microgrid's regulation capacity purchased by the energy storage power station in the secondary flexibility power market at time t, and the price of electricity purchased and sold to the main grid. max , P ess Indicates the maximum capacity and power of the configuration.

[0101] Energy storage configuration cost:

[0102]

[0103] Where r is the discount rate, which is 5% in this paper; γ is the life cycle; δ P is the unit power investment cost; E is the unit capacity investment cost; Y d P represents the daily cost coefficient. ess , S max They are the rated charging and discharging power and rated capacity of the shared energy storage power station respectively.

[0104] Shared energy storage total cost model:

[0105] C ess =C HESS +C B -C sys (twenty one)

[0106] In the formula, C ess Represents the energy storage configuration cost, from which the energy transaction cost of the microgrid needs to be subtracted, because the energy storage power station earns the revenue from the energy services of the microgrid.

[0107] Step S14, determining the prerequisites for the establishment of the alliance.

[0108] The premise for the establishment of an alliance is that the cost of participating in the alliance is less than the cost after participating in the alliance. The goal of the alliance is to minimize the total cost of multiple entities. Whether to adopt overselling is the cost change of each entity, as expressed as follows:

[0109]

[0110] Where, ΔC ess represents the change in energy storage configuration cost, C ess' represents the energy storage configuration cost before the alliance, Δ represents the change; ΔS max , ΔP ess , Δr t - , Δr t + They all correspond to the changes in the parameters described above, P ess , S max The change in microgrid cost is expressed as follows:

[0111]

[0112] In the formula, represents the energy storage operation and maintenance cost before the alliance, C B； , They all correspond to the changes in the parameters described above.

[0113] The total alliance cost is obtained by summing the above two cost changes as follows:

[0114]

[0115] In the formula, △C represents the change in cost.

[0116] When the alliance adopts the multi-microgrid flexibility mutual assistance and energy storage power station overselling operation strategy, causing the cost change ΔC<=0, the opportunity cost is higher than that of not adopting this strategy. Therefore, when ΔC<=0, the energy storage power station overselling strategy has more comparative advantages.

[0117] Step S3, based on the alliance model, iteratively solve the transaction power and flexibility support amount.

[0118] In one embodiment, the transaction power and flexibility support are iteratively solved by the following method:

[0119] The energy storage power stations participating in the transaction must meet the energy sharing balance constraints:

[0120]

[0121] The augmented Lagrange function of the cost minimization model of the first-stage sub-problem is established as follows:

[0122]

[0123] In the formula, and denote the Lagrange multiplier and penalty coefficient respectively, represents the augmented Lagrangian function, represents the minimum cost of system operation in the first stage, j represents the jth microgrid, represents the set of microgrids in the first stage subproblem.

[0124] Each iteration of the microgrid and energy storage power station requires updating decision information.

[0125]

[0126] Here, x represents the number of iterations. represents the interactive power and flexibility transaction volume after the x-th iteration of microgrid i, represents the amount of electricity interacted between microgrid i and energy storage power station after the xth iteration update, represents the flexibility transaction volume between microgrid i and energy storage power station after the xth iteration update, represents the amount of electricity interacted between microgrid i and energy storage power station after the x-1th iteration update, It represents the flexibility trading volume between microgrid i and energy storage power station after the x-1th iteration update. Then the xth strategy of energy storage power station and multiplier is updated.

[0127]

[0128] In the formula, ρ i , Both represent multipliers that appear in the calculation process.

[0129] After updating the decision information, it starts to determine whether the convergence condition is met. If not, it starts the next x+1 iterations until the algorithm converges or the maximum number of iterations is reached and the iteration ends.

[0130]

[0131] Where δ1 represents the upper limit of convergence and its value is 10 -2 If the above equation is satisfied, the algorithm converges.

[0132] Step S4, based on the transaction power and flexibility support, the bargaining power of each subject in the alliance model is calculated, with the goal of exceeding the maximum profit before cooperation, the cost and profit of each microgrid are calculated, and the energy storage configuration result and microgrid interaction power are output.

