Shared energy storage configuration method, device and medium for flexible mutual assistance among multi - energy microgrids

Abstract

The present invention belongs to the technical field of energy management and optimization, and discloses a shared energy storage configuration method, device and medium for flexible mutual assistance among multi-energy microgrids. The method includes: obtaining planning target data, where the configuration parameters of the conventional power source include the installed capacity and operating parameters of the power generation equipment; constructing a coalition model of the microgrid and the energy storage power station with the goal of the optimal comprehensive cost of energy storage configuration and microgrid operation; based on the coalition model, iteratively solving the transaction power and flexibility support power; calculating the bargaining power of each subject in the coalition model based on the transaction power and flexibility support power, and calculating the costs and benefits of each microgrid with the goal of exceeding the maximum benefit before cooperation, and outputting the energy storage configuration result and the microgrid interaction power. The present invention provides an important guarantee for the efficient, stable and sustainable operation of the energy system.

Description

Technical Field

[0001] The present invention relates to the technical field of energy management and optimization, and more specifically, to a shared energy storage configuration method, device, and medium for flexible mutual assistance between multiple energy microgrids. Background Art

[0002] The energy demand and environmental problems have promoted the development of renewable energy technologies, but also triggered the safety and stability problems of the power system. The penetration rate of distributed renewable energy is gradually increasing, and the problems of insufficient bearing capacity and flexibility of local power grids mainly for consuming new energy are becoming more prominent. Configuring energy storage devices can achieve the spatio-temporal migration of energy and improve the flexibility of the microgrid.

[0003] Existing energy storage configurations often only address single problems (such as suppressing the power fluctuation of wind power and improving the peak shaving ability), resulting in the problems of single energy storage function and low utilization rate. The shared energy storage mode uses time-sharing multiplexing to effectively share the energy storage cost, avoid redundant investment, improve the energy storage income of prosumers, and achieve a win-win situation for multiple parties. The operation strategy and capacity configuration of shared energy storage also differ greatly from those of conventional energy storage.

[0004] For the operation mode of shared energy storage, it can be divided into the capacity allocation mode and the power trading mode. The capacity allocation mode may lead to redundant capacity configuration. Although the power trading mode avoids capacity waste, relevant research has less attention on the energy storage operation mode, resulting in inefficient use of energy storage, and flexibility as a scarce resource in the microgrid should be "fully utilized".

[0005] When shared energy storage conducts power trading with the microgrid, it needs to bear the risk of power capacity over-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 main defects in the prior art are as follows:

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

[0008] (2) Failing to comprehensively solve the problems of insufficient energy storage flexibility and cost allocation: Traditional energy storage configuration methods often ignore the dynamic regulation ability of flexibility resources, fail to effectively solve the problem of insufficient flexibility of the energy storage system, and lack a reasonable cost allocation mechanism, resulting in too high investment and operation costs of the energy storage system.

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

[0010] The purpose of the present invention is to provide a shared energy storage configuration method, device and medium for flexible mutual assistance among multiple energy microgrids, so as to optimize the energy storage configuration and operation cost of the energy storage power station - microgrid alliance, realize flexible mutual assistance among multiple microgrids, thereby reducing the overall system cost 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 the energy storage system: Through the over-selling strategy and flexible market trading mechanism, realize the efficient utilization of the energy storage system between the expected demand and the actual use, and enhance the economic benefits.

[0012] (2) Reduce the energy storage configuration and operation costs: Through the shared energy storage mode and flexible market trading, multiple microgrids jointly bear the construction and operation costs of the energy storage system, reducing the high investment of individual users.

[0013] (3) Enhance the flexibility and reliability of the system: The flexible mutual assistance mechanism and secondary market trading mechanism among multiple energy microgrids ensure the dynamic regulation and stable operation of the system among different energy units.

[0014] (4) Promote the consumption and utilization of renewable energy: By reasonably configuring the energy storage system and optimizing flexible resources, improve the carrying capacity of the microgrid for renewable energy and promote the efficient utilization of renewable energy.

[0015] (5) Realize a win-win interest distribution mechanism for multiple parties: Based on the energy storage service pricing mechanism of the Nash bargaining model, make the interest distribution between the energy storage system and the microgrid more fair and reasonable, and promote win-win cooperation and mutual benefit among multiple parties.

[0016] (6) Support the integrated development of the source-grid-load-storage: The method for flexible mutual assistance and shared energy storage configuration of multiple microgrids in the present invention conforms to the policy orientation of "source-grid-load-storage integration", and promotes the integration and optimization of distributed energy systems.

