Micro-grid group energy storage capacity optimal configuration method and device

Abstract

The invention relates to a micro-grid group energy storage capacity optimal configuration method and device, and the method comprises the steps: constructing a micro-grid group electric energy balance rule corresponding to a target micro-grid group; determining a target function corresponding to the total operation cost of the target micro-grid group within one day, and establishing a plurality of optimal configuration constraint conditions corresponding to the target micro-grid group based on the operation characteristics of the target micro-grid group; and based on the target function and the plurality of optimal configuration constraint conditions, constructing an energy storage capacity optimal configuration model corresponding to the target micro-grid group, solving the energy storage capacity optimal configuration model to obtain an energy storage capacity configuration result, and performing optimal configuration on the energy storage capacity of the target micro-grid group according to the energy storage capacity configuration result. Therefore, the problems that most of existing micro-grid group energy storage capacity optimization configuration technologies focus on single energy storage application value, complementary characteristics of energy storage of all sub micro-grids are not fully utilized, and the potential of energy storage in the aspect of improving comprehensive benefits of the micro-grid group is limited are solved.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage optimization configuration, and in particular to a method and device for optimizing configuration of energy storage capacity of a microgrid group. Background Art

[0002] In recent years, with the rapid development of distributed energy technology, microgrid groups composed of multiple microgrids are gradually becoming a key link in accessing the upper power grid as an important form of efficient use of renewable energy. However, due to the uncertainty of wind and solar power generation within each sub-microgrid, the balance of power supply and demand in the microgrid group faces huge challenges. As a device with flexible access location and rapid two-way regulation response, energy storage fully plays its unique power compensation role, giving the system higher flexibility and regulation capabilities. Therefore, the reasonable configuration of energy storage capacity in the microgrid group is crucial.

[0003] The optimal configuration of energy storage capacity in a microgrid group refers to giving full play to the complementary advantages of energy storage in each sub-microgrid through refined management strategies. It is necessary not only to consider the operating economy of the microgrid group, but also to deeply explore the various constraints in the energy storage capacity configuration process, such as the charging and discharging power of energy storage equipment, capacity limitations, etc., to ensure the feasibility and practicality of the configuration plan.

[0004] However, most of the existing microgrid group energy storage capacity optimization configuration technologies focus on the application value of a single energy storage, and do not fully utilize the complementary characteristics of each sub-microgrid energy storage, which limits the potential of energy storage in improving the comprehensive benefits of microgrid groups and needs to be urgently addressed. Summary of the invention

[0005] The present application provides a method and device for optimizing the configuration of energy storage capacity of a microgrid group, in order to solve the problems that the existing technologies for optimizing the configuration of energy storage capacity of a microgrid group mostly focus on the application value of a single energy storage, do not fully utilize the complementary characteristics of the energy storage of each sub-microgrid, and limit the potential of energy storage in improving the comprehensive benefits of the microgrid group.

[0006] The first aspect of the present application provides a method for optimizing the configuration of energy storage capacity of a microgrid group, comprising the following steps: constructing a microgrid group power balance rule corresponding to a target microgrid group; determining an objective function corresponding to the total operating cost of the target microgrid group within one day, and establishing multiple optimization configuration constraints corresponding to the target microgrid group based on the operating characteristics of the target microgrid group; constructing an energy storage capacity optimization configuration model corresponding to the target microgrid group based on the objective function and the multiple optimization configuration constraints, and solving the energy storage capacity optimization configuration model to obtain an energy storage capacity configuration result, and optimizing the energy storage capacity of the target microgrid group according to the energy storage capacity configuration result.

[0007] Optionally, in one embodiment of the present application, the electric energy balancing rule of the microgrid group includes: judging whether there is a power-deficient sub-microgrid that meets a preset power-deficient condition or a power-redundant sub-microgrid that meets a preset power-redundant condition in the target microgrid group; if there is a power-deficient sub-microgrid that meets the preset power-deficient condition in the target microgrid group, controlling the adjacent sub-microgrid of the power-deficient sub-microgrid to transmit power to the power-deficient sub-microgrid, and judging whether the power-deficient sub-microgrid after the power transmission meets the preset power balancing requirement, wherein, when the power-deficient sub-microgrid does not meet the preset power balancing requirement, the power-deficient sub-microgrid is controlled by the adjacent sub-microgrid to transmit power to the power-deficient sub-microgrid. The power-deficient sub-microgrid purchases electricity from the target power grid until the power-deficient sub-microgrid meets the preset power balance requirement; if there is a power redundant sub-microgrid that meets the preset power redundancy condition in the target microgrid group, power is transmitted to the adjacent sub-microgrid of the power redundant sub-microgrid through the power redundant sub-microgrid, and it is determined whether the power redundant sub-microgrid after the power transmission meets the preset power balance requirement, wherein, when the power redundant sub-microgrid does not meet the preset power balance requirement, electricity is sold to the target power grid through the power redundant sub-microgrid until the power redundant sub-microgrid meets the preset power balance requirement.

[0008] Optionally, in one embodiment of the present application, the objective function corresponding to the total operating cost of the target microgrid group within one day includes: calculating the renewal replacement cost and the residual recovery value of the target energy storage equipment; determining the unit investment cost of the energy storage capacity, the unit investment cost of the energy storage power, the energy storage rated capacity and the energy storage rated power of each sub-microgrid in the target microgrid group; calculating the target microgrid group according to the renewal replacement cost, the residual recovery value, the unit investment cost of the energy storage capacity, the unit investment cost of the energy storage power, the energy storage rated capacity and the energy storage rated power. Energy storage investment and construction cost; based on the energy storage unit operation and maintenance cost and DG unit operation and maintenance cost of each sub-microgrid, respectively calculate the energy storage operation and maintenance cost and wind and solar operation and maintenance cost of the target microgrid group; calculate the power purchase cost, power transmission cost between sub-microgrids, peak shaving and valley filling benefits and low-carbon benefits of the target microgrid group; construct the objective function of the energy storage capacity optimization configuration model based on the energy storage investment and construction cost, energy storage operation and maintenance cost, wind and solar operation and maintenance cost, power purchase cost, power transmission cost between sub-microgrids, peak shaving and valley filling benefits, low-carbon benefits, preset prediction error penalty and fluctuation penalty.

