A method, system, electronic device, and medium for calculating the marginal benefit of energy storage regulation.

Abstract

This invention provides a method, system, electronic equipment, and medium for calculating the marginal benefit of energy storage regulation, belonging to the field of energy storage investment technology. The method includes the following steps: Step S1, constructing a multi-element energy storage optimization scheduling model based on new energy consumption; Step S2, inputting preset energy storage configuration capacities from small to large into the multi-element energy storage optimization scheduling model based on new energy consumption, and calculating the new energy consumption corresponding to different energy storage configuration capacities; Step S3, obtaining the marginal benefit of multi-element energy storage for new energy consumption by calculating the new energy consumption corresponding to a unit increase in energy storage capacity. This invention, employing the above-mentioned method, system, electronic equipment, and medium for calculating the marginal benefit of energy storage regulation, can specifically reflect the relationship between investment costs and consumption benefits, providing an effective reference standard for the construction of multi-element energy storage, and has practical engineering value.

Description

Technical Field

[0001] This invention relates to the field of energy storage investment technology, and in particular to a method, system, electronic device and medium for calculating the marginal revenue of energy storage regulation. Background Technology

[0002] As the proportion of new energy sources such as wind power and photovoltaics in the power system continues to rise, the volatility and intermittency of their output levels are becoming increasingly significant, making it difficult to accurately match power generation with load in real time, which in turn poses a serious challenge to the stability and economy of power system operation.

[0003] Energy storage technology, with its dual role as both a "power source" and a "load" and its rapid response capabilities, has become a key means to address this challenge. It can not only enable flexible transfer of electricity over time, effectively reducing the curtailment of wind and solar power and improving the absorption rate of renewable energy, but also significantly smooth the output of new energy sources and promote the smooth grid connection of renewable energy.

[0004] However, given the high volatility and randomness of intermittent renewable energy output such as wind and solar power, the deployment of a single energy storage technology in the power grid is no longer sufficient to meet the requirements of new power systems for a high proportion of renewable energy grid connection. Therefore, the combined use of multiple energy storage technologies is particularly important to minimize energy storage operating costs while meeting the grid connection needs of renewable energy.

[0005] Furthermore, the complexity of the power grid and the uncertainty of source and load characteristics make it difficult to balance economy and flexibility when deploying energy storage solutions, especially when considering the future multi-timescale energy storage regulation and control needs of the power grid. Therefore, how to formulate an economical and flexible energy storage deployment strategy under the background of unclear source and load characteristics and unknown evolution paths has become an urgent problem to be solved.

[0006] It is worth noting that existing research on diversified energy storage technologies for promoting renewable energy integration mostly focuses on improving renewable energy integration levels while neglecting the marginal benefits of energy storage investment. In-depth research on this issue not only has theoretical value but also significant guiding implications for practical applications. Therefore, we need to further optimize the application models and strategies of diversified energy storage technologies to more comprehensively improve the stability and economy of the power system. Summary of the Invention

[0007] The purpose of this invention is to provide a method, system, electronic device and medium for calculating the marginal benefit of energy storage regulation, which can provide effective support for the optimal configuration of energy storage capacity during construction and has practical engineering value. It can obtain the optimal energy storage capacity configuration strategy under the premise of fully considering the marginal benefit of promoting the consumption of new energy.

[0008] To achieve the above objectives, this invention provides a method for calculating the marginal benefit of energy storage regulation, comprising the following steps:

[0009] Step S1: Construct a multi-element energy storage optimization scheduling model based on new energy consumption;

[0010] Step S2: Input the preset energy storage configuration capacity from small to large into the multi-element energy storage optimization scheduling model based on new energy consumption, and calculate the new energy consumption corresponding to different energy storage configuration capacities;

[0011] Step S3: By calculating the amount of new energy consumption corresponding to the unit increase in energy storage capacity, we can obtain the marginal benefits of diversified energy storage for new energy consumption.