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

[0018] According to the first aspect of the present invention, a shared energy storage configuration method for flexible mutual assistance among multiple energy microgrids is provided, and the method includes:

[0019] Obtain the planned target data, where the planned target data includes the renewable energy power generation capacity data of each microgrid, the electricity load data of each microgrid, and the configuration parameters of the conventional power sources; among them, the renewable energy power generation capacity data of each microgrid includes the installed capacity and expected power generation of wind power and photovoltaic power, and the configuration parameters of the conventional power sources include the installed capacity and operating parameters of the power generation equipment;

[0020] With the goal of optimizing the comprehensive cost of energy storage configuration and microgrid operation, construct an alliance model of the microgrid and the energy storage power station;

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

[0022] Based on the transaction electricity quantity and the flexibility support quantity, calculate the bargaining power of each entity in the alliance model, and with the goal of exceeding the maximum benefit before cooperation, calculate the costs and benefits of each microgrid, and output the energy storage configuration result and the microgrid interaction power.

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

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

[0025] A model construction module configured to construct an alliance model of the microgrid and the energy storage power station with the goal of optimizing the comprehensive cost of energy storage configuration and microgrid operation;

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

[0027] A second solving module configured to calculate the bargaining power of each entity in the alliance model based on the transaction electricity quantity and the flexibility support quantity, and with the goal of exceeding the maximum benefit before cooperation, calculate the costs and benefits of each microgrid, and output the energy storage configuration result and the microgrid interaction power.

[0028] According to the third aspect of the present invention, there is provided a readable storage medium storing one or more programs, and 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] Through a flexible market trading mechanism and the Nash bargaining model, the present invention optimizes the utilization of energy storage resources, improves the overall flexibility and reliability of the system. Its multi-energy complementary mechanism enhances the energy utilization efficiency of the system and further reduces the operating cost. By means of a reasonable revenue distribution mechanism, the interests of all parties are maximized to promote win-win cooperation. 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 rate and economic benefits of the energy storage system: Through the over-selling strategy, the energy storage system can conduct over-selling between the expected demand and the actual use, improving the utilization rate of energy storage devices. The flexible market trading mechanism ensures that in the case of over-selling, the energy storage system can purchase the redundant flexibility resources of the microgrid to make up for the deficiency, thus ensuring the stability and reliability of the system.

[0032] (2) Reduce the energy storage configuration and operation costs: Through the shared energy storage mode, multiple microgrids can jointly bear the construction and operation costs of the energy storage system, avoiding high investment for individual users or microgrids. The flexible market trading mechanism further optimizes the resource allocation, enabling the energy storage system to achieve higher operating benefits while reducing the configuration costs.

[0033] (3) Enhance the system flexibility and reliability: The flexibility complementary mechanism between multi-energy microgrids enables the system to conduct dynamic regulation and optimal allocation among different energy units, improving the overall stability and operating efficiency of the system. The establishment of the secondary flexibility trading market enables the acquisition of the required flexibility resources through trading when the flexibility of the energy storage system is insufficient, thus ensuring the stable operation of the system.

[0034] (4) Promote the consumption and utilization of renewable energy: With the continuous increase in the penetration rate of distributed renewable energy, the grid's requirements for its carrying capacity are also getting higher and higher. By reasonably configuring the energy storage system and optimizing the utilization of flexibility resources, the present invention effectively improves the carrying capacity of the microgrid for renewable energy, promoting the efficient utilization and healthy development of renewable energy.

[0035] (5) Implement a win-win interest distribution mechanism for multiple parties: The energy storage service pricing mechanism based on the Nash bargaining model makes the interest distribution between the energy storage system and the microgrid more fair and reasonable. By considering the participation of all parties and market factors, a pricing mechanism that can maximize the benefits of all parties is designed, promoting win-win cooperation and common benefits for multiple parties.

[0036] (6) Support the integrated development of power sources, grids, loads, and energy storage: The multi-microgrid flexibility complementary and shared energy storage configuration method of the present invention conforms to the policy orientation of "integrated development of power sources, grids, loads, and energy storage", which is conducive to promoting the integration and optimization of distributed energy systems and the intelligent and modern development of the energy system.

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

[0038] Figure 1 The flowchart of a shared energy storage configuration method for flexibility mutual assistance between multiple energy microgrids according to an embodiment of the present invention is shown.