[0133] The problem of allocating excess profits between different stakeholders is addressed. The multi-microgrid and shared energy storage cooperation model constructed using Nash negotiation is as follows:

[0134]

[0135] In the formula, C i is the cost of entity i after Nash negotiation; The cost of independent operation of energy storage and microgrid i is the negotiation breakdown point. The energy provided / obtained by each entity can be regarded as a contribution to the alliance microgrid. We use a nonlinear function based on natural logarithms to quantify the contribution of different microgrids in power sharing. Microgrids negotiate with each other based on their respective contributions as bargaining power to determine the power transaction price between them and fairly distribute the benefits of energy sharing. The specific expression is as follows:

[0136]

[0137] After taking the transaction price as the coupling variable and transforming it, we get formula (33):

[0138]

[0139] In the formula, g i represents the weight coefficient;

[0140] When the transaction prices between entities are equal, consensus is reached. The specific expression of the augmented Lagrange function is established as follows:

[0141]

[0142] Each iteration of microgrids and energy storage power stations requires updating price decision information.

[0143]

[0144] Here, x represents the number of iterations. represents the interactive power and flexibility transaction volume after the x-th iteration of microgrid i. Then the x-th strategy update of the energy storage power station is as follows:

[0145]

[0146] After updating the decision information, we start to determine whether the convergence condition is met. If not, we start the next x+1 iterations until the algorithm converges or reaches the maximum number of iterations. i-j is the Lagrange coefficient multiplier; ρ i is the penalty factor. The iterative multiplier is as follows:

[0147]

[0148] Update the number of iterations, calculate the residual γ and determine whether it converges, as shown below:

[0149]

[0150] Where δ represents the upper limit of convergence and its value is 10 -2 When the above equation is satisfied for the mth time, the algorithm converges, and we have:

[0151]

[0152] Since each entity contributes differently to the alliance, it is necessary to distribute costs and profits as fairly as possible when distributing benefits. Therefore, this article quantifies the contribution of each entity to the alliance and gives it different bargaining factors based on its contribution to obtain a more reasonable result. The calculation of bargaining factors for different entities is as follows:

[0153]

[0154] In the formula, Indicates the maximum and minimum values ​​of microgrid i energy transactions, It represents the maximum and minimum value of microgrid i participating in flexibility trading.

[0155] In one embodiment, when the cost price of energy storage discharge is greater than the charging price at the same time, if charging and discharging are performed simultaneously, the energy storage cost objective function C B The incremental changes are as follows:

[0156]

[0157] In the formula, represents the repeated portion of energy storage and simultaneous charging and discharging after relaxing the complementary constraint, ΔC B This is equivalent to adding a penalty function of the simultaneous charging and discharging portion multiplied by the price coefficient. In the optimization process of minimizing cost, only when When it reaches the minimum point.

[0158] like Figure 3 As shown, it is another flow chart of a method for configuring a shared energy storage system with mutual flexibility among multi-energy microgrids. In one embodiment, the method for configuring a shared energy storage system with mutual flexibility among multi-energy microgrids is based on the following Figure 3 The process shown in the figure is to build a microgrid and energy storage power station alliance model, and to solve the privacy protection of multiple subjects, a two-stage optimization model based on distributed computing is established: the first stage aims to maximize the interests of the cooperative alliance, trading electricity and flexibility; the second stage establishes a Nash bargaining model that takes into account the differences in subject participation and market factors, and designs a storage service pricing mechanism based on this. The specific process is as follows:

[0159] Step 1: Enter planning target data

[0160] (1) Input the planned target renewable energy power data: Input the renewable energy generation capacity data of each microgrid, including the installed capacity and expected power generation of wind power, photovoltaic power, etc.

[0161] (2) Input load data: Input the power load data of each microgrid and record the load demand in different time periods in detail.

[0162] (3) Provide the conventional power source structure: Determine the configuration of conventional power sources, such as the installed capacity and operating parameters of thermal power, hydropower, natural gas and other power generation equipment.

[0163] Step 2: Build an alliance

[0164] (1) Target setting: The goal is to optimize the comprehensive cost of energy storage configuration and microgrid operation.

[0165] (2) Alliance establishment: Build an alliance of microgrids and energy storage power stations, define the cooperation mechanism and rules among various entities, and clarify the roles and responsibilities of each entity in the alliance.