[0012] Preferably, in step S1, the objective function of the multi-element energy storage optimization scheduling model based on new energy consumption is as follows:

[0013] minF=min(C op +C p (1);

[0014] C op =C cd +C g (2);

[0015]

[0016] Where F represents the objective function; C op C p These represent the operating costs of energy storage and the costs of wind and solar curtailment, respectively; C cd,h C cd,b These represent the charge / discharge loss costs for hydrogen energy storage and electrochemical energy storage, respectively; c cd,eb c cd,fc These represent the unit charge / discharge loss cost of the electrolyzer and fuel cell, respectively. Let represent the electrolysis power of the electrolyzer and the output power of the fuel cell at time t of the i-th energy storage period, respectively. c represents the electrochemical energy storage charge / discharge power at time t of the i-th energy storage event; lw c lp These represent the penalty costs per unit of wind and solar power curtailment, respectively. These represent the maximum generating capacity and actual grid-connected power of the wind power at time t for the j-th renewable energy plant, respectively. These represent the maximum renewable energy output and the actual grid-connected power of the photovoltaic system at time t for the j-th renewable energy power plant, respectively. Δt represents the output power and cost of the z-th thermal power unit at time t, respectively; Δt represents the optimization time interval considered; N1 represents the maximum number of energy storage facilities; N2 represents the maximum number of thermal power units; N3 represents the maximum number of new energy power plants; and T represents the maximum value at time t.

[0017] Preferably, in step S1, the constraints of the multi-element energy storage optimization scheduling model based on new energy consumption include: system power balance constraints, hydrogen energy storage system operation characteristic constraints, electrochemical energy storage operation characteristic constraints, wind power and photovoltaic power output constraints, and upper and lower limits of grid-injected power constraints.

[0018] The system power balance constraints are as follows:

[0019]

[0020] in, Indicates the system load at time t; This represents the power injected into the upstream power grid at time t; This represents the actual grid-connected power of wind power at time t; This represents the actual grid-connected power of the photovoltaic system at time t; and Let represent the total charging and discharging power of the system's stored energy at time t; and Let represent the electrolysis power of the electrolyzer and the output power of the fuel cell at time t, respectively.

[0021] The operating characteristics constraints of the hydrogen energy storage system are as follows:

[0022]

[0023] Among them, V t EB ρ represents the volume of hydrogen produced by the electrolyzer at time t; EB λ represents the rated hydrogen production volume per unit of electricity consumed by the electrolyzer; EB V represents the electrolysis efficiency of the electrolytic cell. t FC ρ represents the volume of hydrogen consumed by the fuel cell at time t; FC This represents the rated power generation per unit volume of hydrogen consumed by a fuel cell; μ FC E represents the power generation efficiency of a fuel cell; hs,t and E hs,t+1 These represent the remaining hydrogen volumes in the hydrogen storage tank at time t and t+1, respectively. and N represents the volume of hydrogen gas added to and removed from the hydrogen storage tank at time t, respectively; eb Indicates the number of electrolytic cells; N fc N represents the number of fuel cells; hsIndicates the number of hydrogen storage tanks; These represent the hydrogen filling and discharging efficiencies of the hydrogen storage tank, respectively. These represent the rated power of a single electrolyzer and fuel cell, respectively. These represent 0-1 variables that restrict the hydrogen filling and discharging states of the hydrogen storage tank, respectively. These are 0-1 variables representing the hydrogen inlet and outlet states of the hydrogen storage tank, respectively. ε1 and ε2 represent the maximum capacity of a single hydrogen storage tank; ε1 and ε2 represent the ratios of the minimum and maximum allowable remaining capacity of the hydrogen storage tank to the total capacity during operation, respectively.

[0024] The operational characteristics of electrochemical energy storage are constrained as follows:

[0025] E t+1 =E t +(P t ch η-P t dis / η)Δt(10);

[0026] α1E max ≤E t ≤α2E max (11);

[0027]

[0028] Among them, E t E t+1 α1 and α2 represent the remaining energy of the electrochemical energy storage at times t and t+1, respectively; η represents the charge and discharge efficiency of the electrochemical energy storage; α1 and α2 represent the proportions of the minimum and maximum allowable remaining capacity to the total capacity during the operation of the electrochemical energy storage, respectively; β ch β dis E represents the 0-1 variables that restrict the charge and discharge states of electrochemical energy storage, respectively. max P represents the maximum energy storage capacity. max Indicates the maximum energy storage capacity;

[0029] The output constraints for wind power and solar power are as follows:

[0030] 0≤P t w,r ≤P t w (13);

[0031] 0≤P t pv,r ≤P t pv (14);

[0032] Among them, P t w Pt pv This represents the maximum output limit of wind power and photovoltaic units at time t;

[0033] The output power of the fuel cell is as follows:

[0034]

[0035] in, This indicates the upper limit of the power injected into the upper-level power grid.