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

[0040] Figure 3 Another flowchart of a shared energy storage configuration method for flexibility mutual assistance between multiple energy microgrids according to an embodiment of the present invention is shown.

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

[0042] Figure 5 The schematic diagram of the trading price result according to an embodiment of the present invention is shown. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] To enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings and specific examples, but shall not be construed as a limitation to the present invention. For the various steps described herein, if there is no necessity for a front-back relationship between them, the order in which they are described as examples herein shall 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 and the entire process cannot be realized.

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

[0045] Based on this, an embodiment of the present invention provides a shared energy storage configuration method for flexibility mutual assistance between multiple energy microgrids. As Figure 1As shown, it is the flowchart of this method. This method starts from step S1, obtaining the planned target data, where the planned target data includes the renewable energy power generation capacity data of each microgrid, the electricity load data of each microgrid, and the configuration parameters of conventional power sources; among them, the renewable energy power generation capacity data of each microgrid includes the installed capacity and expected power generation of wind power and photovoltaic power, and the configuration parameters of conventional power sources include the installed capacity and operating parameters of power generation equipment.

[0046] Step S2, aiming at the optimal comprehensive cost of energy storage configuration and microgrid operation, constructing an alliance model of the microgrid and the energy storage power station.

[0047] The structure of the multi-microgrid with hybrid energy and the shared energy storage alliance system is as Figure 2 shown. The alliance conducts two electricity market transactions respectively. The first market transaction: when the microgrid lacks or has surplus electric energy, it can buy and sell electric energy from the shared energy storage. The second flexibility market transaction: when the rated capacity and power planned under the over-selling strategy of the shared energy storage are difficult to meet the operation requirements, it can buy the remaining flexibility margin distributed in the microgrid from the microgrid. In terms of information flow, two calculations are carried out respectively for the electricity transaction and the flexibility market transaction in which the energy storage provides services for the microgrid; at the physical level, the interactive power between the microgrid and the energy storage power station is the electric energy flow after two calculations. Inside the microgrid, there are multiple energy flows including electric energy and heat energy flows, and the CHP couples the thermal and electric energy flows together. For the shared energy storage and the microgrid, only interacting with the data center to ensure privacy, and interacting energy and flexibility through the tie line. At the information level, the data center needs to collect the energy interaction situations of each subject and conduct summary and merging processing. It should be noted that when the total sum of the energy interactions between each microgrid and the energy storage is zero, at this time the energy storage does not perform charging and discharging actions and only plays the role of distributing the energy flow. When the interactive energy exceeds the capacity limit or the rated power limit of the shared energy storage, the shared energy storage will participate in the flexibility market transaction with its own deficit amount; by purchasing the flexibility margin of each microgrid, it can meet its own operation.

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

[0049] Step S11, microgrid modeling.

[0050] Establish the following CHP unit operation equation model based on the convex feasible region:

[0051]

[0052] In the formula, and Q t are respectively the electric and thermal powers of the CHP unit at time t. The vertex of the CHP unit feasible region can be represented by (Q s,t , P s,t ); that is, A(Q 1, P 1 ), B(Q 2 , P 2 ), C(Q 3 , P 3 ), D(Q 4 , P 4 ) four vertices. μ s,i represents the convex combination coefficient of the unit, N is the total number of vertices, and T is the operation period.

[0053] The heat production and gas consumption of the CHP unit and the gas boiler are as follows:

[0054]

[0055] Among them, represents the heat production of the gas boiler, η CHP , η GB represent the efficiency of the CHP unit and the boiler, V CHP,CH4 , V GB,CH4 represent the natural gas consumption of the CHP and the gas boiler.

[0056] The power balance constraints of the microgrid for electricity and heat are as follows:

[0057]

[0058] Among them, and represent the heat load, curtailed heat load, and heat load curtailed by participating in flexibility trading of microgrid i. In the power balance constraint P i,t e , represent the electrical load, electricity trading with energy storage, and grid-connected electricity of renewable energy of microgrid i at time t. represents the electrical 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 output outward: represents the flexibility of microgrid i to provide regulation capacity for the energy storage power station to participate in market trading at time t, represents the flexibility of microgrid i to supply its own operation demand at time t. The specific description is as follows:

[0059]

[0060] In the formula, respectively represent the transferred electrical load and curtailed electrical load of microgrid i at time t, represents the flexibility of microgrid i to indirectly affect the electrical power output by influencing the heat demand response. In this paper, it is defined as multi-energy mutual assistance.

