System distribution and storage method considering energy storage frequency support characteristics

Abstract

The invention provides a system distribution and storage method considering an energy storage frequency support characteristic, and the method comprises the steps: firstly, building a target function with the minimum annual operation cost of a system based on a power system unit combination operation constraint and a short-time frequency safety constraint; and secondly, considering frequency response characteristics of energy storage in short-time frequency security constraints, adding an energy storage capacity planning equation, constructing a target function with the minimum energy storage capacity, and finally, comprehensively solving to obtain an optimal energy storage planning scheme. According to the method, the safety requirement of the system for the energy storage frequency supporting effect can be accurately determined, the optimal energy storage investment capacity is decided, and therefore the inertia and frequency stability of the power system is enhanced through the energy storage technology.

Description

Technical Field

[0001] The present invention belongs to the field of energy storage system planning models, and in particular proposes a system storage allocation method that takes into account energy storage frequency support characteristics. Background Art

[0002] As global warming gradually intensifies, carbon emissions have become a global problem. However, the increase in the penetration rate of new energy has led to low inertia and frequency stability problems in the power system. The fundamental reason is that the structure of new energy units is different from that of traditional thermal power units, and they lack rotational inertia during operation. This reduction in inertia leads to frequency stability problems. In addition, there is a strong intermittent nature in the output of new energy, and wind power output is concentrated in time periods with low power load demand. The unabsorbed new energy power will have a strong impact on the stability of the power system. Based on the above description, the energy storage planning model proposed in the present invention mainly considers the following two aspects: First, based on the combined operation constraints of the power system units and the short-term frequency safety constraints, the annual operation plan of the power system is optimized and scheduled; second, the frequency response characteristics of energy storage are considered in the short-term frequency safety constraints, and the energy storage capacity planning equation is added to decide the optimal storage allocation plan. Summary of the invention

[0003] Purpose of the invention: The technical problem to be solved by the present invention is to overcome the problem that the existing planning model does not adequately explore the frequency characteristics of energy storage, and propose a system storage allocation scheme that takes into account the frequency support characteristics of energy storage. The present invention introduces short-term frequency safety constraints into the planning model to plan a storage allocation scheme for the system. The present invention can plan the optimal energy storage capacity configuration scheme to improve the inertia and frequency stability of the power system.

[0004] Technical solution: In order to solve the above technical problems, the present invention proposes a system storage configuration method considering the frequency support characteristics of energy storage, which includes the following steps:

[0005] Step 1: Obtain the operation parameters of the example system, including the output parameters of the thermal power unit, the frequency response index of the thermal power unit, the frequency response index of the new energy unit, the maximum frequency drop rate that the system can withstand, the system frequency low point, and the system quasi-steady-state frequency;

[0006] Step 2: Obtain power load, new energy output data, and system real-time frequency safety indicators;

[0007] Step 3: with respect to the operating parameters, output information of thermal power units and new energy units, and system frequency safety indicators, the power system unit combination operation constraints and short-term frequency safety constraints are used as constraint conditions;

[0008] Step 4: Add the energy storage capacity planning equation to the constraints described in step 3, and use the energy storage capacity planning equation, unit combination operation constraints, and short-term frequency safety constraints as constraints, and use the minimum annual overall operating cost of the system and the minimum energy storage planning capacity as the objective function. Use the GUROBI solver to solve the optimal solution and plan the optimal energy storage capacity configuration plan for the system.

[0009] Furthermore, in step 3, the power system unit combination operation constraints are as follows:

[0010]

[0011] In the formula, t is each time period, y is each typical day, g is each thermal power unit, r is each new energy unit, e is each energy storage unit, P g,t,y Indicates the real-time output of thermal power units on each typical day, Indicates the maximum output of each thermal power unit, Indicates the minimum output of each thermal power unit, Indicates the real-time operating status of each typical day thermal power unit. Indicates the real-time startup status of thermal power units on each typical day. Indicates the real-time shutdown status of each typical day thermal power unit. Indicates the start time of each thermal power unit. Indicates the downtime of each thermal power unit. Indicates the climbing power of each thermal power unit, P r,t,y Indicates the real-time output of each typical day's new energy unit, Indicates the maximum output of renewable energy on each typical day, Indicates the real-time power load on each typical day, represents the dual variable of the power balance equation, Indicates the real-time discharge power of energy storage on each typical day, Indicates the real-time charging power of energy storage on each typical day.

