Optimal configuration and operation method of energy storage system

Abstract

The invention belongs to the field of optimal management of energy storage systems, and particularly relates to an optimal configuration and operation method of an energy storage system. The method includes the following steps that main target optimization configuration is determined, secondary target constraint conditions are determined in combination with the optimization configuration, and an energy storage configuration secondary optimization target function model is established; establishing an energy storage configuration secondary optimization target constraint model; the energy storage configuration secondary optimization target constraint model is established based on energy storage system power balance, installed capacity and power constraint and line transmission capacity constraint; determining an energy storage configuration optimization target optimization evaluation index; determining operation configuration of the energy storage system based on the optimal configuration; the method is used for capacity and power configuration management of the energy storage system matched with various new energy production system devices, a corresponding optimization model is established based on the lowest maintenance and operation cost and the optimal operation income of the energy storage system, and reference is provided for establishing the energy storage system with higher operation efficiency.

Description

Technical Field

[0001] The present invention belongs to the field of optimization management of energy storage systems, and in particular relates to an optimization configuration and operation method of an energy storage system. Background Art

[0002] With the continuous expansion of the scale of national new energy construction, the production capacity of new energy power is constantly increasing. Compared with the characteristics of traditional thermal power generation and nuclear power generation, the output and capacity of new energy power generation often reflect periodic changes. In order to integrate the input and output characteristics of distributed new energy power generation and reduce the uncertainty that may be caused by the access of new energy to the power grid, it is generally necessary to equip corresponding energy storage systems to collect and manage the input and output of distributed new energy equipment, so as to minimize the impact on the daily operation of the main supply and distribution network and improve the stable output capacity of the system. However, due to the periodic change characteristics of distributed new energy systems, the configuration and management strategies of energy storage systems are difficult. At present, the main focus is on maintaining the overall load stability of the distributed production capacity system and the power grid, and the improvement and determination of the capacity and power management capabilities of the energy storage system are relatively poor. Summary of the invention

[0003] The purpose of the present invention is to provide an energy storage system, especially an energy storage system supporting a distributed power system, based on actual needs, which is conducive to improving the configuration strategy of capacity and power management, reducing the system operation and maintenance costs, and improving the system output stability.

[0004] To achieve the above purpose, the present invention adopts the following technical solution.

[0005] An optimal configuration method for an energy storage system comprises the following steps:

[0006] Step 1. Determine the main target optimization configuration, including:

[0007] A1. Establish the main optimization objective function model of energy storage configuration;

[0008] Establish the main optimization objective function model of energy storage configuration based on the minimum energy storage configuration cost function;

[0009] A2. Establish the main optimization objective constraint model of energy storage configuration;

[0010] The main optimization objective constraint model of energy storage configuration is established based on the charging and discharging and capacity and power parameters of the energy storage system.

[0011] Step 2. Determine the secondary objective constraints in combination with the optimization configuration, including:

[0012] B1. Establishing the secondary optimization objective function model of energy storage configuration;

[0013] The optimal capacity configuration of the energy storage system is determined based on the main optimization objective function of energy storage configuration. On this basis, a secondary optimization objective function model is established based on the maximum operating benefit function of the energy storage system and the secondary optimization objective function model of energy storage configuration.

[0014] B2. Establish a secondary optimization target constraint model for energy storage configuration;

[0015] The energy storage configuration secondary optimization objective constraint model is established based on the energy storage system power balance, installed capacity and power constraints, and line transmission capacity constraints.

[0016] Step 3. Determine the optimization evaluation index of energy storage configuration optimization target;

[0017] The energy storage configuration optimization target optimization evaluation index is established based on the self-balancing index and load supply index of the distribution network where the energy storage system is located;

[0018] Step 4. Determine the energy storage system operation configuration based on the optimal configuration

[0019] According to the aforementioned steps one and two, the energy storage system configuration parameters that meet the primary optimization objectives and secondary optimization objectives of the energy storage configuration are determined. Based on step two, several optimal energy storage system configuration parameter schemes are determined as alternative schemes, and the selection is made according to the operation focus and actual operation status of the energy storage system.