[0166] Step 3: Iteratively solve the transaction power and flexibility support

[0167] (1) Transactions between microgrids and energy storage power stations: Iterative solution of transaction power: Iterative solution of transaction power between microgrids and energy storage power stations. Microgrids exchange energy with energy storage power stations based on their own needs and flexible resource supply capabilities.

[0168] (2) Iterative solution of active flexibility support: Consider the action sequence of energy storage within the energy storage power station and determine the reasonable oversale amount. Consider the demand for external electricity within the microgrid and reasonably allocate internal flexibility resources, namely the flexibility of trading with the energy storage power station and the flexibility of supporting internal operations.

[0169] Step 4: Iterative error calculation

[0170] (1) Error calculation: Calculate the iterative error. If the convergence condition is not met, iterate again.

[0171] (2) Error output: If the maximum number of iterations is exceeded, an error message is output, indicating that parameters need to be adjusted or re-planned.

[0172] (3) Entering the second stage: If the iteration error meets the convergence condition, it enters the second stage and outputs the transaction power and the active support amount of flexibility, which is the bargaining part of the transaction power and flexibility supply.

[0173] Step 5: Second stage of benefit-cost allocation

[0174] (1) Input the data of the first stage: The trading volume and active flexibility support obtained in the first stage are input into the second stage as the basic data for benefit and cost allocation.

[0175] Step 6: Calculate Bargaining Power

[0176] (1) Bargaining power calculation: The bargaining power of each bargaining entity is calculated using the data from the first phase.

[0177] (2) Goal setting: With the goal of exceeding the maximum profit before cooperation, the transaction price is iteratively solved to ensure that the interests of each entity are maximized.

[0178] Step 7: Iterative error calculation

[0179] (1) Error calculation: Calculate the iterative error. If the convergence condition is not met, iterate again.

[0180] (2) Error output: If the maximum number of iterations is exceeded, an error message is output, indicating that the bargaining strategy needs to be adjusted or recalculated.

[0181] (3) Final output: If the iterative error meets the convergence condition, the final transaction price is output, and the costs and benefits of each entity are redistributed, and the final allocation result is output.

[0182] Through the above steps, the microgrid and energy storage power station alliance can optimize operation, reduce operating costs, and through a reasonable profit distribution mechanism, ensure that the benefits of each entity in the alliance are maximized to achieve the goal of win-win cooperation.

[0183] In an exemplary embodiment, four microgrids and shared energy storage operators are used as research subjects. Three typical days of summer, winter and transition season are selected, each of which has a 24-hour operation cycle. The basic data of the typical day is shown in Table 1.

[0184] Table 1 System parameters

[0185]

[0186] In order to verify the method proposed in the present invention, two operation schemes are set up respectively: normal operation of shared energy storage and overselling strategy, and the energy storage configuration and cost results are shown in Table 2.

[0187] Table 2 Energy storage planning results

[0188]

[0189]

[0190] Comparing the two configuration schemes of shared energy storage and whether it is oversold, its rated capacity decreased by 6133.81kW.h, a decrease of 25.35%. The rated power decreased by 387.81kW, a decrease of 11.21%. At the same time, the configuration cost after energy storage conversion decreased by 1353.95, a decrease of 24.26%. After the shared energy storage adopts the oversold strategy, although the planned capacity and power are reduced, it is also necessary to pay more for purchasing flexibility in the secondary market of flexibility trading. Therefore, the reduction in the total cost of the alliance is not as large as the reduction in the energy storage planning cost, only 3.69%. It can be seen that in the planning and operation stage, adjusting the capacity and power configuration of energy storage by overselling can effectively reduce planning costs and increase the comprehensive benefits of the system.

[0191] Energy storage power stations reduce the configuration of rated capacity and rated power through overselling operations. In the process of energy storage and microgrid energy exchange, the charging and discharging power and capacity curve of shared energy storage are as follows: Figure 4 As shown, typical days are winter, summer and transition seasons. Hours 1-24 in the figure are typical days in winter, hours 25-48 are typical days in summer, and hours 49-72 represent the transition season, which are marked in the figure.

