A method and system for planning a grid-type energy storage power station

Abstract

The present invention discloses a method and system for planning a grid-type energy storage power station, the method comprising: constructing an energy storage power station planning model, the energy storage power station planning model includes, under a first preset constraint condition, constructing an upper-level planning model with overall cost minimization as the objective function, and under a second preset constraint condition, constructing a lower-level planning model with insufficient flexibility penalty costs and carbon reduction benefits as control objects; solving the energy storage power station planning model based on an improved imperial competition algorithm, and the energy storage power station planning model outputs a planning result. Comprehensively considering the impact of energy storage on peak load regulation and frequency regulation, a corresponding calculation model is proposed and incorporated into the planning objective function. By using the calculation model of the present invention, the benefits of energy storage equipment can be more comprehensively evaluated to achieve accurate planning.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy storage power station planning, and in particular relates to a planning method and system for a grid-type energy storage power station. Background Art

[0002] At present, the planning of energy storage power stations adopts a joint optimization model of conventional units and energy storage power stations under constraints, including an inner optimization model and an outer optimization model; the inner optimization model is solved to obtain the optimal operating cost, the optimal operating cost is substituted into the outer optimization model, and the particle swarm algorithm is used to solve the outer optimization model to obtain the optimized energy storage configuration capacity.

[0003] Existing technologies have taken into account the impact of renewable energy on energy storage planning. However, in the context of new power system construction, the large-scale grid connection of electric vehicles will also have a significant impact on grid planning. Current technologies do not cover grid-connected energy storage planning for both electric vehicles and distributed renewable energy. Summary of the invention

[0004] The present invention provides a planning method and system for a grid-type energy storage power station, which are used to solve the above-mentioned technical problems.

[0005] In a first aspect, the present invention provides a method for planning a grid-type energy storage power station, comprising:

[0006] Construct an energy storage power station planning model, wherein the energy storage power station planning model includes constructing an upper-level planning model with overall cost minimization as the objective function under a first preset constraint condition, and constructing a lower-level planning model with insufficient flexibility penalty cost and carbon reduction benefit as the control object under a second preset constraint condition, wherein the expression of the objective function is:

[0007] ,

[0008] ,

[0009] ,

[0010] In the formula, For the overall cost, For running costs, is the annualized cost of energy storage over its entire life cycle, For peak load benefits, is the frequency modulation gain, The cost of purchasing electricity for the main grid is is the network loss cost, Penalty fee for abandonment. Penalty fees for wind curtailment, is the loss cost of electric vehicle power batteries, For the operation cycle, is the number of EVs participating in peak load regulation, is the price of the power battery of the i-th EV, is the cycle life of the power battery of the i-th EV, is the conversion efficiency of charging and discharging of the power battery of the i-th EV, is the power battery capacity of the i-th EV, The discharge power of EVs participating in peak load regulation;

[0011] The energy storage power station planning model is solved based on the improved imperial competition algorithm, and the energy storage power station planning model outputs a planning result, wherein the expression of the adaptive reform probability in the improved imperial competition algorithm is:

[0012] ,

[0013] In the formula, is the probability of adaptive reform, is the basic value of reform probability, is the operating cost of the colony with the lowest operating cost among the i-th occupied colonies, is the operating cost of the colony with the lowest operating cost among the first colonies occupied, is the operating cost of the colony with the lowest operating cost among the second colonies occupied, is the operating cost of the colony with the smallest operating cost among the nth occupied colonies, is the maximum number of iterations, The number of the current iteration.

[0014] In a second aspect, the present invention provides a grid-type energy storage power station planning system, comprising:

[0015] A construction module is configured to construct an energy storage power station planning model, wherein the energy storage power station planning model includes constructing an upper-level planning model with overall cost minimization as the objective function under a first preset constraint condition, and constructing a lower-level planning model with insufficient flexibility penalty cost and carbon reduction benefit as control objects under a second preset constraint condition, wherein the expression of the objective function is:

[0016] ,

[0017] ,

[0018] ,

[0019] In the formula, For the overall cost, For running costs, is the annualized cost of energy storage over its entire life cycle, For peak load benefits, is the frequency modulation gain, The cost of purchasing electricity for the main grid is is the network loss cost, Penalty fee for abandonment. Penalty fees for wind curtailment, is the loss cost of electric vehicle power batteries, For the operation cycle, is the number of EVs participating in peak load regulation, is the price of the power battery of the i-th EV, is the cycle life of the power battery of the i-th EV, is the conversion efficiency of charging and discharging of the power battery of the i-th EV, is the power battery capacity of the i-th EV, The discharge power of EVs participating in peak load regulation;

[0020] A solution module is configured to solve the energy storage power station planning model based on an improved imperial competition algorithm, and the energy storage power station planning model outputs a planning result, wherein the expression of the adaptive reform probability in the improved imperial competition algorithm is:

[0021] ,

[0022] In the formula, is the probability of adaptive reform, is the basic value of reform probability, is the operating cost of the colony with the lowest operating cost among the i-th occupied colonies, is the operating cost of the colony with the lowest operating cost among the first colonies occupied, is the operating cost of the colony with the lowest operating cost among the second colonies occupied, is the operating cost of the colony with the smallest operating cost among the nth occupied colonies, is the maximum number of iterations, The number of the current iteration.

[0023] According to a third aspect, an electronic device is provided, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the steps of the grid-type energy storage power station planning method of any embodiment of the present invention.

[0024] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor executes the steps of the grid-connected energy storage power station planning method of any embodiment of the present invention.

[0025] The grid-type energy storage power station planning method and system of the present application not only considers the energy storage planning under the influence of distributed renewable energy, but also considers the economic cost caused by the loss of electric vehicle power batteries, and proposes a corresponding calculation model; when considering the configuration of grid-type energy storage, it is not only considered from the investment cost, but also calculated from the whole life cycle cost, including the initial investment, operation and maintenance cost and recovery cost. When the energy storage cost model of the present invention is used for calculation, the calculation result is more in line with reality and has a higher degree of practicality; the impact of energy storage on peak load regulation and frequency regulation is comprehensively considered, and a corresponding calculation model is proposed and incorporated into the planning objective function. The calculation model of the present invention can be used to more comprehensively evaluate the benefits of energy storage equipment and achieve accurate planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0027] Figure 1 A flowchart of a method for planning a grid-type energy storage power station provided by an embodiment of the present invention;

[0028] Figure 2 A structural block diagram of a grid-type energy storage power station planning system provided by an embodiment of the present invention;

[0029] Figure 3 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] See also Figure 1 , which shows a flow chart of a grid-type energy storage power station planning method of the present application.

[0032] like Figure 1 As shown, the planning method of the grid-type energy storage power station specifically includes the following steps:

[0033] Step S101, constructing an energy storage power station planning model, wherein the energy storage power station planning model includes constructing an upper-level planning model with overall cost minimization as the objective function under a first preset constraint condition, and constructing a lower-level planning model with insufficient flexibility penalty cost and carbon reduction benefit as control objects under a second preset constraint condition.

[0034] In this step, the expression of the objective function is:

[0035] ,

[0036] The expression for calculating the peak load benefit is:

[0037] ,

[0038] In the formula, is the peak load unit price, For peak load regulation;

[0039] The expression for calculating the frequency modulation gain is:

[0040] ,

[0041] In the formula, is the frequency modulation unit price, is the maximum active power;

[0042] The expression for calculating the annualized cost of energy storage over its entire life cycle is:

[0043] ,

[0044] In the formula, is the capacity of the transformer to be installed, is the transformer life cycle cost per unit capacity, is the capacity of energy storage equipment to be installed, is the life cycle cost per unit capacity of energy storage equipment, is the installed capacity of the transformer at node i, is the installed capacity of energy storage equipment at node i, is the discount rate, The useful life of the resource.