[0061]

[0062] Among them, represents the change in electric power caused by the multi - energy complementarity. μ chp represents the conversion coefficient from thermal power to electric power. The constraints of the relevant variables involved in the demand response are as follows:

[0063]

[0064] In the formula, represents the maximum value of the curtailed electric load of micro - grid i at time t, represents the maximum value of the transferred electric load of micro - grid i at time t, represents the maximum value of the curtailed thermal load of micro - grid i at time t.

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

[0066] The operation of the energy storage needs to meet the constraints of the state of charge, and the two states of charging and discharging cannot exist simultaneously.

[0067]

[0068] In the formula, represents the charging and discharging power of the energy storage at time t. Formula (7) represents the constraint of the state of charge of the 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 represent the state of charge of the energy storage at time t and at time t - 1 respectively. η+ and η - represent the charging efficiency and discharging efficiency of the energy storage respectively. In formula (8), P ess represents the maximum charging and discharging power of the energy storage. The relationship between the charging and discharging power of the shared energy storage and the interactive power of each micro - grid is as follows:

[0069]

[0070] In the formula, represents the flexibility purchased by the shared energy storage from micro - grid i at time t, represents the electricity quantity sold and purchased by the shared energy storage from micro - grid i at time t. N represents the total number of micro - grids.

[0071] The state of charge of the over - sold shared energy storage is expressed as follows:

[0072]

[0073] In the formula, represents the maximum and minimum over - sold capacities of the shared energy storage, represents the state of charge of the over - sold shared energy storage at time t, P buy,tRepresents the electricity purchased by the energy storage power station from the main grid at time t, P sell,t Represents the electricity sold by the energy storage power station to the main grid at time t. The shared energy storage needs to aggregate the electricity demands of each microgrid and judge the final charge-discharge state. The up- and down-regulation flexibility margins of the energy storage are calculated as follows:

[0074]

[0075] In the formula, Represents the maximum charging power of the energy storage, Represents the maximum discharging power of the energy storage, τ represents the energy storage capacity size, F + (t, τ), F - (t, τ) represents the up- and down-regulation flexibility margins of the energy storage, and its value is closely related to the over-sale decision of the energy storage, and the specific performance is as follows:

[0076]

[0077] In the formula, F s (t) represents the over-sold electricity of the energy storage at time t. The electricity amount of the energy storage adopting the over-sale strategy is related to the regulation capacity purchased by the energy storage participating in the flexibility market for the second time from the microgrid, and the specific performance is as follows:

[0078]

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

[0080] Step S13: Establish a coalition 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 trading cost, Represents the energy storage service cost, C DRi Represents the demand response cost, C tsi Represents the cost of purchasing and selling electricity and gas from outside, C rei Represents the curtailment cost of wind and light of microgrid i. The details of each cost are as follows.

[0084] External power and gas purchase cost:

[0085]

[0086] In the formula, It represents the gas price and the electricity selling price of the main grid, adopting the peak-valley electricity price form. The microgrid can purchase electricity from the large power grid but cannot feed electricity back.

[0087] Energy trading cost:

[0088]

[0089] In the formula, represents the electricity price at which the energy storage provides electricity service to the i-th microgrid, represents the electricity price at which the i-th microgrid provides flexibility.

[0090] Demand response cost:

[0091]

[0092] In the formula, and are respectively the compensation unit prices for electricity load transfer, electricity load curtailment, and heat load curtailment.

[0093] Cost of curtailed wind and curtailed light:

[0094]

[0095] In the formula, and represent the penalty coefficients for curtailed wind and curtailed light of the i-th microgrid, and the predicted value of renewable energy of the i-th microgrid at time t.

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

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

[0098] Energy storage operation and maintenance cost:

[0099]

[0100] In the formula, Ω s and Ω p represent the unit power operation cost unit price and the unit power and capacity maintenance cost unit price of the energy storage power station. and represent the price of the regulation capacity purchased by the microgrid in the secondary flexibility power market of the energy storage power station at time t, and the electricity prices for purchasing and selling electricity from / to the main grid. S max and P ess represent the configured maximum capacity and power.

[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] Sum the above two cost change amounts to obtain the total cost of the alliance as follows:

[0114]

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

[0116] When the alliance adopts the multi - microgrid flexibility mutual assistance and energy storage power station over - selling operation strategy, and the cost change amount ΔC <= 0, the opportunity cost is higher compared with not adopting this strategy. Therefore, when ΔC <= 0, the over - selling strategy of the energy storage power station has a greater comparative advantage.