[0036] Preferably, in step S3, the calculation formula for the marginal benefits of diversified energy storage for new energy consumption is as follows:

[0037]

[0038] Where M represents the incremental capacity and marginal benefits of multi-energy storage; ΔF and ΔC represent the incremental amount of new energy consumption and the incremental amount of energy storage capacity, respectively; F(C) represents the amount of new energy consumption of the system when the energy storage capacity is C; F(C+ΔC) represents the amount of new energy consumption of the system when the energy storage capacity is C+ΔC.

[0039] This invention also provides a system for calculating the marginal benefit of energy storage regulation, comprising:

[0040] An optimized scheduling model construction unit is used to build an optimized scheduling model for multi-element energy storage based on the consumption of new energy sources;

[0041] The energy storage configuration capacity adjustment unit is used to input the preset energy storage configuration capacity from small to large into the multi-element energy storage optimization scheduling model based on new energy consumption, and calculate the new energy consumption corresponding to different energy storage configuration capacities.

[0042] The marginal benefit calculation unit is used to calculate the amount of new energy consumption corresponding to the unit increase in energy storage capacity, so as to obtain the multi-dimensional marginal benefits of energy storage for new energy consumption.

[0043] The present invention also provides a computer device, including: a memory and a processor; the memory stores a computer program, and the processor executes the computer program to perform the steps of the above-described method for calculating the marginal benefit of energy storage regulation.

[0044] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described method for calculating the marginal benefit of energy storage regulation.

[0045] Therefore, the present invention employs the above-mentioned method, system, electronic device, and medium for calculating the marginal benefit of energy storage regulation, and the beneficial technical effects are as follows:

[0046] (1) This invention takes the marginal benefits of energy storage investment as the basis for investment, which can improve the rationality and efficiency of energy storage investment while promoting the consumption of new energy.

[0047] (2) This invention can specifically reflect the relationship between investment costs and absorption benefits, providing an effective reference standard for the construction of diversified energy storage, and has practical engineering value. Attached Figure Description

[0048] Figure 1 This is a flowchart of a method for calculating the marginal benefit of energy storage regulation according to the present invention;

[0049] Figure 2 This is a graph showing the trend of the curtailment rate as a function of the energy storage configuration capacity in this invention.

[0050] Figure 3 This is a diagram illustrating the marginal benefits of renewable energy consumption in energy storage promotion systems under different energy storage construction scales in this invention. Detailed Implementation

[0051] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0052] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0053] Example 1

[0054] like Figure 1 As shown in the flowchart, a method for calculating the marginal benefit of energy storage regulation according to the present invention includes the following steps:

[0055] Step S1: Given the basic operating parameters of the system (energy storage system), including load data, conventional unit output data, and renewable energy installed capacity; given the energy storage investment cost C, determine the selection of energy storage equipment and the multi-source energy storage capacity E. ess ;

[0056] Step S2: Construct a multi-element energy storage optimization scheduling model based on new energy consumption;

[0057] The objective function of the multi-element energy storage optimization scheduling model based on renewable energy consumption is as follows:

[0058] minF=min(C op +C p (1);

[0059] C op =C cd +C g (2);

[0060]

[0061] Where F represents the objective function; C op C p These represent the operating costs of energy storage and the costs of wind and solar curtailment, respectively; C cd,h C cd,b These represent the charge / discharge loss costs for hydrogen energy storage and electrochemical energy storage, respectively; c cd,eb c cd,fc These represent the unit charge / discharge loss cost of the electrolyzer and fuel cell, respectively. Let represent the electrolysis power of the electrolyzer and the output power of the fuel cell at time t of the i-th energy storage period, respectively. c represents the electrochemical energy storage charge / discharge power at time t of the i-th energy storage event; lw c lp These represent the penalty costs per unit of wind and solar power curtailment, respectively. These represent the maximum generating capacity and actual grid-connected power of the wind power at time t for the j-th renewable energy plant, respectively. These represent the maximum renewable energy output and the actual grid-connected power of the photovoltaic system at time t for the j-th renewable energy power plant, respectively. Δt represents the output power and cost of the z-th thermal power unit at time t, respectively; Δt represents the optimization time interval considered; N1 represents the maximum number of energy storage facilities; N2 represents the maximum number of thermal power units; N3 represents the maximum number of new energy power plants; and T represents the maximum value at time t.

[0062] The constraints of the multi-element energy storage optimization scheduling model based on new energy consumption include: system power balance constraints, hydrogen energy storage system operation characteristics constraints, electrochemical energy storage operation characteristics constraints, wind power and photovoltaic power output constraints, and upper and lower limits of grid-injected power constraints.