[0192] Figure 4The solid black line in the middle indicates the upper and lower limits of the energy storage capacity. The largest oversold action of shared energy storage occurred on a typical summer day, with the largest oversold capacity reaching 5324.99kW.h. When the energy storage capacity reaches the maximum capacity, the flexibility of the microgrid is used to make the actual charging and discharging power of the energy storage zero (as shown in the figure at time 30-33). Because the energy storage reaches the minimum rated capacity, it purchases the flexibility of the microgrid at 13-15 to make the actual discharge of the energy storage power station zero. At 13-18, the oversold capacity state of the energy storage exceeds the minimum capacity limit, causing oversold. After the energy storage adopts the oversold strategy, the minimum capacity of the energy storage reaches a negative value because the oversold capacity does not correspond to the actual energy storage capacity. Overall, the overall change trend of the oversold capacity of energy storage is similar to that of the actual capacity state of energy storage. In the secondary flexibility market transaction, the total amount of flexibility purchased by the energy storage from the microgrid is 123198.49kW.h. When adopting the overselling strategy, the energy storage does not purchase flexibility from the microgrid only when the capacity is insufficient, but purchases flexibility from the microgrid in advance. Therefore, the rate of increase and decrease of the oversold capacity of the energy storage is significantly higher than the rate of increase and decrease of the actual capacity state of the energy storage. The reason is that if the energy storage starts to purchase flexibility from the microgrid to make up for the oversold capacity power default only when the capacity is insufficient, then the energy storage capacity state will reach the capacity limit earlier, making it difficult for the energy storage to continue to provide services. In addition, the oversold capacity of the energy storage will also be limited by the maximum flexibility that the microgrid can provide to the energy storage at this time, resulting in a smaller oversold capacity for the energy storage, making it difficult to obtain more profits.

[0193] Different oversale strategies adopted by shared energy storage also have an impact on energy storage configuration and alliance revenue. This article selects schemes with different oversale ratios for comparison and the results are as follows:

[0194] Option 1: Minimum oversold capacity is 5% S max The maximum oversold capacity is 100% S max .

[0195] Option 2: Minimum oversold capacity is -5%S max The maximum oversold capacity is 120% S max .

[0196] Option 3: Minimum oversold capacity is -10%S max The maximum oversold capacity is 190% S max .

[0197] Solution 4: The best oversold capacity is selected: the minimum oversold capacity is -11.37%S max The maximum oversold capacity is 126.25%S max .

[0198] Table 3 Comparison of energy storage planning results

[0199]

[0200] By comparing Table 3, it can be found that the energy storage configuration costs of Schemes 1-4 are reduced by 12.12%, 6.69% and 14.99% respectively compared with Scheme 4, and the overall cost of the alliance is reduced by 526.27, 343.29 and 168.58 respectively. The energy storage oversold capacity found in this embodiment has the lowest alliance cost, the lowest energy storage rated capacity and configuration cost. Adopting different energy storage oversold strategies can have a significant impact on the rated capacity of energy storage and the energy storage configuration cost.

[0201] The flexibility supply on the microgrid side can effectively provide active support for the energy storage side, improve the operating status of energy storage, and strengthen the interconnection and mutual assistance of the microgrid shared energy storage alliance. While providing flexibility to energy storage power stations, the microgrid also needs to reasonably manage its own regulation capacity margin and participate in the flexibility market transactions of energy storage to obtain excess profits, which is the key to operation.

[0202] After the alliance completes the configuration and operation of energy storage in the first phase, the second phase is to distribute the profits of each alliance entity. The transaction price set in this embodiment shall not exceed the time-of-use electricity price on the large power grid side, thereby promoting the willingness of each microgrid to participate in energy storage transactions and increasing the arbitrage space of energy storage power stations. Figure 5 shown.

[0203] The microgrid and shared energy storage determine the transaction price through bargaining, and the energy storage can make a profit through price arbitrage. For the transaction volume of the flexibility market, the energy storage side is the buyer and the microgrids are the sellers. Therefore, for the flexibility secondary market transactions, the energy storage power station is the beneficiary regardless of the purchase and sale of electricity. The cost changes of microgrids and energy storage before and after the cost benefit distribution are shown in Table 4.