[0117] Step S3: Based on the alliance model, iteratively solve the trading electricity quantity and flexibility support quantity.

[0118] In one embodiment, the trading electricity quantity and flexibility support quantity are iteratively solved by the following method:

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

[0120]

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

[0122]

[0123] In the formula, and represent the Lagrange multiplier and penalty coefficient respectively, represents the augmented Lagrangian function, represents the minimum cost of the first - stage system operation, j represents the j - th microgrid, represents the set of microgrids in the first - stage sub - problem.

[0124] The microgrid and the energy storage power station need to update the decision information at each iteration.

[0125]

[0126] Among them, x represents the number of iterations. represents the electricity quantity and flexibility trading volume of the interaction after the x - th iteration update of microgrid i, represents the electricity quantity of the interaction after the x - th iteration update between microgrid i and the energy storage power station, represents the flexibility trading volume of the interaction after the x - th iteration update between microgrid i and the energy storage power station, represents the electricity quantity of the interaction after the (x - 1) - th iteration update between microgrid i and the energy storage power station, It represents the flexibility trading volume after the (x - 1)-th iteration update of Microgrid i and the energy storage power station. Subsequently, the x-th strategy of the energy storage power station and the multiplier is updated.

[0127]

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

[0129] After updating the decision information, it starts to judge whether the convergence condition is met. If not, it starts the next (x + 1)-th iteration until the algorithm converges or reaches the maximum number of iterations to end the iteration.

[0130]

[0131] where δ 1 represents the convergence upper limit, and its value is 10 -2 . Meeting the above formula indicates that the algorithm converges.

[0132] Step S4: Calculate the bargaining power of each entity in the alliance model based on the transaction power and flexibility support power. Aiming at exceeding the maximum revenue before cooperation, calculate the costs and revenues of each microgrid, and output the energy storage configuration result and the interactive power of the microgrids.

[0133] Among different interest entities, there is an issue of distributing the excess revenue of the alliance. The multi-microgrid and shared energy storage cooperation model constructed by Nash negotiation is as follows:

[0134]

[0135] In the formula, C i is the cost of entity i after Nash negotiation; is the independent operation cost of the energy storage and Microgrid i, that is, the breakdown point of the negotiation. The provision / obtaining of energy by each entity can be regarded as a contribution to the alliance microgrid. We use a non-linear function based on the natural logarithm to quantify the contribution of different microgrids in the sharing of electric energy. The microgrids negotiate with each other with their respective contributions as the bargaining power, so as to determine the electricity trading price between them and fairly distribute the benefits of energy sharing. The specific description is as follows:

[0136]

[0137] After taking the trading price as the coupling variable and converting, formula (33) is obtained

[0138]

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

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

[0141]

[0142] The microgrid and the energy storage power station need to update the price decision information at each iteration.

[0143]

[0144] Among them, x represents the number of iterations. represents the interactive power and flexibility trading volume after the microgrid update in 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, it starts to judge whether the convergence condition is reached. If not satisfied, the next (x + 1)-th iteration starts until the algorithm converges or the maximum number of iterations is reached to end the iteration. Among them, λ i-j is the Lagrange coefficient multiplier; ρ i is the penalty factor. The iteration multiplier is as follows:

[0147]

[0148] Update the iteration number, calculate the residual γ and judge whether it converges, as shown below:

[0149]

[0150] Among them, δ represents the convergence upper limit, and its value is 10 -2 . When the above formula is satisfied at the m-th time, it means the algorithm converges, then there is:

[0151]

[0152] Since the contribution degrees of each entity to the alliance are different, when distributing the benefits, it is necessary to distribute the costs and profits as fairly as possible. Therefore, this paper quantifies the contribution degrees of each entity to the alliance and gives different bargaining factors according to their contributions to obtain more reasonable results. The bargaining factors of different entities are calculated as follows:

[0153]

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

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

[0156]

[0157] In the formula, represents the repeated part of the energy storage charging and discharging power when the complementary constraint is relaxed, and ΔC B is equivalent to an additional penalty function of the charging and discharging power part multiplied by the price coefficient. In the optimization process of minimizing the cost, the minimum value point is obtained only when .