[0012] Furthermore, in step 3, the short-term frequency safety constraints are as follows:

[0013]

[0014]

[0015] In the formula, Indicates the real-time enhanced frequency response power of the system on each typical day, Indicates the real-time frequency regulation decision status of energy storage on each typical day, Indicates the real-time frequency regulation decision status of each typical day thermal power unit, EFR e,t,y Indicates the real-time enhanced frequency response power of energy storage on each typical day, EFR g,t,yIndicates the real-time enhanced frequency response power of each typical day thermal power unit, represents the dual variable of the enhanced frequency response equation, Indicates the real-time primary frequency modulation response power of the system on each typical day, PFR e,t,y Indicates the real-time primary frequency regulation response power of energy storage on each typical day, PFR g,t,y It indicates the real-time primary frequency regulation response power of each typical day thermal power unit. represents the dual variable of the primary frequency modulation response equation, represents the real-time inertia of the system on each typical day, H g,t,y It represents the real-time inertial support of each typical day thermal power unit, H e,t,y represents the real-time inertial support of energy storage on each typical day, H r,t,y It represents the real-time inertia time constant of each typical day’s new energy generating unit, Represents the inherent inertia time constant of each new energy unit, represents the real-time droop control coefficient of the system on each typical day, D g,t,y represents the real-time droop control coefficient of each typical day thermal power unit, D e,t,y represents the real-time droop control coefficient of energy storage on each typical day, D r,t,y It represents the real-time droop control coefficient of each typical day’s renewable energy unit, It represents the inherent droop control coefficient of each renewable energy unit. represents the system minimum droop control coefficient, Indicates the real-time charging status of energy storage on each typical day. Indicates the real-time discharge status of energy storage on each typical day, represents the dual variable of the system inertia equation, Δf max Indicates the maximum frequency drop of the system. represents the constant coefficient of the frequency safety margin equation, represents the inertia term coefficient of the frequency safety margin equation, represents the droop term coefficient of the frequency safety margin equation, represents the real-time frequency safety margin of each typical day, f0 represents the system reference frequency, Indicates the real-time unbalanced power of each typical day, RoCoF max Indicates the maximum frequency drop rate that the system can withstand. represents the dual variable of the RoCoF equation, represents the real-time disturbance power of each typical day, represents the dual variable of the QSS equation, T EFR represents the enhanced frequency response time, T PFR Indicates the response time of a frequency modulation response. Represents the dual variable of the frequency low-point equation.

[0016] Furthermore, in step 4, the objective function is to minimize the annual overall operating cost of the system and the minimum planned energy storage capacity as follows:

[0017] cost=C inv +C ope (A-23)

[0018]

[0019] In the formula, e represents each energy storage unit in the system, y represents each typical day, t represents each scheduling time period within the day, and C inv represents the total energy storage investment cost, C ope represents the annual operating cost of the system, represents the energy storage construction cost coefficient, S e represents the planned energy storage capacity, represents the number of typical days, c E represents the electricity cost coefficient, c H represents the inertia cost coefficient, c EFR represents the power cost coefficient of enhanced frequency response, c PFR represents the power cost coefficient of primary frequency modulation response, P g,t,y represents the real-time output of thermal power units on each typical day, P r,t,y represents the real-time output of each typical day’s renewable energy unit, P e,t,y Indicates the real-time energy storage capacity of each scenario, H g,t,y It represents the real-time inertial support of each typical day thermal power unit, H r,t,y It represents the real-time inertial support of each typical day’s new energy unit, H e,t,y Indicates the real-time inertial support of energy storage on each typical day, EFR g,t,y Indicates the real-time enhanced frequency response power of each typical day thermal power unit, EFR e,t,y Indicates the real-time enhanced frequency response power of energy storage on each typical day, PFR g,t,y Indicates the real-time primary frequency regulation response power of each typical day thermal power unit, PFR e,t,y Indicates the real-time primary frequency regulation response power of energy storage on each typical day.