[0204] Table 4 Microgrid and energy storage costs

[0205]

[0206] The non-cooperative scenario set in this embodiment is that the microgrid operates independently. When its own regulation capacity is insufficient, the cost of purchasing and selling electricity from the main grid and the construction cost of the energy storage power station are 0. The benefits of each entity before and after the cooperation are also different. The cost of microgrid A decreased by 5464.69 yuan, a decrease of 16.97%. The cost of microgrid B decreased by 3285.42 yuan, a decrease of 8.10%. The cost reduction of microgrid C was the largest and achieved profitability. The reason is that microgrid C is a microgrid with a very high penetration rate of renewable energy. It is difficult for it to absorb so much wind power, resulting in a high cost of wind abandonment. After participating in the alliance, it can sell more surplus electricity and contribute more to the alliance. Through bargaining, the cost of energy storage is transferred to the microgrid, and the energy storage power station is profitable. At the same time, the cost of each microgrid is greatly reduced compared with before the cooperation, and the overall cost of the alliance is reduced by 18.66%. Therefore, through bargaining, each entity can get a more reasonable distribution of benefits.

[0207] In view of the problem of insufficient flexibility caused by the actual operation of shared energy storage, this embodiment can effectively affect the planning and operation costs of energy storage by establishing a shared energy storage oversale operation and microgrid flexibility active support cooperation alliance, which has the following advantages:

[0208] 1) By establishing an alliance between energy storage and microgrids, the operating costs of microgrids and the planning costs of energy storage can be effectively reduced. Through case simulation, it is found that the energy storage adopts an overselling strategy to establish a flexibility market, and the energy storage configuration capacity and power are 18067.25kW.h and 3072.78kW. Compared with the solution where the energy storage fully responds to the needs of the microgrid, the energy storage capacity and power are reduced by 25.35% and 24.26% respectively.

[0209] 2) For microgrids, by participating in the flexibility market, the oversold power of energy storage is absorbed. The enthusiasm of flexible resources to participate in market transactions is increased, and their operating costs are reduced. After the secondary distribution of benefits and costs, the total cost of all microgrids has dropped by 15.29%. For energy storage power stations, due to the increase in some operating costs due to the payment of flexibility transactions, in the long run, the redundancy of energy storage configuration is reduced and the configuration cost is reduced. The establishment of a microgrid and energy storage power station alliance has obtained excess profits and achieved win-win cooperation.

[0210] 3) A Nash bargaining model based on value contribution was constructed to reasonably allocate the total cost and cooperation benefits of the alliance. The microgrid with higher contribution will get higher net benefits, which effectively stimulated the enthusiasm of each microgrid in the alliance to participate in power interaction and flexibility supply. Microgrids with higher penetration rates of shared energy storage and some renewable energy have achieved profits of 4,509.81 yuan and 660.80 yuan respectively.

[0211] The embodiment of the present invention further provides a shared energy storage configuration device for flexible mutual assistance among multi-energy microgrids, the device comprising:

[0212] A data acquisition module is configured to acquire planning target data, wherein the planning target data includes renewable energy power generation capacity data of each microgrid, power load data of each microgrid, and configuration parameters of conventional power sources; wherein the renewable energy power generation capacity data of each microgrid includes installed capacity and expected power generation of wind power and photovoltaic power, and the configuration parameters of conventional power sources include installed capacity and operating parameters of power generation equipment;

[0213] The model building module is configured to build an alliance model of microgrids and energy storage power stations with the goal of optimizing the comprehensive cost of energy storage configuration and microgrid operation;

[0214] A first solving module is configured to iteratively solve the transaction power and flexibility support amount based on the alliance model;

[0215] The second solution module is configured to calculate the bargaining power of each entity in the alliance model based on the transaction power and flexibility support, calculate the cost and benefit of each microgrid with the goal of exceeding the maximum benefit before cooperation, and output the energy storage configuration result and microgrid interaction power.

[0216] It should be noted that the various device structures described in this embodiment belong to the same technical concept as the previously described method, and achieve the same technical effect through the same principle, which will not be repeated here.

[0217] An embodiment of the present invention further provides a readable storage medium, which stores one or more programs. The one or more programs can be executed by one or more processors to implement the method described in any of the above embodiments.