[0158] As Figure 3 shown, it is another flowchart of a shared energy storage configuration method for flexibility mutual assistance among multiple energy microgrids. In one embodiment, the shared energy storage configuration method for flexibility mutual assistance among multiple energy microgrids operates based on the process shown in Figure 3 . On the basis of constructing the alliance model of the microgrid and the energy storage power station, in order to solve the privacy protection of multiple subjects, a two-stage optimization model based on distributed computing is established: the first stage aims at maximizing the cooperative alliance benefit, trading electricity quantity and flexibility; the second stage establishes a Nash bargaining model considering the differences in subject participation degrees and market factors, and designs an energy storage service pricing mechanism accordingly. The specific process is as follows:

[0159] The first step: Input the planning target data

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

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

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

[0163] The second step: Establish an alliance

[0164] (1) Goal setting: Aim at the optimal comprehensive cost of energy storage configuration and microgrid operation.

[0165] (2) Alliance establishment: Construct an alliance of the microgrid and the energy storage power station, define the cooperation mechanisms and rules among each subject, and clarify the roles and responsibilities of each subject in the alliance.

[0166] The third step: Iteratively solve the traded electricity quantity and the flexibility support quantity

[0167] (1) Transaction between the microgrid and the energy storage power station: Iterative solution of the transaction electricity quantity: Iteratively solve the transaction electricity quantity between the microgrid and the energy storage power station. The microgrid conducts energy exchange with the energy storage power station according to its own needs and the supply capacity of flexible resources.

[0168] (2) Iterative solution of the active support quantity of flexibility: Consider the operation timing of the energy storage within the energy storage power station to determine a reasonable over-sale quantity. Consider the demand for external electricity within the microgrid and reasonably allocate the internal flexible resources, that is, the flexibility traded with the energy storage power station and the flexibility to support internal operation.

[0169] Step 4: Iterative error calculation

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

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

[0172] (3) Enter the second stage: If the iterative error meets the convergence condition, enter the second stage, output the transaction power and the active support quantity of flexibility, and the negotiated part of the transaction electricity quantity and flexibility supply.

[0173] Step 5: Benefit-cost allocation in the second stage

[0174] (1) Input data from the first stage: Input the transaction electricity quantity and the active support quantity of flexibility obtained in the first stage into the second stage as the basic data for benefit-cost allocation.

[0175] Step 6: Calculate the bargaining power

[0176] (1) Bargaining power calculation: Calculate the bargaining power of each bargaining entity through the data in the first stage.

[0177] (2) Goal setting: Set the goal of maximizing the maximum benefit after cooperation, and iteratively solve the transaction price to ensure the maximum benefit of each entity.

[0178] Step 7: Iterative error calculation

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

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

[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 reallocated to output the final allocation result.

[0182] Through the above steps, the microgrid and energy storage power station alliance can achieve optimized operation, reduce operating costs, and ensure the maximization of the benefits of each entity in the alliance through a reasonable benefit distribution mechanism, achieving the goal of win-win cooperation.

[0183] In an exemplary embodiment, 4 microgrids and a shared energy storage operator are taken as the research entities. Three typical days in summer, winter, and the transition season are selected, with a 24-hour operation cycle for each typical day. The basic data for the typical days are shown in Table 1.

[0184] Table 1 System Parameters

[0185]

[0186] To verify the method proposed in the present invention, two operation schemes of normal operation of the shared energy storage and the adoption of the over-selling strategy are respectively set, 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 whether the shared energy storage is over-sold, its rated capacity has decreased by 6133.81 kW·h, with a decrease rate of 25.35%. The rated power has decreased by 387.81 kW, with a decrease rate of 11.21%. At the same time, the configured cost of the energy storage after conversion has decreased by 1353.95, with a decrease rate of 24.26%. After the shared energy storage adopts the over-selling strategy, although the planned capacity and power are reduced, more fees for purchasing flexibility need to be paid in the secondary market of flexible trading. Therefore, the decrease rate of the total cost of the alliance is not as large as that of the energy storage planning cost, only 3.69%. It can be seen that in the planning and operation stage, by adjusting the capacity and power configuration of the energy storage through over-selling, the planning cost can be effectively reduced, and the comprehensive system benefit increases.

[0191] The energy storage power station reduces the configuration of the rated capacity and rated power through over-selling operation. During the process of the energy storage interacting with the microgrid, the charge and discharge power and capacity curves of the shared energy storage are as Figure 4 shown. The typical days are winter, summer, and the transition season. The 1-24 hours in the figure represent the winter typical day, the 25-48 hours represent the summer typical day, and the 49-72 moments represent the transition season, which are marked in the figure.