[0063] The system power balance constraints are as follows:

[0064] P t L =P t dis -P t ch +P t FC -P t EB +P t w,r +P t pv,r +P t inj (6);

[0065] Among them, P t L P represents the system load at time t; tinj P represents the power purchased by the system from the upstream grid at time t; t w,r P represents the actual grid-connected power of wind power at time t; t pv,r P represents the actual grid-connected power of the photovoltaic system at time t; t ch and P t dis P represents the total charge and discharge power of the system's stored energy at time t; t EB and P t FC Let represent the electrolysis power of the electrolyzer and the output power of the fuel cell at time t, respectively.

[0066] The operating characteristics constraints of the hydrogen energy storage system are as follows:

[0067]

[0068] Among them, V t EB ρ represents the volume of hydrogen produced by the electrolyzer at time t; EB λ represents the rated hydrogen production volume per unit of electricity consumed by the electrolyzer; EB V represents the electrolysis efficiency of the electrolytic cell. t FC ρ represents the volume of hydrogen consumed by the fuel cell at time t; FC This represents the rated power generation per unit volume of hydrogen consumed by a fuel cell; μ FC E represents the power generation efficiency of a fuel cell; hs,t and E hs,t+1 These represent the remaining hydrogen volumes in the hydrogen storage tank at time t and t+1, respectively. and N represents the volume of hydrogen gas added to and removed from the hydrogen storage tank at time t, respectively; eb Indicates the number of electrolytic cells; N fc N represents the number of fuel cells; hs Indicates the number of hydrogen storage tanks; These represent the hydrogen filling and discharging efficiencies of the hydrogen storage tank, respectively. These represent the rated power of a single electrolyzer and fuel cell, respectively. These represent 0-1 variables that restrict the hydrogen filling and discharging states of the hydrogen storage tank, respectively. These are 0-1 variables representing the hydrogen inlet and outlet states of the hydrogen storage tank, respectively. ε1 and ε2 represent the maximum capacity of a single hydrogen storage tank; ε1 and ε2 represent the ratios of the minimum and maximum allowable remaining capacity of the hydrogen storage tank to the total capacity during operation, respectively.

[0069] The operational characteristics of electrochemical energy storage are constrained as follows:

[0070] E t+1 =E t +(P t ch η-P t dis / η)Δt(10);

[0071] α1E max ≤E t ≤α2E max (11);

[0072]

[0073] Among them, E t E t+1 α1 and α2 represent the remaining energy of the electrochemical energy storage at times t and t+1, respectively; η represents the charge and discharge efficiency of the electrochemical energy storage; α1 and α2 represent the proportions of the minimum and maximum allowable remaining capacity to the total capacity during the operation of the electrochemical energy storage, respectively; β ch β dis E represents the 0-1 variables that restrict the charge and discharge states of electrochemical energy storage, respectively. max P represents the maximum energy storage capacity. max Indicates the maximum energy storage capacity;

[0074] The output constraints for wind power and solar power are as follows:

[0075] 0≤P t w,r ≤P t w (13);

[0076] 0≤P t pv,r ≤P t pv (14);

[0077] Among them, P t w P t pv This represents the maximum output limit of wind power and photovoltaic units at time t;

[0078] The output power of the fuel cell is as follows:

[0079]

[0080] in, This indicates the upper limit of the power injected into the upper-level power grid.

[0081] Step S3: Input the preset energy storage configuration capacity from small to large into the new energy-based multi-energy storage optimal consumption scheduling model, and calculate the new energy consumption corresponding to different energy storage configuration capacities;

[0082] Step S4: By calculating the amount of new energy consumption corresponding to the unit increase in energy storage capacity, the marginal benefits of diversified energy storage for new energy consumption are obtained.

[0083] The formula for calculating the marginal benefits of diversified energy storage for new energy consumption is as follows:

[0084]

[0085] Where M represents the incremental capacity and marginal benefits of multi-energy storage; ΔF and ΔC represent the incremental amount of new energy consumption and the incremental amount of energy storage capacity, respectively; F(C) represents the amount of new energy consumption of the system when the energy storage capacity is C; F(C+ΔC) represents the amount of new energy consumption of the system when the energy storage capacity is C+ΔC.