[0020] Further improvement or specific implementation of the above energy storage system optimization configuration method, based on the minimum energy storage configuration cost function, the energy storage configuration main optimization objective function model can be expressed as Goal1 = min (C1 + C2 + C3);

[0021] in represents the cost of the asset;

[0022] It represents the fixed input cost of assets;

[0023] C 12 =C price P ed represents the energy conversion cost of the energy storage system;

[0024] C 13 =C wh E ed represents the capacity maintenance cost of the energy storage system;

[0025] Among them C p represents the unit power cost, C e represents the unit capacity cost, P ed Indicates rated power, E ed represents the rated capacity, r represents the interest rate, n is the operation cycle of the energy storage system, C priceis the unit power cost of the energy storage conversion device, C wh Express the maintenance cost per unit capacity of the energy storage system;

[0026] Where C2=μ2W cf represents the charging and discharging operation and maintenance cost of the energy storage system, μ2 represents the operation and maintenance cost coefficient, and W cf Indicates the annual charge and discharge capacity of the energy storage system;

[0027] in represents the energy storage system storage module update cost, C batin represents the initial cost of the energy storage module, and t3 represents the operating life of the energy storage module.

[0028] Further improvement or specific implementation of the above energy storage system optimization configuration method, based on the energy storage system charging and discharging and capacity power parameters to establish the energy storage configuration main optimization target constraint model can be specifically expressed as

[0029] Where f1 represents the remaining capacity of the energy storage battery, SOC min Refers to the minimum remaining capacity limit of the energy storage battery, SOC max Refers to the maximum remaining capacity limit of the energy storage battery, SOC t refers to the remaining capacity of the energy storage battery at time t; f2 represents the charging power constraint of the energy storage module, P ch.t.min represents the minimum charging power limit at time t, P ch.t.max represents the maximum charging power limit at time t, P ch.t represents the charging power at time t; f3 represents the energy storage module discharge power constraint, P pu.t.min represents the minimum discharge rate limit at time t, P pu.t.max Indicates the maximum discharge power limit at time t, P pu.t represents the discharge power at time t; f4 represents the system power constraint, f5 represents the system capacity constraint, P t represents the energy storage system power at time t, E t represents the capacity of the energy storage system at time t, P max Indicates the maximum allowable power of the system, E max Indicates the maximum allowable capacity of the system.

[0030] For further improvement or specific implementation of the above-mentioned energy storage system optimization configuration method, the secondary optimization objective function model established based on the maximum operation benefit function of the energy storage system can be expressed as: Goal2 = max(C 21 +C 22 -C 23 +C 24 );

[0031] in Represents the revenue from electricity purchase and sale of the energy storage system;

[0032] in Indicates the charging and discharging benefits of the energy storage system;

[0033] in Represents the loss cost of the energy storage system;

[0034] in Represents the power generation income of the energy storage system;

[0035] where η sell.t represents the unit price of electricity sold by the energy storage system at time t, η buy represents the unit price of electricity purchased by the energy storage system at time t, P sell.t represents the power sales of the energy storage system at time t, P buy.t represents the amount of electricity purchased by the energy storage system at time t, T represents the total number of hours per year; N cn Represents the total number of energy storage systems, m t represents the electricity price at time t, P i.t.dis represents the discharge power of the i-th energy storage system at time t, P i.t.ch represents the charging power of the i-th energy storage system at time t, Δt dis Denotes the discharge period, Δt ch Indicates the charging cycle; C year Represents the annual operating cost per unit power of the energy storage system, C k represents the unit price of the k-th type of renewable energy power generation subsidy, P k It represents the power generation of the kth type of renewable energy, and K represents the category of renewable energy.