[0045] ,

[0046] ,

[0047] In the formula, For the overall cost, For running costs, is the annualized cost of energy storage over its entire life cycle, For peak load benefits, is the frequency modulation gain, The cost of purchasing electricity for the main grid is is the network loss cost, Penalty fee for abandonment. Penalty fees for wind curtailment, is the loss cost of electric vehicle power batteries, For the operation cycle, is the number of EVs participating in peak load regulation, is the price of the power battery of the i-th EV, is the cycle life of the power battery of the i-th EV, is the conversion efficiency of charging and discharging of the power battery of the i-th EV, is the power battery capacity of the i-th EV, The discharge power of EVs participating in peak load regulation;

[0048] The expression for calculating the main grid electricity purchase cost is:

[0049] ,

[0050] In the formula, The main online electricity price is Purchase electricity for the main network;

[0051] The expression for calculating network loss cost is:

[0052] ,

[0053] In the formula, is the network loss price, is the network loss, To calculate the total number of hours of network loss, is the current hour;

[0054] The expression for calculating the penalty cost of abandoned light is:

[0055] ,

[0056] In the formula, Penalty price for abandoning light, is the amount of abandoned light;

[0057] The expression for calculating the penalty fee for wind curtailment is:

[0058] ,

[0059] In the formula, Penalize prices for wind curtailment, The abandoned air volume.

[0060] It should be noted that the first preset constraint condition includes:

[0061] The power balance constraint is expressed as:

[0062] ,

[0063] In the formula, , , , , , They are the power generation of thermal power units, wind power generation, photovoltaic power generation, wind power abandonment, photovoltaic power abandonment and load power;

[0064] Carbon emission constraint, expressed as:

[0065] ,

[0066] In the formula, is the maximum carbon emission in year t, is the carbon emission rate, is the power generation of thermal power units in year t, For the planning cycle, For thermal power units.

[0067] Furthermore, the expression of the lower-level planning model is:

[0068] ,

[0069] In the formula, Penalty costs for lack of flexibility, is the penalty coefficient for insufficient downward flexibility, is the penalty coefficient for insufficient upward flexibility, To provide flexibility for downward adjustment, To provide flexibility for upward adjustment, For carbon benefits, The amount of coal burned per unit mass The conversion factor, is the coal consumption per unit of electricity produced, For the cost of carbon trading, The amount of electricity generated by new energy.

[0070] The second preset constraint condition includes:

[0071] Power Flexible Power Constraint, the expression is:

[0072] ,

[0073] In the formula, , , , , , They are the thermal power unit power at time t, wind power generation power at time t, photovoltaic power at time t, energy storage charging and discharging power at time t, electric vehicle charging and discharging power at time t, and load power at time t;

[0074] Node voltage constraint, expression is:

[0075] ,

[0076] In the formula, is the voltage lower limit, is the voltage value of the ith node, is the voltage upper limit;

[0077] Energy storage charging and discharging constraints and SOC constraints, the expressions are:

[0078] ,

[0079] In the formula, is the minimum state of charge of the electric vehicle power battery, is the state of charge of the electric vehicle power battery, is the maximum state of charge of the electric vehicle power battery, is the electric energy of the nth sequence of energy storage, is the electric energy of the n-1th sequence of energy storage, is the charging and discharging power of the nth sequence of energy storage, The time that each energy storage can be continuously charged and discharged. is the active power output of the energy storage, , It is the charging efficiency and discharging efficiency of energy storage.

[0080] Step S102, solving the energy storage power station planning model based on the improved imperial competition algorithm, and the energy storage power station planning model outputs a planning result.

[0081] In this step, the energy storage power station planning model is solved based on the improved imperial competition algorithm as follows:

[0082] Random Generation Initial countries, assuming that the powerful imperialist country has , other Each individual is a colony, and all generated countries are defined as a set of one-dimensional arrays, specifically:

[0083] ,

[0084] In the formula, For a collection of countries, For the first country in the set, For the second country in the set, is the nth country in the set;

[0085] The smaller the cost function of an imperialist country, the greater its power. By evaluating the cost function, we can get the power of each imperialist country:

[0086]

[0087] ,

[0088] ,

[0089] ,

[0090] In the formula, is the standardized cost function, is the cost function, Standardize prices for empires, is the number of colonies in Empire n, is the total number of colonies, The number of powerful imperialist countries.