[0086] Step S5: Increase the energy storage investment cost by ΔC, and let C + ΔC = C;

[0087] When the maximum energy storage investment cost C is not reached max At that time, reset the energy storage investment cost C;

[0088] When C = C max At that time, stop and plot the effectiveness curves of energy storage and new energy consumption.

[0089] The invention will be further illustrated below with specific examples.

[0090] To assess the marginal benefit of building energy storage in the system on the system's renewable energy absorption capacity, the time scale is considered to be daily, the energy storage type is electrochemical energy storage, and the total energy storage capacity ranges from 0MW / 0MWh to 1550MW / 3100MWh.

[0091] Table 1 System Power Curtailment Rate

[0092]

[0093]

[0094] The trend of curtailment rate with energy storage configuration capacity is as follows: Figure 2 As shown.

[0095] When energy storage systems are initially configured in the system, the curtailment rate decreases rapidly with each increase in storage capacity. As storage capacity increases, the contribution of each additional unit of storage to the system's renewable energy absorption capacity gradually decreases. Further increases in storage capacity will further reduce the growth rate of renewable energy absorption capacity. Once a certain critical point is reached, all renewable energy in the system will be absorbed.

[0096] The changes in the marginal benefits of energy storage-enhancing systems for renewable energy consumption under different energy storage construction scales are as follows: Figure 3 As shown.

[0097] As the capacity of energy storage configuration increases, the marginal benefit of energy storage in promoting the consumption of new energy decreases, eventually reducing to zero. Considering the construction of energy storage to improve the system's renewable energy consumption capacity, the marginal benefit of the system's curtailment rate changes in a stepwise manner. To optimize the economics of energy storage construction, the energy storage capacity should be selected at the inflection point of the marginal benefit in the middle part.

[0098] Example 2

[0099] A system for calculating the marginal benefit of energy storage regulation, comprising:

[0100] An optimized scheduling model construction unit is used to build an optimized scheduling model for multi-element energy storage based on the consumption of new energy sources;

[0101] The energy storage configuration capacity adjustment unit is used to input the preset energy storage configuration capacity from small to large into the multi-element energy storage optimization scheduling model based on new energy consumption, and calculate the new energy consumption corresponding to different energy storage configuration capacities.

[0102] The marginal benefit calculation unit is used to calculate the amount of new energy consumption corresponding to the unit increase in energy storage capacity, so as to obtain the multi-dimensional marginal benefits of energy storage for new energy consumption.

[0103] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0104] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0105] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0106] It is worth noting that all contents not described in detail in this invention are existing technologies and are well known to those skilled in the art.

[0107] Therefore, the present invention employs the above-mentioned method, system, electronic equipment and medium for calculating the marginal benefit of energy storage regulation, which can provide effective support for the optimal configuration of energy storage capacity during construction and has practical engineering value. It can obtain the optimal energy storage capacity configuration strategy under the premise of fully considering the marginal benefit of promoting the consumption of new energy.

[0108] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for calculating the marginal benefit of energy storage regulation, characterized in that, Includes the following steps: Step S1: Construct a multi-element energy storage optimization scheduling model based on new energy consumption; Step S2: Input the preset energy storage configuration capacity from small to large into the multi-element energy storage optimization scheduling model based on new energy consumption, and calculate the new energy consumption corresponding to different energy storage configuration capacities; Step S3: By calculating the amount of new energy consumption corresponding to the unit increase in energy storage capacity, the marginal benefits of diversified energy storage for new energy consumption are obtained. The formula for calculating the marginal benefits of diversified energy storage for new energy consumption is as follows: （16）； in, This indicates the incremental capacity and marginal benefits of diversified energy storage. , These represent the increase in new energy consumption and the increase in energy storage capacity, respectively. Indicates energy storage capacity as The amount of new energy consumed by the system at any time; Indicates energy storage capacity as The amount of new energy consumed by the system at any time; The objective function of the multi-element energy storage optimization scheduling model based on renewable energy consumption is as follows: （1）； （2）； （3）； （4）； （5）； in, Represent the objective function; , These represent the operating costs of energy storage and the costs of wind and solar power curtailment, respectively. , These represent the charging and discharging loss costs of hydrogen energy storage and electrochemical energy storage, respectively. , These represent the unit charge / discharge loss cost of the electrolyzer and fuel cell, respectively. , They represent the first Energy storage The electrolysis power of the electrolyzer and the output power of the fuel cell at all times; , They represent the first Energy storage The constant electrochemical energy storage charging and discharging power; , These represent the penalty costs per unit of wind and solar power curtailment, respectively. , They represent the first A new energy power station The maximum generating capacity and actual grid-connected capacity of wind power at any given time; , They represent the first A new energy power station The maximum renewable power and actual grid-connected power of photovoltaic power at any given time; , They represent Time of the first Power output and cost of individual thermal power units; Indicates the optimization time interval under consideration; This represents the maximum number of energy storage facilities. This represents the maximum number of thermal power units. This represents the maximum value of new energy power plants; This represents the maximum value at any given time.