[0020] Furthermore, in step 4, the energy storage capacity planning equation is as follows:

[0021]

[0022]

[0023] In the formula, S e,t,y represents the real-time energy storage capacity demand on each typical day, Represents the capacity limit of a single energy storage system, S cap Indicates the total capacity limit, Indicates the real-time minimum discharge power of energy storage on each typical day, Indicates the real-time maximum discharge power of energy storage on each typical day, Indicates the real-time minimum charging power of energy storage on each typical day, Indicates the real-time maximum charging power of energy storage on each typical day, S e,y represents the energy storage capacity planning results for each typical day, S e represents the final planning result of energy storage, ρ y represents the weight of each typical day, Indicates the real-time charging status of energy storage on each typical day. Indicates the real-time discharge status of energy storage on each typical day, Indicates the number of energy storage charging state switching times, Indicates the number of energy storage discharge state switching, P e,t,y Indicates the real-time electric energy of energy storage on each typical day, represents the initial energy storage capacity for each typical day, Indicates the final amount of energy stored on each typical day, Indicates the real-time discharge power of energy storage on each typical day, Indicates the real-time charging power of energy storage on each typical day.

[0024] Beneficial effects: Compared with the prior art, the technical solution of the present invention has the following beneficial technical effects:

[0025] The present invention introduces a short-term frequency safety constraint that takes into account the frequency support characteristics of energy storage into the planning model to plan a storage allocation plan for the system; the present invention can plan an optimal energy storage capacity configuration plan to maintain the frequency stability of a high-proportion new energy system. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of the method of the present invention.

[0027] Figure 2 This is a system calculation example diagram.

[0028] Figure 3 It is a comparison chart of planning results whether the planning model introduces short-term frequency safety constraints.

[0029] Figure 4 It is a comparison chart of the inertia of the planning model whether the short-time frequency safety constraint system is introduced, which reflects the superiority of the planning model in terms of the inertia of the supporting system. DETAILED DESCRIPTION

[0030] The present invention is further explained below in conjunction with the accompanying drawings and specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. After reading the present invention, various equivalent modifications of the present invention by those skilled in the art all fall within the scope defined by the claims attached to this application.

[0031] like Figure 1 As shown, the present invention proposes a system storage configuration method considering the frequency support characteristics of energy storage, the method comprising the following steps:

[0032] Step 1: Obtain the operation parameters of the example system, including the output parameters of the thermal power unit, the frequency response index of the thermal power unit, the frequency response index of the new energy unit, the maximum frequency drop rate that the system can withstand, the system frequency low point, and the system quasi-steady-state frequency;

[0033] Step 2: Obtain power load, new energy output data, and system real-time frequency safety indicators;

[0034] Step 3: with respect to the operating parameters, output information of thermal power units and new energy units, and system frequency safety indicators, the power system unit combination operation constraints and short-term frequency safety constraints are used as constraint conditions;

[0035] Step 4: Add the energy storage capacity planning equation to the constraints described in step 3, and use the energy storage capacity planning equation, unit combination operation constraints, and short-term frequency safety constraints as constraints, and use the minimum annual overall operating cost of the system and the minimum energy storage planning capacity as the objective function. Use the GUROBI solver to solve the optimal solution and plan the optimal energy storage capacity configuration plan for the system.

[0036] Furthermore, in step 3, the power system unit combination operation constraints are as follows:

[0037]

[0038]

[0039] In the formula, t is each time period, y is each typical day, g is each thermal power unit, r is each new energy unit, e is each energy storage unit, P g,t,y Indicates the real-time output of thermal power units on each typical day, Indicates the maximum output of each thermal power unit, Indicates the minimum output of each thermal power unit, Indicates the real-time operating status of each typical day thermal power unit. Indicates the real-time startup status of thermal power units on each typical day. Indicates the real-time shutdown status of each typical day thermal power unit. Indicates the start time of each thermal power unit. Indicates the downtime of each thermal power unit. Indicates the climbing power of each thermal power unit, P r,t,y Indicates the real-time output of each typical day's new energy unit, Indicates the maximum output of renewable energy on each typical day, Indicates the real-time power load on each typical day, represents the dual variable of the power balance equation, Indicates the real-time discharge power of energy storage on each typical day, Indicates the real-time charging power of energy storage on each typical day.