[0036] For further improvement or specific implementation of the above-mentioned optimization configuration method of the energy storage system, the target constraint model established based on the self-balancing index and load supply index of the distribution network where the energy storage system is located can be specifically expressed as:

[0037]

[0038] Where f1' represents the power balance constraint of the energy storage system, and P k.t represents the output power of the kth generation node at time t, P tran.t represents the exchange power between the energy storage system and the power grid; f2' and f3' represent the system installed capacity constraint and power constraint, where S p Represents the installed power of the energy storage system, S p.max Represents the installed power limit of the energy storage system, where S z Represents the installed capacity of the energy storage system, S z.max represents the installed capacity limit of the energy storage system; f4' represents the network transmission capacity constraint of the energy storage system, where U t represents the energy storage system transmission power at time t, U t.minrepresents the lower limit of the energy storage system transmission power at time t, U t.max Indicates the upper limit of the energy storage system transmission power at time t.

[0039] For further improvement or specific implementation of the above-mentioned optimization configuration method of the energy storage system, the evaluation function established based on the self-balancing index and the load supply index can be expressed as Test1=λ1T1-λ2T2;

[0040] in represents the power self-supply index, where Q self Indicates the amount of electricity in the energy storage system used to meet its own power load, Q all Indicates the total amount of electricity required for the stable operation of the energy storage system itself;

[0041] in represents the power supply reliability index; where λ1∈[0,1] and λ2∈[0,1] refer to the normalized indicator weights.

[0042] The present application also provides an optimization operation method for an energy storage system, which is characterized in that an optimal operation strategy is determined by optimizing the operation mode of the energy storage system, and specifically includes the following steps:

[0043] D1. Calculate the output power P of various power generation nodes in the energy storage system based on the current configuration parameters k.t , calculate the power difference If ΔP t >0, then turn to D2, if ΔP t <0, go to D3;

[0044] D2. If the real-time electricity price is low or medium, the SOC of the battery in the energy storage module t ≤SOC max , and ΔP t ≤P ch.t.max When ΔP t >P ch.t.max , and the real-time electricity price is at a low or medium price, the output of various power generation nodes is used to power the load in the energy storage system and charge the energy storage battery, and the remaining electricity is sold to the grid; if ΔP t >P ch.t.max , the real-time electricity price is at the peak price, if SOC t ≤SOC min , the output of various power generation nodes is used to power the loads in the energy storage system and charge the energy storage batteries until SOC t ≥SOC t.set and sell the remaining electricity to the grid, where SOC t.set Refers to the preset safety power at time t; if ΔPt >P ch.t.max , the real-time electricity price is at the peak price, if SOC t ≥SOC t.min , selling the output of various power generation nodes to the power grid;

[0045] D3, if SOC t <SOC min And ΔP t >P ch.t.max , start the energy storage system power purchase and storage program, use the output of various power generation nodes to charge the energy storage system, and the remaining shortfall is met by purchasing electricity. If the real-time electricity price is at the peak price, charge until SOC t ≥SOC min If the real-time electricity price is low or medium, charge until SOC t ≥SOC t.set . BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a schematic diagram of the relationship between the primary optimization objective and the secondary optimization objective of the optimization configuration method of the energy storage system. DETAILED DESCRIPTION

[0047] The present invention is described in detail below in conjunction with specific embodiments.

[0048] The present application provides an optimization configuration method for an energy storage system, which is mainly used for capacity and power configuration management of energy storage systems supporting various types of new energy production system equipment. A corresponding optimization model is established based on the minimum maintenance and operation cost of the energy storage system and the optimal operating income, providing a reference for establishing an energy storage system with higher operating efficiency.