[0091] Assimilation of colonies:

[0092] If the colonies are improved, the imperialist country will move all its colonies in the direction of itself, with a moving distance of x, where x is a random variable that satisfies:

[0093] ,

[0094] In the formula, is the direction coefficient, d is the distance between the empire and the colony, Indicates that the random variable x follows the interval Uniform distribution on

[0095] Distinguish different points around the empire and make random deviations Introduced colony movement direction, obey , is the distribution coefficient. and Usually the values ​​are and 2.

[0096] Imperial Competition:

[0097] Sort the empires by size and analyze the advantages of occupation. The total power of each empire is expressed as:

[0098] ,

[0099] In the formula, is the empire power coefficient, is the total power of the nth empire, For the power of the nth colonial country, For the colonial power of Empire n;

[0100] Adaptive Reform Probability:

[0101] In the original empire competition algorithm, the reform probability is a fixed value. After the reform probability is adaptively changed with the number of iterations, the group diversity can be continuously improved. The expression of the adaptive reform probability is:

[0102] ,

[0103] In the formula, is the probability of adaptive reform, is the basic value of reform probability, is the operating cost of the colony with the lowest operating cost among the i-th occupied colonies, is the operating cost of the colony with the lowest operating cost among the first colonies occupied, is the operating cost of the colony with the lowest operating cost among the second colonies occupied, is the operating cost of the colony with the smallest operating cost among the nth occupied colonies, is the maximum number of iterations, The number of the current iteration.

[0104] The Empire Falls:

[0105] When an empire loses all its colonies, it is in a state of extinction, with only one most powerful empire left.

[0106] In summary, the method of the present application not only considers the energy storage planning under the influence of distributed renewable energy, but also considers the economic cost brought about by the loss of electric vehicle power batteries, and proposes a corresponding calculation model; when considering the configuration of grid-type energy storage, it is not only considered from the investment cost, but also calculated from the cost of the entire life cycle, including the initial investment, operation and maintenance cost and recovery cost. When the energy storage cost model of the present invention is used for calculation, the calculation result is more in line with reality and has a higher degree of practicality; comprehensively considering the impact of energy storage on peak load regulation and frequency regulation, a corresponding calculation model is proposed and incorporated into the planning objective function. The calculation model of the present invention can be used to more comprehensively evaluate the benefits of energy storage equipment and achieve accurate planning.

[0107] See also Figure 2 , which shows a structural block diagram of a grid-type energy storage power station planning system of the present application.

[0108] like Figure 2 As shown, the grid-type energy storage power station planning system 200 includes a construction module 210 and a solution module 220 .

[0109] The construction module 210 is configured to construct an energy storage power station planning model, wherein the energy storage power station planning model includes constructing an upper-level planning model with overall cost minimization as the objective function under a first preset constraint condition, and constructing a lower-level planning model with insufficient flexibility penalty cost and carbon reduction benefit as the control object under a second preset constraint condition, wherein the expression of the objective function is:

[0110] ,

[0111] ,

[0112] ,

[0113] In the formula, For the overall cost, For running costs, is the annualized cost of energy storage over its entire life cycle, For peak load benefits, is the frequency modulation gain, The cost of purchasing electricity for the main grid is is the network loss cost, Penalty fee for abandonment. Penalty fees for wind curtailment, is the loss cost of electric vehicle power batteries, For the operation cycle, is the number of EVs participating in peak load regulation, is the price of the power battery of the i-th EV, is the cycle life of the power battery of the i-th EV, is the conversion efficiency of charging and discharging of the power battery of the i-th EV, is the power battery capacity of the i-th EV, The discharge power of EVs participating in peak load regulation;

[0114] The solving module 220 is configured to solve the energy storage power station planning model based on the improved imperial competition algorithm, and the energy storage power station planning model outputs a planning result, wherein the expression of the adaptive reform probability in the improved imperial competition algorithm is:

[0115] ,

[0116] In the formula, is the probability of adaptive reform, is the basic value of reform probability, is the operating cost of the colony with the lowest operating cost among the i-th occupied colonies, is the operating cost of the colony with the lowest operating cost among the first colonies occupied, is the operating cost of the colony with the lowest operating cost among the second colonies occupied, is the operating cost of the colony with the smallest operating cost among the nth occupied colonies, is the maximum number of iterations, The number of the current iteration.