[0218] In addition, although exemplary embodiments have been described herein, the scope includes any and all embodiments based on the present invention with equivalent elements, modifications, omissions, combinations (e.g., various embodiments intersecting schemes), adaptations or changes. The elements in the claims will be interpreted broadly based on the language adopted in the claims, and are not limited to the examples described in this specification or during the implementation of this application, and the examples will be interpreted as non-exclusive. Therefore, this specification and examples are intended to be considered as examples only, and the true scope and spirit are indicated by the following claims and the full scope of their equivalents.

Claims

1. A method for configuring shared energy storage with mutual flexibility among multi-energy microgrids, characterized in that: The method comprises: Acquire planning target data, power generation capacity data, power load data of each microgrid and configuration parameters of conventional power sources; wherein the renewable energy power generation capacity data of each microgrid includes installed capacity and expected power generation of wind power and photovoltaic power, and the configuration parameters of conventional power sources include installed capacity and operating parameters of power generation equipment; With the goal of optimizing the comprehensive cost of energy storage configuration and microgrid operation, an alliance model of microgrids and energy storage power stations is constructed; Based on the alliance model, iteratively solve the transaction power and flexibility support amount; The bargaining power of each subject in the alliance model is calculated based on the transaction power and flexibility support, and the cost and benefit of each microgrid are calculated with the goal of exceeding the maximum benefit before cooperation, and the energy storage configuration result and microgrid interaction power are output.

2. The method according to claim 1, characterized in that With the goal of optimizing the comprehensive cost of energy storage configuration and microgrid operation, an alliance model of microgrid and energy storage power station is constructed, including: The CHP unit operation equation model based on the convex feasible region is established as follows: In the formula, and Q t are the electrical and thermal power of the CHP unit at time t; Q s,t , P s,t They represent the vertices of the feasible region of the CHP unit; μ s,t It represents the convex combination coefficient of the unit, N is the total number of vertices, T is the operation cycle, and s is the vertex number; The expressions for heat production and gas consumption of CHP units and gas boilers are as follows: In the formula, Q GB represents the heat output of the gas boiler, η CHP , η GB Respectively represent the efficiency of CHP unit and boiler, V CHP,CH4 、V GB,CH4 Respectively represent the natural gas consumption of CHP and gas boiler; The electrical and thermal power balance constraints of the microgrid are as follows: in, and denote the heat load, curtailed heat load and heat load curtailed by participating in flexibility trading of microgrid i respectively; They represent the power load of microgrid i at time t, the power transaction with the energy storage power station, and the power of renewable energy on the grid; represents the electric power of the CHP unit in microgrid i at time t, It indicates the flexibility of microgrid i to provide regulation capability for energy storage power station to participate in market transactions at time t. It represents the flexibility of microgrid i in supplying its own operation demand at time t, which is expressed as follows: In the formula, They represent the transfer load and reduction load of microgrid i at time t, It indicates that microgrid i indirectly affects the flexibility of electric power output at time t by affecting the thermal demand response, taking flexibility as multi-energy mutual assistance; The equilibrium relationship of multi-energy mutual assistance is expressed as: in, Indicates the change in electric power caused by multi-energy mutual assistance; μ chp Represents the conversion coefficient from thermal power to electrical power; the constraints on the relevant variables corresponding to the participating demand are as follows: In the formula, represents the maximum value of the reduced load of microgrid i at time t, represents the maximum value of the transferred electric load of microgrid i at time t, It represents the maximum value of the reduced heat load of microgrid i at time t.