[0049] The optimization configuration method of the energy storage system of the present application is composed of a two-layer optimization objective function, and the relationship between the main optimization objective and the secondary optimization objective is as follows: Figure 1 As shown, the specific steps are as follows:

[0050] Step 1. Determine the main target optimization configuration, including:

[0051] A1. Establish the main optimization objective function model of energy storage configuration;

[0052] The energy storage configuration main optimization objective function model is established based on the minimum energy storage configuration cost function, and its objective function can be expressed as Goal1=min(C1+C2+C3);

[0053] C total =C nin +C om +C exc-BESS +C rep ;

[0054] in represents the cost of the asset;

[0055] It represents the fixed input cost of assets;

[0056] C 12 =C price P ed represents the energy conversion cost of the energy storage system;

[0057] C 13 =C wh E ed represents the capacity maintenance cost of the energy storage system;

[0058] Among them C p represents the unit power cost, C e represents the unit capacity cost, P ed Indicates rated power, E ed represents the rated capacity, r represents the interest rate, n is the operation cycle of the energy storage system, C price is the unit power cost of the energy storage conversion device, C wh Express the maintenance cost per unit capacity of the energy storage system;

[0059] Where C2=μ2W cf represents the charging and discharging operation and maintenance cost of the energy storage system, μ2 represents the operation and maintenance cost coefficient, and W cf Indicates the annual charge and discharge capacity of the energy storage system;

[0060] in represents the energy storage system storage module update cost, C batin represents the initial cost of the energy storage module, and t3 represents the operating life of the energy storage module;

[0061] A2. Establish the main optimization objective constraint model of energy storage configuration;

[0062] The energy storage configuration main optimization objective constraint model is determined based on the energy storage system charging and discharging and capacity power parameters, which can be specifically expressed as:

[0063] Where f1 represents the remaining capacity of the energy storage battery, SOC min Refers to the minimum remaining capacity limit of the energy storage battery, SOC max Refers to the maximum remaining capacity limit of the energy storage battery, SOC t refers to the remaining capacity of the energy storage battery at time t; f2 represents the charging power constraint of the energy storage module, P ch.t.min represents the minimum charging power limit at time t, P ch.t.max represents the maximum charging power limit at time t, P ch.trepresents the charging power at time t; f3 represents the energy storage module discharge power constraint, P pu.t.min represents the minimum discharge rate limit at time t, P pu.t.max Indicates the maximum discharge power limit at time t, P pu.t represents the discharge power at time t; f4 represents the system power constraint, f5 represents the system capacity constraint, P t represents the energy storage system power at time t, E t represents the capacity of the energy storage system at time t, P max Indicates the maximum allowable power of the system, E max Indicates the maximum allowable capacity of the system;

[0064] Step 2. Determine the secondary objective constraints in combination with the optimization configuration, including:

[0065] B1. Establishing the secondary optimization objective function model of energy storage configuration;

[0066] Based on the main optimization objective function of energy storage configuration, the optimal capacity configuration of the energy storage system is determined. On this basis, the capacity allocation method of the energy storage system and the operation mode of different power generation modules in the energy storage system will further affect the various states of the energy storage system. Generally speaking, in order to ensure the continuous and stable operation of the energy storage system, it should be ensured that it can generate sufficient economic benefits. Therefore, in this application, the secondary optimization objective function model of energy storage configuration is established based on the maximum operating benefit function of the energy storage system, and its objective function can be expressed as: Goal2 = max(C 21 +C 22 -C 23 +C 24 );

[0067] in Represents the revenue from electricity purchase and sale of the energy storage system;

[0068] in Indicates the charging and discharging benefits of the energy storage system;

[0069] in Represents the loss cost of the energy storage system;

[0070] in Represents the power generation income of the energy storage system;

[0071] where η sell.t represents the unit price of electricity sold by the energy storage system at time t, η buy represents the unit price of electricity purchased by the energy storage system at time t, P sell.t represents the power sales of the energy storage system at time t, P buy.t represents the amount of electricity purchased by the energy storage system at time t, T represents the total number of hours per year; N cn Represents the total number of energy storage systems, m t represents the electricity price at time t, Pi.t.dis represents the discharge power of the i-th energy storage system at time t, P i.t.ch represents the charging power of the i-th energy storage system at time t, Δt dis Denotes the discharge period, Δt ch Indicates the charging cycle; C year Represents the annual operating cost per unit power of the energy storage system, C k represents the unit price of the k-th type of renewable energy power generation subsidy, P k represents the kth type of renewable energy power generation, K represents the renewable energy category;