[0009] Optionally, in one embodiment of the present application, based on the operating characteristics of the target microgrid group, multiple optimization configuration constraints corresponding to the target microgrid group are established, including: determining the tie line power, distributed power output, energy storage discharge power, energy storage charging power and load power of the target microgrid group, so as to establish a power balance constraint among the multiple optimization configuration constraints according to the tie line power, the distributed power output, the energy storage discharge power, the energy storage charging power and the load power; obtaining the distributed power theoretical output, tie line power limit and energy storage rated capacity of the target microgrid group, so as to determine the distributed power output constraint, tie line power constraint, energy storage charging and discharging state constraint, energy storage power output constraint, energy storage capacity constraint, energy storage SOC constraint, energy storage charging and discharging time constraint and inter-microgrid power transmission constraint among the multiple optimization configuration constraints based on the distributed power theoretical output, the tie line power limit and the energy storage rated capacity.

[0010] Optionally, in one embodiment of the present application, solving the energy storage capacity optimization configuration model to obtain an energy storage capacity configuration result includes: converting the energy storage capacity optimization configuration model into a linear model, and solving the linear model through a preset Gurobi solver to obtain the energy storage capacity configuration result, wherein the energy storage capacity configuration result includes a target energy storage power capacity and a target energy storage rated capacity corresponding to the target microgrid group.

[0011] The second aspect of the present application provides a device for optimizing the configuration of energy storage capacity of a microgrid group, including: a rule module, used to construct a microgrid group power balance rule corresponding to a target microgrid group; an establishment module, used to determine the objective function corresponding to the total operating cost of the target microgrid group within one day, and based on the operating characteristics of the target microgrid group, establish multiple optimization configuration constraints corresponding to the target microgrid group; an optimization configuration module, used to construct an energy storage capacity optimization configuration model corresponding to the target microgrid group based on the objective function and the multiple optimization configuration constraints, and solve the energy storage capacity optimization configuration model to obtain an energy storage capacity configuration result, and optimize the energy storage capacity of the target microgrid group according to the energy storage capacity configuration result.

[0012] Optionally, in one embodiment of the present application, the rule module includes: a judgment unit, used to judge whether there is a power-deficient sub-microgrid that meets a preset power deficiency condition or a power-redundant sub-microgrid that meets a preset power redundancy condition in the target microgrid group; a power-deficient unit, used to control the adjacent sub-microgrid of the power-deficient sub-microgrid to transfer power to the power-deficient sub-microgrid if there is a power-deficient sub-microgrid that meets the preset power deficiency condition in the target microgrid group, and judge whether the power-deficient sub-microgrid after the power transmission meets the preset power balance requirement, wherein, when the power-deficient sub-microgrid does not meet the preset power balance requirement, the power-deficient sub-microgrid is controlled by the adjacent sub-microgrid of the power-deficient sub-microgrid to transfer power to the power-deficient sub-microgrid. The power-deficient sub-microgrid purchases electricity from the target power grid until the power-deficient sub-microgrid meets the preset power balance requirement; a power redundancy unit is used to transmit power to an adjacent sub-microgrid of the power redundant sub-microgrid through the power redundant sub-microgrid if there is a power redundant sub-microgrid that meets the preset power redundancy condition in the target microgrid group, and determine whether the power redundant sub-microgrid after the power transmission meets the preset power balance requirement, wherein, when the power redundant sub-microgrid does not meet the preset power balance requirement, sell electricity to the target power grid through the power redundant sub-microgrid until the power redundant sub-microgrid meets the preset power balance requirement.

[0013] Optionally, in one embodiment of the present application, the establishment module includes: a first calculation unit, used to calculate the renewal replacement cost and the residual recovery value of the target energy storage equipment; a first determination unit, used to determine the unit investment cost of the energy storage capacity, the unit investment cost of the energy storage power, the energy storage rated capacity and the energy storage rated power of each sub-microgrid in the target microgrid group; a second calculation unit, used to calculate the energy storage investment and construction cost of the target microgrid group based on the renewal replacement cost, the residual recovery value, the unit investment cost of the energy storage capacity, the unit investment cost of the energy storage power, the energy storage rated capacity and the energy storage rated power; The third calculation unit is used to calculate the energy storage operation and maintenance cost and wind and solar operation and maintenance cost of the target microgrid group based on the energy storage unit operation and maintenance cost and DG unit operation and maintenance cost of each sub-microgrid; the fourth calculation unit is used to calculate the power purchase cost, power transmission cost between sub-microgrids, peak shaving and valley filling benefits and low-carbon benefits of the target microgrid group; the construction unit is used to construct the objective function of the energy storage capacity optimization configuration model according to the energy storage investment and construction cost, energy storage operation and maintenance cost, wind and solar operation and maintenance cost, power purchase cost, power transmission cost between sub-microgrids, peak shaving and valley filling benefits, low-carbon benefits, preset prediction error penalty and fluctuation penalty.

[0014] Optionally, in one embodiment of the present application, the establishment module also includes: a second determination unit, used to determine the tie line power, distributed power output, energy storage discharge power, energy storage charging power and load power of the target microgrid group, so as to establish the power balance constraint among the multiple optimization configuration constraints according to the tie line power, the distributed power output, the energy storage discharge power, the energy storage charging power and the load power; an acquisition unit, used to obtain the distributed power theoretical output, tie line power limit and energy storage rated capacity of the target microgrid group, so as to determine the distributed power output constraint, tie line power constraint, energy storage charging and discharging state constraint, energy storage power output constraint, energy storage capacity constraint, energy storage SOC constraint, energy storage charging and discharging time constraint and inter-microgrid power transmission constraint among the multiple optimization configuration constraints based on the distributed power theoretical output, the tie line power limit and the energy storage rated capacity.