[0040] Furthermore, in step 3, the short-term frequency safety constraints are as follows:

[0041]

[0042]

[0043] In the formula, Indicates the real-time enhanced frequency response power of the system on each typical day, Indicates the real-time frequency regulation decision status of energy storage on each typical day, Indicates the real-time frequency regulation decision status of each typical day thermal power unit, EFR e,t,y Indicates the real-time enhanced frequency response power of energy storage on each typical day, EFR g,t,y Indicates the real-time enhanced frequency response power of each typical day thermal power unit, represents the dual variable of the enhanced frequency response equation, Indicates the real-time primary frequency modulation response power of the system on each typical day, PFR e,t,y Indicates the real-time primary frequency regulation response power of energy storage on each typical day, PFR g,t,y It indicates the real-time primary frequency regulation response power of each typical day thermal power unit. represents the dual variable of the primary frequency modulation response equation, represents the real-time inertia of the system on each typical day, H g,t,y It represents the real-time inertial support of each typical day thermal power unit, H e,t,y represents the real-time inertial support of energy storage on each typical day, H r,t,y It represents the real-time inertia time constant of each typical day’s new energy generating unit, Represents the inherent inertia time constant of each new energy unit, represents the real-time droop control coefficient of the system on each typical day, D g,t,y represents the real-time droop control coefficient of each typical day thermal power unit, D e,t,y represents the real-time droop control coefficient of energy storage on each typical day, D r,t,y It represents the real-time droop control coefficient of each typical day’s renewable energy unit, It represents the inherent droop control coefficient of each renewable energy unit. represents the system minimum droop control coefficient, Indicates the real-time charging status of energy storage on each typical day. Indicates the real-time discharge status of energy storage on each typical day, represents the dual variable of the system inertia equation, Δf maxIndicates the maximum frequency drop of the system. represents the constant coefficient of the frequency safety margin equation, represents the inertia term coefficient of the frequency safety margin equation, represents the droop term coefficient of the frequency safety margin equation, represents the real-time frequency safety margin of each typical day, f0 represents the system reference frequency, Indicates the real-time unbalanced power of each typical day, RoCoF max Indicates the maximum frequency drop rate that the system can withstand. represents the dual variable of the RoCoF equation, represents the real-time disturbance power of each typical day, represents the dual variable of the QSS equation, T EFR represents the enhanced frequency response time, T PFR Indicates the response time of a frequency modulation response. Represents the dual variable of the frequency low-point equation.

[0044] Furthermore, in step 4, the objective function is to minimize the annual overall operating cost of the system and the minimum planned energy storage capacity as follows:

[0045] cost=C inv +C ope (A-23)

[0046]

[0047] In the formula, e represents each energy storage unit in the system, y represents each typical day, t represents each scheduling time period within the day, and C inv represents the total energy storage investment cost, C ope represents the annual operating cost of the system, represents the energy storage construction cost coefficient, S e represents the planned energy storage capacity, represents the number of typical days, c E represents the electricity cost coefficient, c H represents the inertia cost coefficient, c EFR represents the power cost coefficient of enhanced frequency response, c PFR represents the power cost coefficient of primary frequency modulation response, P g,t,y represents the real-time output of thermal power units on each typical day, P r,t,y represents the real-time output of each typical day’s renewable energy unit, P e,t,y Indicates the real-time energy storage capacity of each scenario, H g,t,y It represents the real-time inertial support of each typical day thermal power unit, H r,t,y It represents the real-time inertial support of each typical day’s new energy unit, H e,t,y Indicates the real-time inertial support of energy storage on each typical day, EFRg,t,y Indicates the real-time enhanced frequency response power of each typical day thermal power unit, EFR e,t,y Indicates the real-time enhanced frequency response power of energy storage on each typical day, PFR g,t,y Indicates the real-time primary frequency regulation response power of each typical day thermal power unit, PFR e,t,y Indicates the real-time primary frequency regulation response power of energy storage on each typical day.

[0048] Furthermore, in step 4, the energy storage capacity planning equation is as follows:

[0049]

[0050]

[0051]

[0052]

[0053] In the formula, S e,t,y represents the real-time energy storage capacity demand on each typical day, Represents the capacity limit of a single energy storage system, S cap Indicates the total capacity limit, Indicates the real-time minimum discharge power of energy storage on each typical day, Indicates the real-time maximum discharge power of energy storage on each typical day, Indicates the real-time minimum charging power of energy storage on each typical day, Indicates the real-time maximum charging power of energy storage on each typical day, S e,y represents the energy storage capacity planning results for each typical day, S e represents the final planning result of energy storage, ρ y represents the weight of each typical day, Indicates the real-time charging status of energy storage on each typical day. Indicates the real-time discharge status of energy storage on each typical day, Indicates the number of energy storage charging state switching times, Indicates the number of energy storage discharge state switching, P e,t,y Indicates the real-time electric energy of energy storage on each typical day, represents the initial energy storage capacity for each typical day, Indicates the final amount of energy stored on each typical day, Indicates the real-time discharge power of energy storage on each typical day, Indicates the real-time charging power of energy storage on each typical day.