[0117] It should be understood that Figure 2 Modules and references documented in Figure 1 Therefore, the operations and features described above for the method and the corresponding technical effects are also applicable to Figure 2 The modules in it will not be described in detail here.

[0118] In some other embodiments, the embodiments of the present invention further provide a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor executes the grid-type energy storage power station planning method in any of the above method embodiments;

[0119] As an implementation mode, the computer-readable storage medium of the present invention stores computer-executable instructions, and the computer-executable instructions are configured as follows:

[0120] Construct an energy storage power station planning model, wherein the energy storage power station planning model includes constructing an upper-level planning model with overall cost minimization as the objective function under a first preset constraint condition, and constructing a lower-level planning model with insufficient flexibility penalty cost and carbon reduction benefit as the control object under a second preset constraint condition, wherein the expression of the objective function is:

[0121] ,

[0122] ,

[0123] ,

[0124] In the formula, For the overall cost, For running costs, is the annualized cost of energy storage over its entire life cycle, For peak load benefits, is the frequency modulation gain, The cost of purchasing electricity for the main grid is is the network loss cost, Penalty fee for abandonment. Penalty fees for wind curtailment, is the loss cost of electric vehicle power batteries, For the operation cycle, is the number of EVs participating in peak load regulation, is the price of the power battery of the i-th EV, is the cycle life of the power battery of the i-th EV, is the conversion efficiency of charging and discharging of the power battery of the i-th EV, is the power battery capacity of the i-th EV, The discharge power of EVs participating in peak load regulation;

[0125] The energy storage power station planning model is solved based on the improved imperial competition algorithm, and the energy storage power station planning model outputs a planning result, wherein the expression of the adaptive reform probability in the improved imperial competition algorithm is:

[0126] ,

[0127] In the formula, is the probability of adaptive reform, is the basic value of reform probability, is the operating cost of the colony with the lowest operating cost among the i-th occupied colonies, is the operating cost of the colony with the lowest operating cost among the first colonies occupied, is the operating cost of the colony with the lowest operating cost among the second colonies occupied, is the operating cost of the colony with the smallest operating cost among the nth occupied colonies, is the maximum number of iterations, is the number of current iterations. The computer-readable storage medium may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required by at least one function; the data storage area may store data created according to the use of the network-based energy storage power station planning system, etc. In addition, the computer-readable storage medium may include a high-speed random access memory, and may also include a memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the computer-readable storage medium may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the network-based energy storage power station planning system via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0128] Figure 3 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention, such as Figure 3As shown, the device includes: a processor 310 and a memory 320. The electronic device may also include: an input device 330 and an output device 340. The processor 310, the memory 320, the input device 330 and the output device 340 may be connected via a bus or other means. Figure 3 In the example, the connection through the bus is taken as an example. The memory 320 is the above-mentioned computer-readable storage medium. The processor 310 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions and modules stored in the memory 320, that is, the network-type energy storage power station planning method of the above-mentioned method embodiment is realized. The input device 330 can receive input digital or character information, and generate key signal input related to user settings and function control of the network-type energy storage power station planning system. The output device 340 may include display devices such as display screens.

[0129] The electronic device can execute the method provided by the embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not described in detail in this embodiment, please refer to the method provided by the embodiment of the present invention.

[0130] As an implementation mode, the electronic device is applied to a grid-type energy storage power station planning system and is used for a client, and includes: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can:

[0131] Construct an energy storage power station planning model, wherein the energy storage power station planning model includes constructing an upper-level planning model with overall cost minimization as the objective function under a first preset constraint condition, and constructing a lower-level planning model with insufficient flexibility penalty cost and carbon reduction benefit as the control object under a second preset constraint condition, wherein the expression of the objective function is:

[0132] ,

[0133] ,

[0134] ,

[0135] In the formula, For the overall cost, For running costs, is the annualized cost of energy storage over its entire life cycle, For peak load benefits, is the frequency modulation gain, The cost of purchasing electricity for the main grid is is the network loss cost, Penalty fee for abandonment. Penalty fees for wind curtailment, is the loss cost of electric vehicle power batteries, For the operation cycle, is the number of EVs participating in peak load regulation, is the price of the power battery of the i-th EV, is the cycle life of the power battery of the i-th EV, is the conversion efficiency of charging and discharging of the power battery of the i-th EV, is the power battery capacity of the i-th EV, The discharge power of EVs participating in peak load regulation;