[0072] B2. Establish a secondary optimization target constraint model for energy storage configuration;

[0073] The energy storage configuration secondary optimization objective constraint model is established based on the energy storage system power balance, installed capacity and power constraints, and line transmission capacity constraints, and can be specifically expressed as:

[0074]

[0075] Where f1' represents the power balance constraint of the energy storage system, and P k.t represents the output power of the kth generation node at time t, P tran.t represents the exchange power between the energy storage system and the power grid; f2' and f3' represent the system installed capacity constraint and power constraint, where S p Represents the installed power of the energy storage system, S p.max Represents the installed power limit of the energy storage system, where S z Represents the installed capacity of the energy storage system, S z.max represents the installed capacity limit of the energy storage system; f4' represents the network transmission capacity constraint of the energy storage system, where U t represents the energy storage system transmission power at time t, U t.min represents the lower limit of the energy storage system transmission power at time t, U t.max represents the upper limit of the energy storage system transmission power at time t;

[0076] Step 3. Determine the optimization evaluation index of energy storage configuration optimization target;

[0077] The energy storage configuration optimization target optimization evaluation index is established based on the self-balancing index and load supply index of the distribution network where the energy storage system is located, and its evaluation function can be expressed as Test1=λ1T1-λ2T2;

[0078] in represents the power self-supply index, where Q self Indicates the amount of electricity in the energy storage system used to meet its own power load, Q all Indicates the total amount of electricity required for the stable operation of the energy storage system itself;

[0079] in represents the power supply reliability index; where λ1∈[0,1] and λ2∈[0,1] refer to the normalized index weights;

[0080] Step 4. Determine the energy storage system operation configuration based on the optimal configuration

[0081] According to the aforementioned steps one and two, the energy storage system configuration parameters that meet the primary optimization objectives and secondary optimization objectives of the energy storage configuration are determined. Based on step two, several optimal energy storage system configuration parameter schemes are determined as alternative schemes, and the selection is made according to the operation focus and actual operation status of the energy storage system.

[0082] On the basis of the above steps, the optimal operation strategy is determined by optimizing the operation mode of the energy storage system. The present invention further provides a configuration optimization operation method of the energy storage system, which specifically includes:

[0083] D1. Calculate the output power P of various power generation nodes in the energy storage system based on the current configuration parameters k.t , calculate the power difference If ΔP t >0, then turn to D2, if ΔP t <0, go to D3;

[0084] D2. If the real-time electricity price is low or medium, the SOC of the battery in the energy storage module t ≤SOC max , and ΔP t ≤P ch.t.max When ΔP t >P ch.t.max , and the real-time electricity price is at a low or medium price, the output of various power generation nodes is used to power the load in the energy storage system and charge the energy storage battery, and the remaining electricity is sold to the grid; if ΔP t >P ch.t.max , the real-time electricity price is at the peak price, if SOC t ≤SOC min , the output of various power generation nodes is used to power the loads in the energy storage system and charge the energy storage batteries until SOC t ≥SOC t.set and sell the remaining electricity to the grid, where SOC t.set Refers to the preset safety power at time t; if ΔP t >P ch.t.max , the real-time electricity price is at the peak price, if SOC t ≥SOC t.min , selling the output of various power generation nodes to the power grid;

[0085] D3, if SOCt <SOC min And ΔP t >P ch.t.max , start the energy storage system power purchase and storage program, use the output of various power generation nodes to charge the energy storage system, and the remaining shortfall is met by purchasing electricity. If the real-time electricity price is at the peak price, charge until SOC t ≥SOC min If the real-time electricity price is low or medium, charge until SOC t ≥SOC t.set ;

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention, rather than to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the essence and scope of the technical solution of the present invention.