[0192] Figure 4The black solid line represents the upper and lower limits of the energy storage capacity. The maximum over-selling operation of the shared energy storage occurs on a typical summer day, where the maximum over-selling capacity reaches 5324.99 kW·h. When the energy storage reaches its maximum capacity, the actual charging and discharging power of the energy storage becomes zero through the flexibility supply of the microgrid (as shown at times 30 - 33 in the figure). When the energy storage reaches its minimum rated capacity, it purchases the flexibility of the microgrid from 13:00 to 15:00 to make the actual discharge of the energy storage power station zero. From 13:00 to 18:00, the over-selling capacity state of the energy storage exceeds the minimum capacity limit, causing over-selling. After the energy storage adopts the over-selling strategy, the minimum capacity of the energy storage reaches a negative value because the over-selling capacity does not correspond to the actual energy storage capacity. Generally speaking, the overall change trend of the over-selling capacity of the energy storage is similar to the actual capacity state of the energy storage. In the secondary flexibility market transaction, the total amount of flexibility purchased by the energy storage from the microgrid is 123198.49 kW·h. When adopting the over-selling strategy, the energy storage does not purchase flexibility from the microgrid when the capacity is insufficient but purchases flexibility from the microgrid in advance. Therefore, the rising and falling rates of the over-selling capacity of the energy storage are significantly higher than the rising and falling rates 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 part of the over-selling capacity power default when the capacity is insufficient, the capacity state of the energy storage will reach the capacity limit earlier, making it difficult for the energy storage to continue to provide services. Moreover, the over-selling capacity of the energy storage is also restricted by the maximum flexibility that the microgrid can provide to the energy storage at this time, resulting in a smaller over-selling capacity that the energy storage can achieve and making it difficult to obtain more profits.

[0193] The adoption of different over-selling strategies by the shared energy storage also affects the energy storage configuration and the benefits of the alliance. In this paper, different over-selling ratio schemes are selected for comparison, and the results are as follows:

[0194] Scenario 1: The minimum over-selling capacity is 5%S max The maximum over-selling capacity is 100%S max 。

[0195] Scenario 2: The minimum over-selling capacity is -5%S max The maximum over-selling capacity is 120%S max 。

[0196] Scenario 3: The minimum over-selling capacity is -10%S max The maximum over-selling capacity is 190%S max 。

[0197] Scenario 4: The selected optimal over-selling capacity: The minimum over-selling capacity is -11.37%S max The maximum over-selling capacity is 126.25%S max 。

[0198] Table 3 Comparison of energy storage planning results

[0199]

[0200] As can be seen from the comparison table 3, the energy storage configuration costs of Scenarios 1-4 decreased by 12.12%, 6.69% and 14.99% respectively compared with that of Scenario 4, and the overall costs of the alliance decreased by 526.27, 343.29 and 168.58 respectively. The energy storage oversold capacities found in this embodiment all have the lowest alliance cost, the lowest energy storage rated capacity and configuration cost. Adopting different energy storage overselling strategies can have a greater impact on the size of the energy storage rated capacity and the energy storage configuration cost.

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

[0202] After the alliance completes the configuration and operation of the energy storage in the first stage, the second stage is to distribute the benefits of each subject of the alliance. 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 the energy storage transaction and increasing the arbitrage space of the energy storage power station. The energy transaction price after bargaining is as Figure 5 shown.

[0203] The transaction price between the microgrid and the shared energy storage is determined through bargaining. The energy storage can arbitrage through the price to make itself profitable. For the flexible market trading volume, the energy storage side is the buyer and each microgrid is the seller. Therefore, for the flexible secondary market trading, regardless of the situation of the energy storage buying and selling electricity, the energy storage power station is the beneficiary. Before and after the cost-benefit distribution, the cost changes of the microgrid and the energy storage are shown in Table 4.

[0204] Table 4 Microgrid and Energy Storage Costs

[0205]

[0206] In this embodiment, the uncooperative scenario is set as the independent operation of the microgrid. When its own adjustment ability is insufficient, it purchases and sells electricity with the main grid, and the construction cost of the energy storage power station is 0. The revenues of each entity before and after participating in the cooperation are also different. The cost of Microgrid A decreases by 5,464.69 yuan, with a decrease rate of 16.97%. The cost of Microgrid B decreases by 3,285.42 yuan, with a decrease rate of 8.10%. The cost of Microgrid C has the largest decrease rate and realizes a profit. The reason is that Microgrid C is a microgrid with a very high renewable energy penetration rate. It is difficult for itself to absorb so much wind power, resulting in a relatively high curtailment cost. After participating in the alliance, it can sell more surplus electricity and make a greater contribution to the alliance. Through bargaining, the cost of energy storage is transferred to the microgrid, realizing the profit of the energy storage power station. At the same time, the costs of each microgrid are also significantly reduced compared with before the cooperation, and the overall cost of the alliance is reduced by 18.66%. Therefore, through bargaining, each entity can obtain a more reasonable benefit distribution.