[0054] Case Analysis

[0055] The present invention adopts the IEEE-30 node power system transformation calculation. The thermal power units are connected to the power system nodes 1, 2, 22, 27, 23, and 13 respectively. The wind turbines are connected to the power system nodes 7 and 11. Photovoltaic unit b is connected to the power system nodes 19 and 29. The total installed capacity of the power system is 735MW, of which the installed capacity of wind turbines is 200MW, accounting for 27.2% of the total installed capacity, and the installed capacity of photovoltaic units is 200MW, accounting for 27.2% of the total installed capacity. The penetration rate of new energy is 54.4%. The present invention is implemented through the GAMS optimization platform and the GUROBI solver is used to solve the MILP problem.

[0056] Based on this example, the method of the present invention is used to determine the system storage solution, promoting the construction of more energy storage capacity to support the frequency stability of the high-proportion new energy system. The results are shown in Figure 3 , and the support effect of introducing frequency security constraints that consider the short-term frequency support characteristics of energy storage in the planning model on the real-time inertia of the power system is given. The results are shown in Figure 4 . It is explained that under the condition of considering the supporting role of energy storage frequency regulation, compared with the traditional planning model, the present invention can promote more investment in energy storage capacity to support the frequency stability and inertia of a high-proportion new energy system. Based on the energy storage planning model, the present invention establishes a system storage solution that considers the frequency support characteristics of energy storage based on the combined operation constraints of the power system units and the short-term frequency safety constraints.

[0057] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention.

Claims

1. A system storage allocation method considering the frequency support characteristics of energy storage, characterized in that: The method comprises the following steps: Step 1: Obtain the operation parameters of the example system, including the output parameters of the thermal power unit, the frequency response index of the thermal power unit, the frequency response index of the new energy unit, the maximum frequency drop rate that the system can withstand, the system frequency low point, and the system quasi-steady-state frequency; Step 2: Obtain power load, new energy output data, and system real-time frequency safety indicators; Step 3: with respect to the operating parameters, output information of thermal power units and new energy units, and system frequency safety indicators, the power system unit combination operation constraints and short-term frequency safety constraints are used as constraint conditions; Step 4: Add the energy storage capacity planning equation to the constraints described in step 3, and use the energy storage capacity planning equation, unit combination operation constraints, and short-term frequency safety constraints as constraints, and use the minimum annual overall operating cost of the system and the minimum energy storage planning capacity as the objective function. Use the GUROBI solver to solve the optimal solution and plan the optimal energy storage capacity configuration plan for the system.

2. A system storage allocation method considering energy storage frequency support characteristics according to claim 1, characterized in that: In step 3, the combined operation constraints of the power system units are as follows: In the formula, t is each time period, y is each typical day, g is each thermal power unit, r is each new energy unit, e is each energy storage unit, P g,t,y Indicates the real-time output of thermal power units on each typical day, Indicates the maximum output of each thermal power unit, Indicates the minimum output of each thermal power unit, Indicates the real-time operating status of each typical day thermal power unit. Indicates the real-time startup status of thermal power units on each typical day. Indicates the real-time shutdown status of each typical day thermal power unit. Indicates the start time of each thermal power unit. Indicates the downtime of each thermal power unit. Indicates the climbing power of each thermal power unit, P r,t,y Indicates the real-time output of each typical day's new energy unit, Indicates the maximum output of renewable energy on each typical day, Indicates the real-time power load on each typical day, represents the dual variable of the power balance equation, Indicates the real-time discharge power of energy storage on each typical day, Indicates the real-time charging power of energy storage on each typical day.