[0015] Optionally, in one embodiment of the present application, the optimization configuration module includes: a solving unit, used to convert the energy storage capacity optimization configuration model into a linear model, and solve the linear model through a preset Gurobi solver to obtain the energy storage capacity configuration result, wherein the energy storage capacity configuration result includes the target energy storage power capacity and the target energy storage rated capacity corresponding to the target microgrid group.

[0016] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for optimizing the configuration of energy storage capacity of a microgrid group as described in the above embodiment.

[0017] The fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program. When the program is executed by a processor, it implements the above-mentioned method for optimizing the configuration of energy storage capacity of a microgrid group.

[0018] The fifth aspect of the present application provides a computer program product, including a computer program, which is executed to implement the above-mentioned method for optimizing the configuration of energy storage capacity of a microgrid group.

[0019] Therefore, the embodiments of the present application have the following beneficial effects:

[0020] The embodiments of the present application can be implemented by constructing a microgrid group power balance rule corresponding to the target microgrid group; determining the objective function corresponding to the total operating cost of the target microgrid group within one day, and establishing multiple optimization configuration constraints corresponding to the target microgrid group based on the operating characteristics of the target microgrid group; constructing an energy storage capacity optimization configuration model corresponding to the target microgrid group based on the objective function and multiple optimization configuration constraints, and solving the energy storage capacity optimization configuration model to obtain the energy storage capacity configuration result, and optimizing the energy storage capacity of the target microgrid group according to the energy storage capacity configuration result. The present application can effectively reduce the operating cost of the microgrid group by determining the power capacity and rated capacity of the energy storage, thereby improving the system economy. As a result, the existing microgrid group energy storage capacity optimization configuration technology is solved, which mostly focuses on the application value of a single energy storage, does not fully utilize the complementary characteristics of each sub-microgrid energy storage, and limits the potential of energy storage in improving the comprehensive benefits of the microgrid group.

[0021] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0023] Figure 1 A flowchart of a method for optimizing energy storage capacity configuration of a microgrid group provided according to an embodiment of the present application;

[0024] Figure 2 A schematic diagram of the structure of a microgrid group provided for one embodiment of the present application;

[0025] Figure 3 A block diagram of an energy storage capacity optimization configuration model provided for an embodiment of the present application;

[0026] Figure 4 This is an example diagram of a device for optimizing and configuring energy storage capacity of a microgrid group according to an embodiment of the present application;

[0027] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0028] Among them, 10-microgrid group energy storage capacity optimization configuration device; 100-rule module, 200-establishment module, 300-optimization configuration module; 501-memory, 502-processor, 503-communication interface. DETAILED DESCRIPTION

[0029] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0030] The following describes the method and device for optimizing the energy storage capacity configuration of a microgrid group according to an embodiment of the present application with reference to the accompanying drawings. In view of the problems mentioned in the above background technology, the present application provides a method for optimizing the energy storage capacity configuration of a microgrid group, in which a microgrid group power balance rule corresponding to a target microgrid group is constructed; an objective function corresponding to the total operating cost of the target microgrid group within one day is determined, and multiple optimization configuration constraints corresponding to the target microgrid group are established based on the operating characteristics of the target microgrid group; based on the objective function and multiple optimization configuration constraints, an energy storage capacity optimization configuration model corresponding to the target microgrid group is constructed, and the energy storage capacity optimization configuration model is solved to obtain the energy storage capacity configuration result, and the energy storage capacity of the target microgrid group is optimized according to the energy storage capacity configuration result. The present application can effectively reduce the operating cost of the microgrid group by determining the power capacity and rated capacity of the energy storage, thereby improving the system economy. As a result, the existing microgrid group energy storage capacity optimization configuration technology is solved, and the problems such as the focus of the existing microgrid group energy storage capacity optimization configuration technology on the application value of a single energy storage is mostly solved, and the complementary characteristics of the energy storage of each sub-microgrid are not fully utilized, which limits the potential of energy storage in improving the comprehensive benefits of the microgrid group.

[0031] Specifically, Figure 1 A flowchart of a method for optimizing energy storage capacity configuration of a microgrid group provided in an embodiment of the present application.

[0032] like Figure 1 As shown, the method for optimizing the configuration of energy storage capacity of a microgrid group includes the following steps:

[0033] In step S101, a microgrid group power balance rule corresponding to the target microgrid group is constructed.

[0034] The embodiment of the present application first takes the formation of a microgrid group by multiple microgrids and access to a superior power grid as the background, and considers the overall economic efficiency of the microgrid group, thereby establishing an energy balance rule within the microgrid group.

[0035] Optionally, in one embodiment of the present application, the microgrid group power balance rule includes: determining whether there is a power-deficient sub-microgrid that meets a preset power-deficient condition or a power-redundant sub-microgrid that meets a preset power-redundant condition in the target microgrid group; if there is a power-deficient sub-microgrid that meets the preset power-deficient condition in the target microgrid group, controlling the adjacent sub-microgrid of the power-deficient sub-microgrid to transfer power to the power-deficient sub-microgrid, and determining whether the power-deficient sub-microgrid after the power transfer meets the preset power balance requirement, wherein, when the power-deficient sub-microgrid does not meet the preset power balance requirement, the power-deficient sub-microgrid purchases electricity from the target grid until the power-deficient sub-microgrid meets the preset power balance requirement; if there is a power-redundant sub-microgrid that meets the preset power-redundant condition in the target microgrid group, transferring power to the adjacent sub-microgrid of the power-deficient sub-microgrid through the power-redundant sub-microgrid, and determining whether the power-deficient sub-microgrid after the power transfer meets the preset power balance requirement, wherein, when the power-deficient sub-microgrid does not meet the preset power balance requirement, the power-deficient sub-microgrid sells electricity to the target grid until the power-deficient sub-microgrid meets the preset power balance requirement.