2. The method for calculating the marginal benefit of energy storage regulation according to claim 1, characterized in that, In step S1, the constraints of the multi-element energy storage optimization scheduling model based on new energy consumption include: system power balance constraints, hydrogen energy storage system operation characteristics constraints, electrochemical energy storage operation characteristics constraints, wind power and photovoltaic power output constraints, and upper and lower limits of grid-injected power constraints. The system power balance constraints are as follows: （6）； in, express System load at all times; express Power injected by the upstream power grid at any time; express The actual grid-connected power of wind power at any given time; express The actual grid-connected power of photovoltaic power at any given time; and Representing the system Total charging and discharging power of stored energy at all times; and Representing the system The electrolysis power of the electrolyzer and the output power of the fuel cell at all times; The operating characteristics constraints of the hydrogen energy storage system are as follows: （7）； （8）； （9）； in, express The volume of hydrogen produced by the electrolyzer at any given time; This indicates the rated hydrogen production volume per unit of electricity consumed by the electrolyzer; Indicates the electrolysis efficiency of the electrolytic cell; express The volume of hydrogen consumed by the fuel cell at any given time; This indicates the rated power generation per unit volume of hydrogen consumed by the fuel cell; Indicates the power generation efficiency of the fuel cell; and They represent Time and The remaining hydrogen volume in the hydrogen storage tank at any time; and They represent in The volume of hydrogen being added to and removed from the hydrogen storage tank at all times; Indicates the number of electrolytic cells; Indicates the number of fuel cells; Indicates the number of hydrogen storage tanks; , These represent the hydrogen filling and discharging efficiency of the hydrogen storage tank, respectively. , These represent the rated power of a single electrolyzer and fuel cell, respectively. , These represent 0-1 variables that restrict the hydrogen filling and discharging states of the hydrogen storage tank, respectively. , These are 0-1 variables representing the hydrogen inlet and outlet states of the hydrogen storage tank, respectively. Indicates the maximum capacity of a single hydrogen storage tank; , These represent the minimum and maximum allowable remaining capacity of the hydrogen storage tank during operation, respectively, as proportions of the total capacity. The operational characteristics of electrochemical energy storage are constrained as follows: （10）； （11）； （12）； in, , They represent , The remaining energy stored in electrochemical energy at all times; Indicates the charging and discharging efficiency of electrochemical energy storage; , These represent the ratios of the minimum and maximum allowable remaining capacity to the total capacity during the operation of electrochemical energy storage, respectively. , These represent 0-1 variables that restrict the charge and discharge states of electrochemical energy storage, respectively. Indicates the maximum energy storage capacity; Indicates the maximum energy storage capacity; The output constraints for wind power and solar power are as follows: （13）； （14）； in, , express The maximum output limit of wind power and photovoltaic units at all times; The output power of the fuel cell is as follows: （15）； in, This indicates the upper limit of the power injected into the upper-level power grid.

3. A system for calculating the marginal revenue of energy storage regulation, characterized in that, The method for calculating the marginal benefit of energy storage regulation as described in any one of claims 1-2 includes: An optimized scheduling model construction unit is used to build an optimized scheduling model for multi-element energy storage based on the consumption of new energy sources; The energy storage configuration capacity adjustment unit is used to input the preset energy storage configuration capacity from small to large into the multi-element energy storage optimization scheduling model based on new energy consumption, and calculate the new energy consumption corresponding to different energy storage configuration capacities. The marginal benefit calculation unit is used to calculate the amount of new energy consumption corresponding to the unit increase in energy storage capacity, so as to obtain the multi-dimensional marginal benefits of energy storage for new energy consumption.

4. A computer device, comprising: Memory and processor; The memory stores a computer program, characterized in that when the processor executes the computer program, it implements the steps of the energy storage regulation marginal benefit calculation method according to any one of claims 1-2.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that, When a computer program is executed by a processor, it implements the steps of the method for calculating the marginal benefit of energy storage regulation as described in any one of claims 1-2.

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