3. A system storage allocation method considering energy storage frequency support characteristics according to claim 2, characterized in that: In step 3, the short-term frequency safety constraints are as follows: In the formula, Indicates the real-time enhanced frequency response power of the system on each typical day, Indicates the real-time frequency regulation decision status of energy storage on each typical day, Indicates the real-time frequency regulation decision status of each typical day thermal power unit, EFR e,t,y Indicates the real-time enhanced frequency response power of energy storage on each typical day, EFR g,t,y Indicates the real-time enhanced frequency response power of each typical day thermal power unit, represents the dual variable of the enhanced frequency response equation, Indicates the real-time primary frequency modulation response power of the system on each typical day, PFR e,t,y Indicates the real-time primary frequency regulation response power of energy storage on each typical day, PFR g,t,y It indicates the real-time primary frequency regulation response power of each typical day thermal power unit. represents the dual variable of the primary frequency modulation response equation, represents the real-time inertia of the system on each typical day, H g,t,y It represents the real-time inertial support of each typical day thermal power unit, H e,t,y represents the real-time inertial support of energy storage on each typical day, H r,t,y It represents the real-time inertia time constant of each typical day’s new energy generating unit, Represents the inherent inertia time constant of each new energy unit, represents the real-time droop control coefficient of the system on each typical day, D g,t,y represents the real-time droop control coefficient of each typical day thermal power unit, D e,t,y represents the real-time droop control coefficient of energy storage on each typical day, D r,t,y It represents the real-time droop control coefficient of each typical day’s renewable energy unit, It represents the inherent droop control coefficient of each renewable energy unit. represents the system minimum droop control coefficient, Indicates the real-time charging status of energy storage on each typical day. Indicates the real-time discharge status of energy storage on each typical day, represents the dual variable of the system inertia equation, Δf max Indicates the maximum frequency drop of the system. represents the constant coefficient of the frequency safety margin equation, represents the inertia term coefficient of the frequency safety margin equation, represents the droop term coefficient of the frequency safety margin equation, represents the real-time frequency safety margin of each typical day, f0 represents the system reference frequency, Indicates the real-time unbalanced power of each typical day, RoCoF max Indicates the maximum frequency drop rate that the system can withstand. represents the dual variable of the RoCoF equation, represents the real-time disturbance power of each typical day, represents the dual variable of the QSS equation, T EFR represents the enhanced frequency response time, T PFR Indicates the response time of a frequency modulation response. Represents the dual variable of the frequency low-point equation.

4. A system storage allocation method considering energy storage frequency support characteristics according to claim 3, characterized in that: In step 4, the objective function is to minimize the annual total operating cost of the system and the minimum planned energy storage capacity as follows: cost=C inv +C ope (A-23) In the formula, e represents each energy storage unit in the system, y represents each typical day, t represents each scheduling time period within the day, and C inv represents the total energy storage investment cost, C ope represents the annual operating cost of the system, represents the energy storage construction cost coefficient, S e represents the planned energy storage capacity, represents the number of typical days, c E represents the electricity cost coefficient, c H represents the inertia cost coefficient, c EFR represents the power cost coefficient of enhanced frequency response, c PFR represents the power cost coefficient of primary frequency modulation response, P g,t,y represents the real-time output of thermal power units on each typical day, P r,t,y represents the real-time output of each typical day’s renewable energy unit, P e,t,y Indicates the real-time electric energy of energy storage in each scenario, H g,t,y It represents the real-time inertial support of each typical day thermal power unit, H r,t,y It represents the real-time inertial support of each typical day’s new energy unit, H e,t,y Indicates the real-time inertial support of energy storage on each typical day, EFR g,t,y Indicates the real-time enhanced frequency response power of each typical day thermal power unit, EFR e,t,y Indicates the real-time enhanced frequency response power of energy storage on each typical day, PFR g,t,y Indicates the real-time primary frequency regulation response power of each typical day thermal power unit, PFR e,t,y Indicates the real-time primary frequency regulation response power of energy storage on each typical day.

5. A system storage allocation method considering energy storage frequency support characteristics according to claim 4, characterized in that: In step 4, the energy storage capacity planning equation is as follows: S e,y =max{S e,t,y }(A-32) In the formula, S e,t,y represents the real-time energy storage capacity demand on each typical day, Represents the capacity limit of a single energy storage system, S cap Indicates the total capacity limit, Indicates the real-time minimum discharge power of energy storage on each typical day, Indicates the real-time maximum discharge power of energy storage on each typical day, Indicates the real-time minimum charging power of energy storage on each typical day, Indicates the real-time maximum charging power of energy storage on each typical day, S e,y represents the energy storage capacity planning results for each typical day, S e represents the final planning result of energy storage, ρ y represents the weight of each typical day, Indicates the real-time charging status of energy storage on each typical day. Indicates the real-time discharge status of energy storage on each typical day, Indicates the number of energy storage charging state switching times, Indicates the number of energy storage discharge state switching, P e,t,y Indicates the real-time electric energy of energy storage on each typical day, represents the initial energy storage capacity for each typical day, Indicates the final amount of energy stored on each typical day, Indicates the real-time discharge power of energy storage on each typical day, Indicates the real-time charging power of energy storage on each typical day.

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