Claims

1. A method for optimizing configuration of an energy storage system, characterized in that: The steps include: Step 1. Determine the main target optimization configuration, including: A1. Establish the main optimization objective function model of energy storage configuration; Establish the main optimization objective function model of energy storage configuration based on the minimum energy storage configuration cost function; A2. Establish the main optimization objective constraint model of energy storage configuration; The main optimization objective constraint model of energy storage configuration is established based on the charging and discharging and capacity and power parameters of the energy storage system. Step 2. Determine the secondary objective constraints in combination with the optimization configuration, including: B1. Establishing the secondary optimization objective function model of energy storage configuration; The optimal capacity configuration of the energy storage system is determined based on the main optimization objective function of energy storage configuration. On this basis, a secondary optimization objective function model is established based on the maximum operating benefit function of the energy storage system and the secondary optimization objective function model of energy storage configuration. B2. Establish a secondary optimization target constraint model for energy storage configuration; The energy storage configuration secondary optimization objective constraint model is established based on the energy storage system power balance, installed capacity and power constraints, and line transmission capacity constraints. Step 3. Determine the optimization evaluation index of energy storage configuration optimization target; The energy storage configuration optimization target optimization evaluation index is established based on the self-balancing index and load supply index of the distribution network where the energy storage system is located; Step 4. Determine the energy storage system operation configuration based on the optimal configuration According to the aforementioned steps one and two, the energy storage system configuration parameters that meet the primary optimization objectives and secondary optimization objectives of the energy storage configuration are determined. Based on step two, several optimal energy storage system configuration parameter schemes are determined as alternative schemes, and the selection is made according to the operation focus and actual operation status of the energy storage system.

2. The method for optimizing configuration of an energy storage system according to claim 1, characterized in that: The main optimization objective function model of energy storage configuration is established based on the minimum energy storage configuration cost function, which can be expressed as Goal1=min(C1+C2+C3); in represents the cost of the asset; It represents the fixed input cost of assets; C 12 =C price P ed represents the energy conversion cost of the energy storage system; C 13 =C wh E ed represents the capacity maintenance cost of the energy storage system; Among them C p represents the unit power cost, C e represents the unit capacity cost, P ed Indicates rated power, E ed represents the rated capacity, r represents the interest rate, n is the operation cycle of the energy storage system, C price is the unit power cost of the energy storage conversion device, C wh Express the maintenance cost per unit capacity of the energy storage system; Where C2=μ2W cf represents the charging and discharging operation and maintenance cost of the energy storage system, μ2 represents the operation and maintenance cost coefficient, and W cf Indicates the annual charge and discharge capacity of the energy storage system; in represents the energy storage system storage module update cost, C batin represents the initial cost of the energy storage module, and t3 represents the operating life of the energy storage module.

3. The method for optimizing configuration of an energy storage system according to claim 1, characterized in that: The main optimization objective constraint model of energy storage configuration is established based on the charging and discharging and capacity and power parameters of the energy storage system, which can be specifically expressed as: Where f1 represents the remaining capacity of the energy storage battery, SOC min Refers to the minimum remaining capacity limit of the energy storage battery, SOC max Refers to the maximum remaining capacity limit of the energy storage battery, SOC t refers to the remaining capacity of the energy storage battery at time t; f2 represents the charging power constraint of the energy storage module, P ch.t.min represents the minimum charging power limit at time t, P ch.t.max represents the maximum charging power limit at time t, P ch.t represents the charging power at time t; f3 represents the energy storage module discharge power constraint, P pu.t.min represents the minimum discharge rate limit at time t, P pu.t.max Indicates the maximum discharge power limit at time t, P pu.t represents the discharge power at time t; f4 represents the system power constraint, f5 represents the system capacity constraint, P t represents the energy storage system power at time t, E t represents the capacity of the energy storage system at time t, P max Indicates the maximum allowable power of the system, E max Indicates the maximum allowable capacity of the system.