3. The method according to claim 2, characterized in that In the alliance model of microgrid and energy storage power station: Energy storage operation needs to meet the constraints of the state of charge, and the two states of charging and discharging cannot exist at the same time: In the formula, r t + , They represent the charging and discharging power of energy storage at time t, P ess Indicates the maximum charge and discharge power of energy storage, S min and S max Represent the minimum energy storage capacity and the maximum energy storage capacity respectively, S t and S t-1 They represent the state of charge of the energy storage at time t and time t-1 respectively, η+ and η- represent the energy storage charging efficiency and energy storage discharging efficiency respectively; the relationship between the shared energy storage charging and discharging power and the interactive power of each microgrid is as follows: In the formula, represents the flexibility of shared energy storage purchased from microgrid i at time t, represents the amount of electricity sold and purchased by shared energy storage to microgrid i at time t, and N represents the total number of microgrids; The state of charge of shared energy storage oversale is expressed as follows: In the formula, Indicates the maximum and minimum oversold capacity of shared energy storage, represents the state of charge of shared energy storage oversale at time t, P buy,t P represents the amount of electricity purchased by the energy storage power station from the main grid at time t. sell,t It represents the amount of electricity sold by the energy storage power station to the main grid at time t; the flexibility margin of energy storage is calculated as follows: In the formula, Indicates the maximum charging power of the energy storage, represents the maximum discharge power of energy storage, τ represents the energy storage capacity, F + (t,τ), F - (t,τ) represents the flexibility margin of energy storage up and down, which is expressed as follows: In the formula, F s (t) represents the oversold amount of energy storage at time t, expressed as:

4. The method according to claim 2, characterized in that: The alliance model of the microgrid and the energy storage power station includes an alliance cost model, and the alliance cost model includes a microgrid cost model and a shared energy storage cost model; The microgrid cost model is expressed as: In the formula, represents the total cost of microgrid i, represents the power transaction cost of microgrid i, represents the energy storage service cost of microgrid i, represents the corresponding cost of microgrid i demand, represents the cost of purchasing and selling electricity and gas from the external power grid i. represents the cost of wind and solar power abandonment of microgrid i; Calculated by the following formula In the formula, Indicates the gas price and the electricity price of the main grid, in the form of peak and valley electricity prices. Microgrids can purchase electricity from the large grid but cannot send electricity in the reverse direction. Calculated by the following formula: In the formula, The energy storage represents the electricity price for the electricity service provided by i Microgrid. represents the electricity price of microgrid i that provides flexibility; Calculated by the following formula In the formula, and They are the compensation unit prices for electric load shifting, electric load reduction and thermal load reduction; Calculated by the following formula In the formula, and It represents the penalty coefficient for wind and solar abandonment of microgrid i, and the predicted value of renewable energy of microgrid i at time t; The shared energy storage cost model includes energy storage operation and maintenance costs and energy storage configuration costs; Energy storage operation and maintenance cost C B It is expressed as: In the formula, Ω s p ,Ω s ,Ω p Indicates the unit price of operating cost per unit power of the energy storage power station and the unit price of maintenance cost per unit power and capacity; and S represents the price of the microgrid's regulation capacity purchased by the energy storage power station in the secondary flexibility power market at time t, and the price of electricity purchased and sold to the main grid; max , P ess Indicates the maximum capacity and power of the configuration; Energy storage configuration cost C HESS It is expressed as: In the formula, r is the discount rate; γ is the life cycle; δ P is the unit power investment cost; E is the unit capacity investment cost; Y d represents the daily chemical cost coefficient; P ess , S max They are the rated charging and discharging power and rated capacity of the shared energy storage power station; The shared energy storage cost model is expressed as: C ess =C HESS +C B -C sys (21) In the formula, C ess Represents the energy storage configuration cost.

5. The method according to claim 4, characterized in that The alliance model is established on the premise that the following conditions are met: Where, ΔC ess represents the change in energy storage configuration cost, C ess' represents the energy storage configuration cost before the alliance, Δ represents the change; P ess , S max The change in microgrid cost is expressed as follows: In the formula, C B； represents the energy storage operation and maintenance cost before the alliance; The total alliance cost is obtained by summing the two cost changes as follows: In the formula, △C represents the change in cost.