[0036] In the embodiments of the present application, Figure 2 As shown in the figure, the microgrid group system includes three sub-microgrids. Each sub-microgrid has a connecting line switch with the external power grid. Each sub-microgrid contains wind turbines, photovoltaics, energy storage and loads. Power interaction can be carried out between the sub-microgrids to form a microgrid group connected to the external power grid, and shared energy storage is configured in the system to take into account the complementarity of energy storage charging and discharging needs.

[0037] It should be noted that the power balance rule within the microgrid group means that when there is power loss or power redundancy in a sub-microgrid, the microgrid group achieves power balance of each sub-microgrid within the microgrid group through flexible switching among off-grid operation, partial grid-connected operation and grid-connected operation modes.

[0038] Among them, the power balance in the case of power loss in a sub-microgrid is specifically as follows: when there is a power loss in a sub-microgrid within a microgrid group, power is transmitted from the adjacent sub-microgrid first. If power balance cannot be achieved (that is, the preset power balance requirements cannot be met), then choose to purchase electricity from the power grid.

[0039] The specific energy balance under the condition of power redundancy within a sub-microgrid is as follows: when there is power redundancy among sub-microgrids within a microgrid group, power is transmitted to adjacent sub-microgrids first. If power balance cannot be achieved, electricity is sold to the grid.

[0040] Therefore, the embodiments of the present application provide reliable data and technical support for the implementation of optimal configuration of energy storage capacity of the microgrid group by constructing a microgrid group power balance rule corresponding to the target microgrid group.

[0041] In step S102, an objective function corresponding to the total operating cost of the target microgrid group in one day is determined, and based on the operating characteristics of the target microgrid group, a plurality of optimization configuration constraints corresponding to the target microgrid group are established.

[0042] Furthermore, the embodiments of the present application also need to start from the operating economy of the microgrid group, with the goal of minimizing the total operating cost of the target microgrid group system within one day, and establish the objective function of the energy storage capacity optimization configuration model; at the same time, the embodiments of the present application also need to consider the operating characteristics of the microgrid group, so as to establish multiple optimization configuration constraints of the energy storage capacity optimization configuration model.

[0043] Optionally, in one embodiment of the present application, determining the objective function corresponding to the total operating cost of the target microgrid group within one day includes: calculating the renewal replacement cost and residual recovery value of the target energy storage equipment; determining the unit investment cost of energy storage capacity, unit investment cost of energy storage power, energy storage rated capacity and energy storage rated power of each sub-microgrid in the target microgrid group; calculating the energy storage investment and construction cost of the target microgrid group based on the renewal replacement cost, residual recovery value, unit investment cost of energy storage capacity, unit investment cost of energy storage power, energy storage rated capacity and energy storage rated power; calculating the energy storage operation and maintenance cost and wind and solar operation and maintenance cost of the target microgrid group based on the energy storage unit operation and maintenance cost and DG unit operation and maintenance cost of each sub-microgrid; calculating the electricity purchase cost, electricity transmission cost between sub-microgrids, peak shaving and valley filling benefits and low-carbon benefits of the target microgrid group; constructing the objective function of the energy storage capacity optimization configuration model based on the energy storage investment and construction cost, energy storage operation and maintenance cost, wind and solar operation and maintenance cost, electricity purchase cost, electricity transmission cost between sub-microgrids, peak shaving and valley filling benefits, low-carbon benefits, preset prediction error penalty and fluctuation penalty.

[0044] It should be noted that the embodiments of the present application need to determine the energy storage investment and construction cost, energy storage operation and maintenance cost, wind and solar operation and maintenance cost, wind and solar loss, electricity purchase cost, power transmission cost between sub-microgrids, prediction error penalty, fluctuation penalty, peak shaving and valley filling benefits and low-carbon benefits, so as to construct the objective function of the energy storage capacity optimization configuration model, as described below.

[0045] (1) The investment and construction cost of energy storage is:

[0046]

[0047] Among them, C 1,i is the unit investment cost of the energy storage capacity of the i-th microgrid; C 2,i is the unit investment cost of energy storage power of the i-th microgrid; E i is the rated capacity of energy storage of the i-th microgrid; is the rated power of the energy storage of the i-th microgrid; C replaceis the replacement cost of energy storage equipment; C recycle It is the residual recovery value of the energy storage equipment.

[0048] The replacement cost of energy storage equipment is:

[0049] C replace =(1-r) kT C Inv,ESS (2)

[0050] Where k is the number of times the battery is replaced; T is the battery energy storage life cycle; C Inv,ESS It is the initial investment cost. If the project cycle is short, the full life cycle cost in the planning period does not take into account the renewal and replacement costs.

[0051] The residual recovery value of the energy storage equipment is:

[0052] C recycle =c res C Inv,ESS (3)

[0053] Among them, c res is a fixed recovery factor.

[0054] (2) The energy storage operation and maintenance cost is as follows:

[0055]

[0056] Among them, C OM,i is the unit operation and maintenance cost of the i-th microgrid energy storage.

[0057] (3) The mathematical expression of wind and solar operation and maintenance cost is:

[0058]

[0059] Among them, C DG,i is the unit operation and maintenance cost of the i-th sub-microgrid DG.

[0060] (4) The mathematical expression of wind and solar power loss is:

[0061]

[0062] Among them, c loss_pv is the unit photovoltaic loss cost; c loss_wt is the unit wind power loss cost; P PVcut,i is the photovoltaic power loss of the i-th microgrid; P WTcut,i is the wind power loss power of the i-th microgrid.

[0063] (5) The mathematical expression of electricity purchase cost is:

[0064]

[0065] Among them, C in is the electricity price that the microgrid group purchases from the grid; C out P is the electricity price sold by the microgrid group to the grid; in,i is the power absorbed by the ith microgrid from the grid; P out,i is the power emitted by the ith microgrid to the grid.

[0066] (6) The mathematical expression of the power transmission cost between sub-microgrids is:

[0067]

[0068] Among them, c MG P is the unit power transmission cost between microgrids; MGs It is the power transmission between microgrids.