[0136] The energy storage power station planning model is solved based on the improved imperial competition algorithm, and the energy storage power station planning model outputs a planning result, wherein the expression of the adaptive reform probability in the improved imperial competition algorithm is:

[0137] ,

[0138] In the formula, is the probability of adaptive reform, is the basic value of reform probability, is the operating cost of the colony with the lowest operating cost among the i-th occupied colonies, is the operating cost of the colony with the lowest operating cost among the first colonies occupied, is the operating cost of the colony with the lowest operating cost among the second colonies occupied, is the operating cost of the colony with the smallest operating cost among the nth occupied colonies, is the maximum number of iterations, is the number of current iterations. Through the description of the above implementation modes, those skilled in the art can clearly understand that each implementation mode can be implemented by means of software plus a necessary general hardware platform, and of course, by hardware. Based on this understanding, the above technical solution essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of various embodiments or certain parts of the embodiments.

[0139] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for planning a grid-type energy storage power station, characterized in that: include: Construct an energy storage power station planning model, wherein the energy storage power station planning model includes constructing an upper-level planning model with overall cost minimization as the objective function under a first preset constraint condition, and constructing a lower-level planning model with insufficient flexibility penalty cost and carbon reduction benefit as the control object under a second preset constraint condition, wherein the expression of the objective function is: ， ， ， In the formula, For the overall cost, For operating costs, is the annualized cost of energy storage over its entire life cycle, For peak load benefits, is the frequency modulation gain, The cost of purchasing electricity for the main grid is is the network loss cost, Penalty fee for abandonment. Penalty fees for wind curtailment, is the loss cost of electric vehicle power batteries, For the operation cycle, is the number of EVs participating in peak load regulation, is the price of the power battery of the i-th EV, is the cycle life of the power battery of the i-th EV, is the conversion efficiency of charging and discharging of the power battery of the i-th EV, is the power battery capacity of the i-th EV, The discharge power of EVs participating in peak load regulation; The expression of the lower-level planning model is: ， In the formula, Penalty costs for lack of flexibility, is the penalty coefficient for insufficient downward flexibility, is the penalty coefficient for insufficient upward flexibility, To provide flexibility for downward adjustment, To provide flexibility for upward adjustment, For carbon benefits, is the conversion coefficient produced by the combustion of unit mass of coal, is the coal consumption per unit of electricity produced, For the cost of carbon trading, The amount of electricity generated by renewable energy; The energy storage power station planning model is solved based on the improved imperial competition algorithm, and the energy storage power station planning model outputs a planning result, wherein the expression of the adaptive reform probability in the improved imperial competition algorithm is: ， In the formula, is the probability of adaptive reform, is the basic value of reform probability, is the operating cost of the colony with the smallest operating cost among the i-th occupied colonies, is the operating cost of the colony with the lowest operating cost among the first colonies occupied, is the operating cost of the colony with the lowest operating cost among the second colonies occupied, is the operating cost of the colony with the smallest operating cost among the nth occupied colonies, is the maximum number of iterations, The number of the current iteration.

2. A method for planning a grid-type energy storage power station according to claim 1, characterized in that: in, The expression for calculating the peak load benefit is: ， In the formula, is the peak load unit price, For peak load regulation; The expression for calculating the frequency modulation gain is: ， In the formula, is the frequency modulation unit price, is the maximum active power; The expression for calculating the annualized cost of energy storage over its entire life cycle is: ， In the formula, is the capacity of the transformer to be installed, is the transformer life cycle cost per unit capacity, is the capacity of energy storage equipment to be installed, is the life cycle cost per unit capacity of energy storage equipment, is the installed capacity of the transformer at node i, is the installed capacity of energy storage equipment at node i, is the discount rate, The useful life of the resource.