6. The method according to claim 5, characterized in that Based on the alliance model, the transaction power and flexibility support are iteratively solved, including: The energy storage power stations participating in the transaction must meet the energy sharing balance constraints: The augmented Lagrange function of the cost minimization model of the first-stage sub-problem is established as follows: In the formula, and denote the Lagrange multiplier and penalty coefficient respectively, represents the augmented Lagrangian function, represents the minimum cost of system operation in the first stage, j represents the jth microgrid, represents the set of microgrids in the first stage sub-problem; The microgrid and energy storage power station update decision information at each iteration: Where x represents the number of iterations, represents the interactive power and flexibility transaction volume after the x-th iteration of microgrid i, represents the amount of electricity interacted between microgrid i and energy storage power station after the xth iteration update, represents the flexibility transaction volume between microgrid i and energy storage power station after the xth iteration update, represents the amount of electricity interacted between microgrid i and energy storage power station after the x-1th iteration update, represents the flexibility transaction volume between microgrid i and energy storage power station after the x-1th iteration update; Update the x-th strategy of the energy storage plant and the multiplier: In the formula, ρ i , All represent multipliers that appear in the calculation process; After updating the decision information, it starts to determine whether the convergence condition is met. If not, the next iteration starts until convergence or the maximum number of iterations is reached; Among them, δ1 represents the upper limit of convergence, and satisfying the above formula indicates convergence.

7. The method according to claim 6, characterized in that The bargaining power of each subject in the alliance model is calculated based on the transaction power and flexibility support, and the cost and benefit of each microgrid are calculated with the goal of exceeding the maximum benefit before cooperation, and the energy storage configuration result and microgrid interaction power are output, including: The problem of allocating excess profits between different stakeholders is addressed. The multi-microgrid and shared energy storage cooperation model constructed using Nash negotiation is as follows: In the formula, C i is the cost of microgrid i after Nash negotiation; The independent operation cost of energy storage and microgrid is the breaking point of negotiation; A nonlinear function based on natural logarithm is used to quantify the contribution of different microgrids in power sharing. The nonlinear function based on natural logarithm is expressed as: After taking the transaction price as the coupling variable, we can get: In the formula, g i represents the weight coefficient; When the transaction prices between entities are equal, consensus is reached and the augmented Lagrange function is established as follows: Where, L i represents the i-th Lagrangian function; Each iteration of the microgrid and energy storage power station updates the price decision information: Where x represents the number of iterations, represents the interactive power and flexibility transaction volume after the x-th iteration of microgrid i is updated; The xth strategy update of the energy storage power station is as follows: After updating the decision information, it starts to determine whether the convergence condition is met. If not, the next iteration starts until convergence or the maximum number of iterations is reached. The iteration multiplier is as follows: Update the number of iterations, calculate the residual γ and determine whether it converges, as shown below: Where δ represents the upper limit of convergence; When equation (38) is satisfied for the mth time, we have: The calculation of bargaining factors of different entities is as follows: In the formula, Indicates the maximum and minimum values ​​of microgrid i energy transactions, It represents the maximum and minimum value of microgrid i participating in flexibility trading.

8. The method according to claim 6, characterized in that The method further includes: when the cost price of energy storage discharge is greater than the charging price at the same time, if charging and discharging are performed simultaneously, the incremental change of the energy storage cost objective function is as follows: In the formula, represents the repeated portion of energy storage and simultaneous charging and discharging after relaxing the complementary constraint, ΔC B This is equivalent to adding a penalty function that multiplies the amount of electricity charged and discharged at the same time by the price coefficient. In the optimization process of minimizing the cost, only when When it reaches the minimum point.

9. A shared energy storage configuration device with flexible mutual assistance among multi-energy microgrids, characterized in that: The device comprises: A data acquisition module is configured to acquire planning target data, wherein the planning target data includes renewable energy power generation capacity data of each microgrid, power load data of each microgrid, and configuration parameters of conventional power sources; wherein the renewable energy power generation capacity data of each microgrid includes installed capacity and expected power generation of wind power and photovoltaic power, and the configuration parameters of conventional power sources include installed capacity and operating parameters of power generation equipment; The model building module is configured to build an alliance model of microgrids and energy storage power stations with the goal of optimizing the comprehensive cost of energy storage configuration and microgrid operation; A first solving module is configured to iteratively solve the transaction power and flexibility support amount based on the alliance model; The second solution module is configured to calculate the bargaining power of each entity in the alliance model based on the transaction power and flexibility support, calculate the cost and benefit of each microgrid with the goal of exceeding the maximum benefit before cooperation, and output the energy storage configuration result and microgrid interaction power. 10 . A non-transitory computer-readable storage medium storing instructions, which, when executed by a processor, perform the method according to claim 1 .

Images