[0069] (7) The mathematical expression of the prediction error penalty is:

[0070]

[0071] Among them, c error is the prediction error penalty coefficient; is the photovoltaic prediction error penalty power of the i-th sub-microgrid; is the wind power prediction error penalty power of the i-th microgrid.

[0072] (8) The mathematical expression of volatility penalty is:

[0073]

[0074] Among them, P line,t is the interconnection line power.

[0075] (9) The mathematical expression of peak shaving and valley filling benefits is:

[0076]

[0077] Among them, c pl is the peak shaving and valley filling benefit coefficient; c g,t Time-of-use electricity price; is the energy storage discharge power; is the energy storage discharge power; u d,t u is the variable for starting the energy storage discharge operation, which is a 0-1 variable; c,t This is the variable that starts the energy storage discharge operation, which is a 0-1 variable.

[0078] (10) The mathematical expression of low-carbon benefits is:

[0079]

[0080] Among them, the carbon emission coefficient K c =0.364kg / kWh.

[0081] Afterwards, the embodiment of the present application can establish the objective function of the energy storage capacity optimization configuration model according to the above parameters such as the energy storage investment and construction cost, as shown in the following formula:

[0082] min C inv +C OM +C DG +C LOSS +C grid +C MGs +C error +C wave -F pl -F c (13)

[0083] Among them, C inv C is the energy storage investment and construction cost; OM is the energy storage operation and maintenance cost; C DG is the wind and solar operation and maintenance cost; C LOSS is the loss of wind and solar power; C grid The cost of purchasing electricity; MGs is the cost of power transmission between sub-microgrids; C error is the prediction error penalty; C wave is the volatility penalty; F pl To reduce the peak and fill the valley benefits; c For low carbon benefits.

[0084] Based on the above objective function, the embodiment of the present application can use the Shapley value method to solve the problem of allocating the shared energy storage configuration cost among multiple microgrids, that is, the embodiment of the present application uses the microgrid MG i The benefits shared from the overall benefit (i.e. the cost savings from building shared energy storage) are as follows:

[0085]

[0086] Where v(S) is MG i The benefits generated by the entire alliance S when participating in the alliance S; v(S\{i}) is the benefit of removing the microgrid MG i The benefits generated by the alliance S; v(S)-v(S\{i}) represents the microgrid MG i The marginal contribution created by S for itself and the alliance by participating in different alliances.

[0087] Therefore, the embodiment of the present application aims to minimize the total operating cost of the target microgrid group system in one day to construct the objective function of the energy storage capacity optimization configuration model, thereby ensuring the reliability of the objective function.

[0088] Optionally, in one embodiment of the present application, based on the operating characteristics of the target microgrid group, multiple optimization configuration constraints corresponding to the target microgrid group are established, including: determining the interconnection line power, distributed power output, energy storage discharge power, energy storage charging power and load power of the target microgrid group, so as to establish a power balance constraint among the multiple optimization configuration constraints according to the interconnection line power, distributed power output, energy storage discharge power, energy storage charging power and load power; obtaining the distributed power theoretical output, interconnection line power limit and energy storage rated capacity of the target microgrid group, so as to determine the distributed power output constraint, interconnection line power constraint, energy storage charging and discharging state constraint, energy storage power output constraint, energy storage capacity constraint, energy storage SOC constraint, energy storage charging and discharging time constraint and power transmission constraint between microgrids among the multiple optimization configuration constraints based on the distributed power theoretical output, interconnection line power limit and energy storage rated capacity.

[0089] In the actual implementation process, the embodiment of the present application can establish multiple optimization configuration constraints of the energy storage capacity optimization configuration model based on the operating characteristics of the microgrid group. The specific optimization configuration constraints are as follows:

[0090] (1) The mathematical expression of the power balance constraint is:

[0091]

[0092] Among them, P g is the tie line power; Provide distributed power generation; is the energy storage discharge power; Charging power for energy storage; is the load power.

[0093] (2) The mathematical expression of the distributed generation output constraint is:

[0094]

[0095] in, Contribute to the theory of distributed power supply.

[0096] (3) The mathematical expression of the tie line power constraint is:

[0097]

[0098] Among them, P line_limit,t It is the power limit of the tie line.

[0099] (4) The mathematical expression of energy storage charge and discharge state constraint is:

[0100]

[0101] in, It is the variable for starting the energy storage discharge operation, which is a 0-1 variable; The variable for starting the energy storage charging operation is a 0-1 variable.

[0102] (5) The mathematical expression of energy storage power output constraint is:

[0103]

[0104] in, is the minimum value of energy storage discharge power; is the maximum value of energy storage discharge power; It is the minimum value of energy storage charging power; It is the maximum value of energy storage charging power.

[0105] (6) The mathematical expression of energy storage capacity constraint is:

[0106]

[0107] in, is the energy storage capacity at time t; is the energy storage capacity at time t+1; is the minimum value of energy storage capacity; The maximum value of energy storage capacity.

[0108] (7) The mathematical expression of energy storage SOC constraint is:

[0109]

[0110] Among them, SOC j,t SOC is the state of charge of the energy storage at time t; min SOC is the minimum state of charge for energy storage. max is the maximum state of charge of energy storage; E j is the rated capacity of energy storage; Charging efficiency for energy storage; is the discharge efficiency of energy storage; SOC j,0 SOC is the state of charge of the energy storage at time 0; j,24 is the charge state of the energy storage at time 24; Δτ is the state duration at time t.

[0111] (8) The mathematical expression of energy storage charging and discharging time constraint is:

[0112]

[0113] in, is the rated capacity of energy storage.

[0114] (9) The inter-microgrid power transmission constraints include the following two forms of constraints:

[0115] 1) State constraint: Two microgrids cannot purchase and sell electricity at the same time, as shown in the following formula:

[0116]

[0117] in, It is the variable for starting the microgrid electricity purchase operation, which is a 0-1 variable; It is the variable for starting the microgrid electricity selling operation, which is a 0-1 variable.