3. A method for planning a grid-type energy storage power station according to claim 1, characterized in that: in, The expression for calculating the main grid electricity purchase cost is: ， In the formula, The main online electricity price is Purchase electricity for the main network; The expression for calculating network loss cost is: ， In the formula, is the network loss price, is the network loss, To calculate the total number of hours of network loss, is the current hour; The expression for calculating the penalty cost of abandoned light is: ， In the formula, Penalty price for abandoning light, is the amount of abandoned light; The expression for calculating the penalty fee for wind curtailment is: ， In the formula, Penalize prices for wind curtailment, The abandoned air volume.

4. A method for planning a grid-type energy storage power station according to claim 1, characterized in that: The first preset constraint condition includes: The power balance constraint is expressed as: ， In the formula, , , , , , They are the power generation of thermal power units, wind power generation, photovoltaic power generation, wind power abandonment, photovoltaic power abandonment and load power; Carbon emission constraint, expressed as: ， In the formula, is the maximum carbon emission in year t, is the carbon emission rate, is the power generation of thermal power units in year t, For the planning cycle, For thermal power units.

5. A method for planning a grid-type energy storage power station according to claim 1, characterized in that: The second preset constraint condition includes: Power Flexible Power Constraint, the expression is: ， In the formula, , , , , , They are the thermal power unit power at time t, wind power generation power at time t, photovoltaic power at time t, energy storage charging and discharging power at time t, electric vehicle charging and discharging power at time t, and load power at time t; Node voltage constraint, expression is: ， In the formula, is the voltage lower limit, is the voltage value of the ith node, is the voltage upper limit; Energy storage charging and discharging constraints and SOC constraints, the expressions are: ， In the formula, is the minimum state of charge of the electric vehicle power battery, is the state of charge of the electric vehicle power battery, is the maximum state of charge of the electric vehicle power battery, is the electric energy of the nth sequence of energy storage, is the electric energy of the n-1th sequence of energy storage, is the charging and discharging power of the nth sequence of energy storage, The time that each energy storage can be continuously charged and discharged. is the active power output of the energy storage, , It is the charging efficiency and discharging efficiency of energy storage.

6. A grid-type energy storage power station planning system, characterized in that: include: A construction module is configured to construct an energy storage power station planning model, wherein the energy storage power station planning model includes constructing an upper-level planning model with overall cost minimization as the objective function under a first preset constraint condition, and constructing a lower-level planning model with insufficient flexibility penalty cost and carbon reduction benefit as control objects under a second preset constraint condition, wherein the expression of the objective function is: ， ， ， In the formula, For the overall cost, For operating costs, is the annualized cost of energy storage over its entire life cycle, For peak load benefits, is the frequency modulation gain, The cost of purchasing electricity for the main grid is is the network loss cost, Penalty fee for abandonment. Penalty fees for wind curtailment, is the loss cost of electric vehicle power batteries, For the operation cycle, is the number of EVs participating in peak load regulation, is the price of the power battery of the i-th EV, is the cycle life of the power battery of the i-th EV, is the conversion efficiency of charging and discharging of the power battery of the i-th EV, is the power battery capacity of the i-th EV, The discharge power of EVs participating in peak load regulation; The expression of the lower-level planning model is: ， In the formula, Penalty costs for lack of flexibility, is the penalty coefficient for insufficient downward flexibility, is the penalty coefficient for insufficient upward flexibility, To provide flexibility for downward adjustment, To provide flexibility for upward adjustment, For carbon benefits, is the conversion coefficient produced by the combustion of unit mass of coal, is the coal consumption per unit of electricity produced, For the cost of carbon trading, The amount of electricity generated by renewable energy; A solution module is configured to solve the energy storage power station planning model based on an improved imperial competition algorithm, and the energy storage power station planning model outputs a planning result, wherein the expression of the adaptive reform probability in the improved imperial competition algorithm is: ， In the formula, is the probability of adaptive reform, is the basic value of reform probability, is the operating cost of the colony with the smallest operating cost among the i-th occupied colonies, is the operating cost of the colony with the lowest operating cost among the first colonies occupied, is the operating cost of the colony with the lowest operating cost among the second colonies occupied, is the operating cost of the colony with the smallest operating cost among the nth occupied colonies, is the maximum number of iterations, The number of the current iteration.

7. An electronic device, characterized in that: include: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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