4. The method for optimizing configuration of an energy storage system according to claim 2, characterized in that: The secondary optimization objective function model established based on the maximum operating benefit function of the energy storage system can be expressed as: Goal2 = max(C 21 +C 22 -C 23 +C 24 ); in Represents the revenue from electricity purchase and sale of the energy storage system; in Indicates the charging and discharging benefits of the energy storage system; in Represents the loss cost of the energy storage system; in represents the power generation income of the energy storage system; where η sell.t represents the unit price of electricity sold by the energy storage system at time t, η buy represents the unit price of electricity purchased by the energy storage system at time t, P sell.t represents the power sales of the energy storage system at time t, P buy.t represents the amount of electricity purchased by the energy storage system at time t, T represents the total number of hours per year; N cn Represents the total number of energy storage systems, m t represents the electricity price at time t, P i.t.dis represents the discharge power of the i-th energy storage system at time t, P i.t.ch represents the charging power of the i-th energy storage system at time t, Δt dis Represents the discharge period, Δt ch Indicates the charging cycle; C year Represents the annual operating cost per unit power of the energy storage system, C k represents the unit price of the k-th type of renewable energy power generation subsidy, P k It represents the power generation of the kth type of renewable energy, and K represents the category of renewable energy.

5. The method for optimizing configuration of an energy storage system according to claim 1, characterized in that: The target constraint model established based on the self-balancing index and load supply index of the distribution network where the energy storage system is located can be specifically expressed as: Where f1' represents the power balance constraint of the energy storage system, and P k.t represents the output power of the kth generation node at time t, P tran.t represents the exchange power between the energy storage system and the power grid; f2' and f3' represent the system installed capacity constraint and power constraint, where S p Represents the installed power of the energy storage system, S p.max Represents the installed power limit of the energy storage system, where S z Represents the installed capacity of the energy storage system, S z.max represents the installed capacity limit of the energy storage system; f4' represents the network transmission capacity constraint of the energy storage system, where U t represents the energy storage system transmission power at time t, U t.min represents the lower limit of the energy storage system transmission power at time t, U t.max Indicates the upper limit of the energy storage system transmission power at time t.

6. The method for optimizing configuration of an energy storage system according to claim 1, characterized in that: The evaluation function established based on the self-balancing index and the load supply index can be expressed as Test1 = λ1T1-λ2T2; in represents the power self-supply index, where Q self Indicates the amount of electricity in the energy storage system used to meet its own power load, Q all Indicates the total amount of electricity required for the stable operation of the energy storage system itself; in represents the power supply reliability index; where λ1∈[0,1] and λ2∈[0,1] refer to the normalized indicator weights.

7. The method for optimizing the operation of the energy storage system according to claim 6, characterized in that: The optimal operation strategy is determined by optimizing the operation mode of the energy storage system, which includes the following steps: D1. Calculate the output power P of various power generation nodes in the energy storage system based on the current configuration parameters k.t , calculate the power difference If ΔP t >0, then turn to D2, if ΔP t <0, go to D3; D2. If the real-time electricity price is low or medium, the SOC of the battery in the energy storage module t ≤SOC max , and ΔP t ≤P ch.t.max When ΔP t >P ch.t.max , and the real-time electricity price is at a low or medium price, the output of various power generation nodes is used to power the load in the energy storage system and charge the energy storage battery, and the remaining electricity is sold to the grid; if ΔP t >P ch.t.max , the real-time electricity price is at the peak price, if SOC t ≤SOC min , the output of various power generation nodes is used to power the loads in the energy storage system and charge the energy storage batteries until SOC t ≥SOC t.set and sell the remaining electricity to the grid, where SOC t.set Refers to the preset safe power at time t; if ΔP t >P ch.t.max , the real-time electricity price is at the peak price, if SOC t ≥SOC t.min , selling the output of various power generation nodes to the power grid; D3, if SOC t <SOC min And ΔP t >P ch.t.max , start the energy storage system power purchase and storage program, use the output of various power generation nodes to charge the energy storage system, and the remaining shortfall is met by purchasing electricity. If the real-time electricity price is at the peak price, charge until SOC t ≥SOC min If the real-time electricity price is low or medium, charge until SOC t ≥SOC t.set .

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