[0118] 2) Power constraint: The sub-microgrid should first satisfy power autonomy before considering selling electricity to avoid ineffective power flow, as shown in the following formula:

[0119] P MGs ≤P PV +P Wind -P Load (twenty four)

[0120] Therefore, the embodiments of the present application establish multiple optimization configuration constraints of the energy storage capacity optimization configuration model according to the operating characteristics of the microgrid group, thereby providing a reliable data basis for the construction of the energy storage capacity optimization configuration model.

[0121] In step S103, based on the objective function and multiple optimization configuration constraints, an energy storage capacity optimization configuration model corresponding to the target microgrid group is constructed, and the energy storage capacity optimization configuration model is solved to obtain an energy storage capacity configuration result, and the energy storage capacity of the target microgrid group is optimized according to the energy storage capacity configuration result.

[0122] Furthermore, the embodiments of the present application can construct an energy storage capacity optimization configuration model corresponding to the target microgrid group according to the objective function and multiple optimization configuration constraints, such as Figure 3 As shown, the energy storage capacity optimization configuration model is solved to obtain the energy storage capacity configuration result, so as to optimize the energy storage capacity of the target microgrid group according to the energy storage capacity configuration result.

[0123] Optionally, in one embodiment of the present application, solving the energy storage capacity optimization configuration model to obtain the energy storage capacity configuration result includes: converting the energy storage capacity optimization configuration model into a linear model, and solving the linear model through a preset Gurobi solver to obtain the energy storage capacity configuration result, wherein the energy storage capacity configuration result includes the target energy storage power capacity and the target energy storage rated capacity corresponding to the target microgrid group.

[0124] It should be noted that the embodiments of the present application may adopt the Big M method to convert the nonlinear part of the energy storage capacity optimization configuration model into a linearized model for solution, and provide a MATLAB platform to call the Gurobi solver to solve the linearized model to determine the power capacity and rated capacity of the energy storage, thereby effectively reducing the operating cost of the microgrid group and improving the system economy.

[0125] Therefore, the embodiment of the present application considers the energy storage configuration strategy of subnet self-consistency and inter-group sharing, optimizes it with the goal of optimizing the economic efficiency of the microgrid group operation, thereby providing a reference for the optimal configuration of the energy storage capacity of the microgrid group, further reducing the operating cost of the distribution network, and promoting the consumption of new energy.

[0126] According to the method for optimizing the configuration of energy storage capacity of a microgrid group proposed in the embodiment of the present application, the electric energy balance rule of the microgrid group corresponding to the target microgrid group is constructed; the objective function corresponding to the total operating cost of the target microgrid group within one day is determined, and based on the operating characteristics of the target microgrid group, multiple optimization configuration constraints corresponding to the target microgrid group are established; based on the objective function and multiple optimization configuration constraints, an energy storage capacity optimization configuration model corresponding to the target microgrid group is constructed, and the energy storage capacity optimization configuration model is solved to obtain the energy storage capacity configuration result, and the energy storage capacity of the target microgrid group is optimized according to the energy storage capacity configuration result. The present application can effectively reduce the operating cost of the microgrid group by determining the power capacity and rated capacity of the energy storage, thereby improving the economy of the system.

[0127] Secondly, the device for optimizing the energy storage capacity configuration of a microgrid group proposed in accordance with an embodiment of the present application is described with reference to the accompanying drawings.

[0128] Figure 4 It is a block diagram of a device for optimizing energy storage capacity configuration of a microgrid group according to an embodiment of the present application.

[0129] like Figure 4 As shown, the microgrid group energy storage capacity optimization configuration device 10 includes: a rule module 100, an establishment module 200 and an optimization configuration module 300.

[0130] The rule module 100 is used to construct a microgrid group power balance rule corresponding to the target microgrid group.

[0131] The module 200 is established to determine the objective function corresponding to the total operating cost of the target microgrid group within one day, and to establish a plurality of optimization configuration constraints corresponding to the target microgrid group based on the operating characteristics of the target microgrid group.

[0132] The optimization configuration module 300 is used to construct an energy storage capacity optimization configuration model corresponding to the target microgrid group based on the objective function and multiple optimization configuration constraints, and solve the energy storage capacity optimization configuration model to obtain the energy storage capacity configuration result, and optimize the energy storage capacity of the target microgrid group according to the energy storage capacity configuration result.

[0133] Optionally, in one embodiment of the present application, the rule module 100 includes: a judgment unit, a power loss unit and a power redundancy unit.

[0134] The judgment unit is used to judge whether there is a power-deficient sub-microgrid that meets a preset power-deficient condition or a power-redundant sub-microgrid that meets a preset power-redundant condition in the target microgrid group.

[0135] The power missing unit is used to control the adjacent sub-microgrids of the power missing sub-microgrid to transmit power to the power missing sub-microgrid if there is a power missing sub-microgrid that meets the preset power missing condition in the target microgrid group, and to determine whether the power missing sub-microgrid meets the preset power balance requirement after the power transmission, wherein, when the power missing sub-microgrid does not meet the preset power balance requirement, electricity is purchased from the target grid through the power missing sub-microgrid until the power missing sub-microgrid meets the preset power balance requirement.

[0136] The power redundancy unit is used to transmit power to an adjacent sub-microgrid of the power redundant sub-microgrid through the power redundant sub-microgrid if there is a power redundant sub-microgrid that meets the preset power redundancy condition in the target microgrid group, and determine whether the power redundant sub-microgrid after the power transmission meets the preset power balance requirement, wherein, when the power redundant sub-microgrid does not meet the preset power balance requirement, sell electricity to the target grid through the power redundant sub-microgrid until the power redundant sub-microgrid meets the preset power balance requirement.

[0137] Optionally, in one embodiment of the present application, the establishing module 200 includes: a first calculating unit, a first determining unit, a second calculating unit, a third calculating unit, a fourth calculating unit and a constructing unit.