[0207] Aiming at the problem of insufficient flexibility caused by the actual operation status of shared energy storage, this embodiment can effectively affect the planning and operation cost of energy storage by establishing a cooperation alliance for the over-sale operation of shared energy storage and the active support of microgrid flexibility, and has the following advantages:

[0208] 1) By establishing an alliance between the energy storage and the microgrid, the operation cost of the microgrid and the planning cost of the energy storage can be effectively reduced. Through case simulation, it is found that when the energy storage adopts the over-sale strategy and establishes a flexibility market, the configured capacity and power of the energy storage are 18,067.25 kW·h and 3,072.78 kW respectively. Compared with the scheme where the energy storage fully responds to the microgrid demand, the reduction rates of the energy storage capacity and power are 25.35% and 24.26% respectively.

[0209] 2) For the microgrid, by participating in the flexibility market, it absorbs the over-sold power of the energy storage. It improves the enthusiasm of flexibility resources to participate in market transactions, reduces its operation cost, and after the secondary distribution of interest costs, the total cost of all microgrids decreases by 15.29%. For the energy storage power station, due to paying for the flexibility trading volume, part of the operation cost increases. In the long run, it reduces the redundant energy storage configuration and the configuration cost. Establishing an alliance between the microgrid and the energy storage power station obtains excess benefits and realizes win-win cooperation.

[0210] 3) Construct a Nash bargaining model based on the value contribution degree to reasonably allocate the total cost and cooperation revenue of the alliance. The higher the contribution degree of the microgrid, the higher the net revenue obtained from the distribution, effectively stimulating the enthusiasm of each microgrid in the alliance to participate in power interaction and flexibility supply. The shared energy storage and some microgrids with a relatively high renewable energy penetration rate realize profits, with profits of 4,509.81 yuan and 660.80 yuan respectively.

[0211] The embodiment of the present invention also provides a shared energy storage configuration device for flexibility mutual assistance among multi-energy microgrids, and the device includes:

[0212] A data acquisition module, configured to acquire planned target data, where the planned target data includes renewable energy power generation capacity data of each microgrid, power consumption 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 capacities and expected power generation amounts of wind power and photovoltaic power, and the configuration parameters of the conventional power sources include installed capacities and operating parameters of power generation equipment;

[0213] A model construction module, configured to construct a coalition model of a microgrid and an energy storage power station with the goal of the overall cost optimal for energy storage configuration and microgrid operation;

[0214] A first solution module, configured to iteratively solve trading electricity quantities and flexibility support quantities based on the coalition model;

[0215] A second solution module, configured to calculate the bargaining power of each entity in the coalition model based on the trading electricity quantities and flexibility support quantities, calculate the costs and benefits of each microgrid with the goal of exceeding the maximum benefit before cooperation, and output the energy storage configuration result and the microgrid interaction power.

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

[0217] An embodiment of the present invention further provides a readable storage medium, where the readable storage medium stores one or more programs, and 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 having equivalent elements, modifications, omissions, combinations (e.g., schemes of cross - combination of various embodiments), adaptations, or alterations. The elements in the claims will be broadly interpreted based on the language employed in the claims and are not limited to the examples described in the present specification or during the implementation of the present application, and the examples will be interpreted as non - exclusive. Therefore, the present specification and examples are intended to be considered only as examples, and the true scope and spirit are indicated by the full scope of the following claims and 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; Calculate the bargaining power of each subject 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; 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, represents the maximum value of the reduced heat load of microgrid i at time t; 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 subproblem; 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.

2. The method according to claim 1, 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:

3. The method according to claim 1, 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; λ t f , 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.

4. The method according to claim 3, 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.

5. The method according to claim 1, 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; C i o 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.

6. The method according to claim 1, 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, ΔP t B 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 charge and discharge portion multiplied by the price coefficient. In the optimization process of minimizing the cost, only when ΔP t B =0 when it reaches the minimum value.

7. 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 subject 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; 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, represents the maximum value of the reduced heat load of microgrid i at time t; 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 subproblem; 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. 8 . A non-transitory computer-readable storage medium storing instructions, which, when executed by a processor, executes the method according to claim 1 .

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