[0138] Among them, the first calculation unit is used to calculate the renewal replacement cost and the remaining recovery value of the target energy storage equipment.

[0139] The first determination unit is used to determine the unit investment cost of energy storage capacity, the unit investment cost of energy storage power, the energy storage rated capacity and the energy storage rated power of each sub-microgrid in the target microgrid group.

[0140] The second calculation unit is used to calculate the energy storage investment and construction cost of the target microgrid group according to the renewal replacement cost, the residual recovery value, the unit investment cost of the energy storage capacity, the unit investment cost of the energy storage power, the energy storage rated capacity and the energy storage rated power.

[0141] The third calculation unit is used to calculate the energy storage operation and maintenance cost and wind and solar operation and maintenance cost of the target microgrid group based on the energy storage unit operation and maintenance cost and DG unit operation and maintenance cost of each sub-microgrid.

[0142] The fourth calculation unit is used to calculate the electricity purchase cost of the target microgrid group, the electricity transmission cost between sub-microgrids, the peak shaving and valley filling benefits and the low-carbon benefits.

[0143] The construction unit is used to construct the objective function of the energy storage capacity optimization configuration model according to the energy storage investment and construction cost, energy storage operation and maintenance cost, wind and solar operation and maintenance cost, electricity purchase cost, power transmission cost between sub-microgrids, peak shaving and valley filling benefits, low-carbon benefits, preset prediction error penalties and fluctuation penalties.

[0144] Optionally, in one embodiment of the present application, the establishing module 200 further includes: a second determining unit and an acquiring unit.

[0145] Among them, the second determination unit is used to determine the interconnection line power, distributed power output, energy storage discharge power, energy storage charging power and load power of the target microgrid group, so as to establish a power balance constraint condition among multiple optimization configuration constraints according to the interconnection line power, distributed power output, energy storage discharge power, energy storage charging power and load power.

[0146] The acquisition unit is used to obtain the theoretical output of distributed power sources, the power limit of the interconnection line and the rated capacity of energy storage of the target microgrid group, so as to determine the distributed power source output constraint condition, the interconnection line power constraint condition, the energy storage charging and discharging state constraint condition, the energy storage power output constraint condition, the energy storage capacity constraint condition, the energy storage SOC constraint condition, the energy storage charging and discharging time constraint condition and the power transmission constraint condition between microgrids among multiple optimization configuration constraints based on the theoretical output of distributed power sources, the power limit of the interconnection line and the rated capacity of energy storage.

[0147] Optionally, in one embodiment of the present application, the optimization configuration module 300 includes: a solving unit, used to convert the energy storage capacity optimization configuration model into a linear model, and solve the linear model through a preset Gurobi solver to obtain an energy storage capacity configuration result, wherein the energy storage capacity configuration result includes a target energy storage power capacity and a target energy storage rated capacity corresponding to the target microgrid group.

[0148] It should be noted that the aforementioned explanation of the embodiment of the method for optimizing the configuration of the energy storage capacity of a microgrid group is also applicable to the device for optimizing the configuration of the energy storage capacity of a microgrid group of this embodiment, and will not be repeated here.

[0149] The device for optimizing the energy storage capacity configuration of a microgrid group proposed in the embodiment of the present application includes a rule module for constructing a microgrid group electric energy balance rule corresponding to the target microgrid group; an establishment module for determining the objective function corresponding to the total operating cost of the target microgrid group within one day, and establishing multiple optimization configuration constraints corresponding to the target microgrid group based on the operating characteristics of the target microgrid group; an optimization configuration module for constructing an energy storage capacity optimization configuration model corresponding to the target microgrid group based on the objective function and multiple optimization configuration constraints, and solving the energy storage capacity optimization configuration model to obtain an energy storage capacity configuration result, and optimizing the energy storage capacity of the target microgrid group according to the energy storage capacity configuration result. The present application can effectively reduce the operating cost of the microgrid group by determining the power capacity and rated capacity of the energy storage, thereby improving the economy of the system.

[0150] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0151] A memory 501 , a processor 502 , and a computer program stored in the memory 501 and executable on the processor 502 .

[0152] When the processor 502 executes the program, the method for optimizing the configuration of the energy storage capacity of the microgrid group provided in the above embodiment is implemented.

[0153] Furthermore, the electronic device further comprises:

[0154] The communication interface 503 is used for communication between the memory 501 and the processor 502 .

[0155] The memory 501 is used to store computer programs that can be executed on the processor 502 .

[0156] The memory 501 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0157] If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0158] Optionally, in a specific implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can communicate with each other through an internal interface.

[0159] The processor 502 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0160] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for optimizing the configuration of energy storage capacity of a microgrid group.

[0161] The embodiment of the present application also provides a computer program product, including a computer program, which, when executed, is used to implement the above-mentioned method for optimizing the configuration of energy storage capacity of a microgrid group.

[0162] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0163] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0164] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0165] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0166] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0167] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0168] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0169] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for optimizing the energy storage capacity of a microgrid group, characterized in that: The following steps are involved: Constructing the microgrid group power balance rules corresponding to the target microgrid group; Determine an objective function corresponding to the total operating cost of the target microgrid group within one day, and establish a plurality of optimization configuration constraints corresponding to the target microgrid group based on the operating characteristics of the target microgrid group; Based on the objective function and the multiple optimization configuration constraints, an energy storage capacity optimization configuration model corresponding to the target microgrid group is constructed, and the energy storage capacity optimization configuration model is solved to obtain an energy storage capacity configuration result, and the energy storage capacity of the target microgrid group is optimized according to the energy storage capacity configuration result.

2. The method according to claim 1, characterized in that The microgrid group power balance rule includes: Determine whether there is a power-deficient sub-microgrid that meets a preset power-deficient condition or a power-redundant sub-microgrid that meets a preset power-redundant condition in the target microgrid group; If there is a power-deficient sub-microgrid that meets the preset power-deficient condition in the target microgrid group, the adjacent sub-microgrid of the power-deficient sub-microgrid is controlled to transmit power to the power-deficient sub-microgrid, and it is determined whether the power-deficient sub-microgrid after the power transmission meets the preset power balance requirement, wherein, when the power-deficient sub-microgrid does not meet the preset power balance requirement, electricity is purchased from the target grid through the power-deficient sub-microgrid until the power-deficient sub-microgrid meets the preset power balance requirement; If there is a power redundant sub-microgrid that meets the preset power redundancy condition in the target microgrid group, power is transmitted to an adjacent sub-microgrid of the power redundant sub-microgrid through the power redundant sub-microgrid, and it is determined whether the power redundant sub-microgrid after the power transmission meets the preset power balance requirement, wherein, when the power redundant sub-microgrid does not meet the preset power balance requirement, electricity is sold to the target grid through the power redundant sub-microgrid until the power redundant sub-microgrid meets the preset power balance requirement.

3. The method according to claim 2, characterized in that The objective function corresponding to the total operating cost of the target microgrid group in one day is determined, including: Calculate the replacement cost and residual recovery value of the target energy storage equipment; Determine the energy storage capacity unit investment cost, energy storage power unit investment cost, energy storage rated capacity and energy storage rated power of each sub-microgrid in the target microgrid group; Calculate the energy storage investment and construction cost of the target microgrid group according to the renewal replacement cost, the remaining recovery value, the unit investment cost of the energy storage capacity, the unit investment cost of the energy storage power, the energy storage rated capacity and the energy storage rated power; Based on the energy storage unit operation and maintenance cost and DG unit operation and maintenance cost of each sub-microgrid, respectively calculate the energy storage operation and maintenance cost and wind and solar operation and maintenance cost of the target microgrid group; Calculate the electricity purchase cost, power transmission cost between sub-microgrids, peak shaving and valley filling benefits and low-carbon benefits of the target microgrid group; The objective function of the energy storage capacity optimization configuration model is constructed based on the energy storage investment and construction cost, energy storage operation and maintenance cost, wind and solar operation and maintenance cost, electricity purchase cost, power transmission cost between sub-microgrids, peak shaving and valley filling benefits, low-carbon benefits, preset prediction error penalty and fluctuation penalty.

4. The method according to claim 3, characterized in that The establishing of a plurality of optimization configuration constraints corresponding to the target microgrid group based on the operating characteristics of the target microgrid group includes: Determine the tie line power, distributed power output, energy storage discharge power, energy storage charging power and load power of the target microgrid group, so as to establish a power balance constraint condition among the multiple optimization configuration constraints according to the tie line power, the distributed power output, the energy storage discharge power, the energy storage charging power and the load power; The distributed power theoretical output, tie line power limit and energy storage rated capacity of the target microgrid group are obtained, so as to determine the distributed power output constraint, tie line power constraint, energy storage charge and discharge state constraint, energy storage power output constraint, energy storage capacity constraint, energy storage SOC constraint, energy storage charge and discharge time constraint and inter-microgrid power transmission constraint among the multiple optimization configuration constraints based on the distributed power theoretical output, tie line power limit and energy storage rated capacity.

5. The method according to claim 4, characterized in that Solving the energy storage capacity optimization configuration model to obtain an energy storage capacity configuration result includes: The energy storage capacity optimization configuration model is converted into a linear model, and the linear model is solved by a preset Gurobi solver to obtain the energy storage capacity configuration result, wherein the energy storage capacity configuration result includes the target energy storage power capacity and the target energy storage rated capacity corresponding to the target microgrid group.

6. A device for optimizing the energy storage capacity of a microgrid group, characterized in that: include: A rule module, used to construct a microgrid group power balance rule corresponding to the target microgrid group; Establishing a module for determining an objective function corresponding to the total operating cost of the target microgrid group within one day, and establishing a plurality of optimization configuration constraints corresponding to the target microgrid group based on the operating characteristics of the target microgrid group; The optimization configuration module is used to construct an energy storage capacity optimization configuration model corresponding to the target microgrid group based on the objective function and the multiple optimization configuration constraints, and solve the energy storage capacity optimization configuration model to obtain an energy storage capacity configuration result, and optimize the energy storage capacity of the target microgrid group according to the energy storage capacity configuration result.

7. The device according to claim 6, characterized in that The rule module includes: A judging unit, used to judge whether there is a power-deficient sub-microgrid that meets a preset power-deficient condition or a power-redundant sub-microgrid that meets a preset power-redundant condition in the target microgrid group; A power-deficient unit is used for controlling the adjacent sub-microgrid of the power-deficient sub-microgrid to transmit power to the power-deficient sub-microgrid if there is a power-deficient sub-microgrid that meets the preset power-deficient condition in the target microgrid group, and judging whether the power-deficient sub-microgrid after the power transmission meets the preset power balance requirement, wherein when the power-deficient sub-microgrid does not meet the preset power balance requirement, purchasing electricity from the target grid through the power-deficient sub-microgrid until the power-deficient sub-microgrid meets the preset power balance requirement; A power redundancy unit is used for, if there is a power redundant sub-microgrid satisfying the preset power redundancy condition in the target microgrid group, transmitting power to an adjacent sub-microgrid of the power redundant sub-microgrid through the power redundant sub-microgrid, and judging whether the power redundant sub-microgrid after the power transmission satisfies the preset power balance requirement, wherein, when the power redundant sub-microgrid does not satisfy the preset power balance requirement, selling electricity to the target grid through the power redundant sub-microgrid until the power redundant sub-microgrid satisfies the preset power balance requirement.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for optimizing the configuration of energy storage capacity of a microgrid group as described in any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method for optimizing the configuration of energy storage capacity of a microgrid group as described in any one of claims 1 to 5.

10. A computer program product, comprising a computer program, characterized in that The computer program is executed to implement the method for optimizing the configuration of energy storage capacity of a microgrid group as described in any one of claims 1 to 5.

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