A method and system for evaluating the value of energy storage providing multiple ancillary services

Abstract

This invention relates to a method and system for evaluating the value of energy storage providing multiple ancillary services. The method includes the following steps: Step S100, modeling the process of energy storage and generating units providing frequency regulation reserve, inertia, and voltage regulation ancillary services; Step S200, modeling the inertia response, frequency regulation, and voltage regulation processes of the power system; Step S300, modeling the power system dispatch problem involving energy storage providing ancillary services; Step S400, obtaining the dual multipliers of the constraints corresponding to each ancillary service by solving the power system dispatch problem in Step S300; Step S500, calculating the service cost of each ancillary service of energy storage based on the dual multipliers of the constraints corresponding to each ancillary service. Compared with the prior art, this invention provides a method for evaluating the value of energy storage providing multiple ancillary services, thereby providing a technical reference for the pricing standard of energy storage providing ancillary services and optimizing the allocation efficiency of ancillary service resources.

Description

Technical Field

[0001] This invention relates to the field of energy storage dispatch and ancillary service pricing technology, and in particular to a method and system for evaluating the value of energy storage providing multiple ancillary services. Background Technology

[0002] Currently, the penetration rate of renewable energy in China's power system is continuously increasing. The high proportion of new energy access places higher demands on the safety and reliability of the power system. Energy storage systems participating in the provision of ancillary services have become an effective means to improve the stability of the power system. A reasonable pricing mechanism can effectively guide energy storage to actively participate in the ancillary service market and improve the efficiency of allocating ancillary service resources.

[0003] Over the years, there has been a wealth of research on the costs and benefits of energy storage providing ancillary services. For example, Reference 1, "Design and Scheduling Strategy of Frequency Regulation Ancillary Service Market Mechanism Adapted to Energy Storage Participation" (Lu Qiuyu, Yang Yinguo, Xie Pingping, Chen Yue, Wu Jiekang, Lei Zhen. Power Grid Technology, 2023, 47(12):4971-4989.), designed an operation mechanism for frequency regulation ancillary services adapted to energy storage participation. It uses a subjective and objective weighting method to calculate the weight coefficient of the comprehensive frequency regulation performance index of different types of frequency regulation resources, characterizes the differences in frequency regulation performance of multiple types of frequency regulation resources, compares the frequency regulation demand of different trading periods horizontally, introduces a time relaxation factor to optimize the marginal clearing price of trading periods, and uses a spatial relaxation factor to quantify the substitution capacity of different frequency regulation resources, forming a reasonable compensation for fast and slow frequency regulation resources. Reference 2, "Design of Market Mechanism for Independent Energy Storage Participation in Frequency Regulation Ancillary Services" (Lin Azhu, Ke Qinghui, Jiang Yuewen. Power Automation Equipment, 2022, 42(12):26-34.), sets frequency regulation performance indicators such as regulation accuracy, response time, and regulation speed, and introduces an efficiency factor to reflect the advantages of fast frequency regulation resources, thereby encouraging the market to actively introduce independent energy storage to participate in frequency regulation in order to optimize the allocation of frequency regulation resources in the system. Reference 3, "Comprehensive Economic Benefit Analysis of Energy Storage Participation in Wind Power Ancillary Services" (Ma Meiting, Yuan Tiejiang, Chen Guangyu, Cai Gaolei, Peng Shengjiang, Zhang Zengqiang. Power Grid Technology, 2016, 40(11):3362-3367.), studies the economics of battery energy storage power stations participating in wind power ancillary services based on risk mitigation, establishes a comprehensive economic benefit model for its participation in wind power ancillary services, and evaluates the advantages and disadvantages of energy storage power stations participating in wind power ancillary services through economic indicators such as the return on investment and investment payback period of energy storage power stations. Reference 4, "Coordination Mechanism for Market Clearing of Spot Electricity and Frequency Regulation Ancillary Services Including Independent Energy Storage" (Xiao Yunpeng, Zhang Lan, Zhang Xuan, Liu Qixing. Proceedings of the CSEE, 2020, 40(S1):167-180.), establishes a market clearing model for frequency regulation ancillary services. It considers capacity and mileage bids in ancillary service bidding and calculates the opportunity cost of providing frequency regulation ancillary services to form a comprehensive bid. The benefits and behaviors of independent energy storage participating in the market are analyzed within the market clearing model that includes independent energy storage.

[0004] Based on various research findings, numerous patent applications have been filed concerning the cost or pricing of energy storage participating in ancillary services. For example, patent application 1, "Cost Model for Energy Storage Participating in Ancillary Services" (Li Xin, Dou Dong, Yang Wensheng, Niu Getu, Li Haiqing, Wang Yanyu, Tai Yuxin, Liang Wenyan, Shi Xiaoran, Zhang Beihong, Huan Xiaochao, Tana, Wang Ting, Gao Zetian, Zheng Haitong, Wang Zhongwei, Liu Huixia. CN202211531639.3[P]. 2023-03-14.), proposes a simple cost assessment method for energy storage participating in ancillary services, including the fixed cost, variable cost, and unit cost of the energy storage power station. The types of ancillary services involved include peak shaving and frequency regulation services, and the unit cost is mainly obtained by dividing the annual value of the total life cycle cost by the annual electricity volume processed or the total frequency regulation mileage. Patent application 2, "A Coordinated Clearing Method for the Electric Energy and Frequency Regulation Ancillary Services Market with Energy Storage Participation" (Shu Shi, Peng Jigang, Liu Zhenda, Wang Zhen, Jiang Taiping, Chen Yiyu, Zhang Zhengmei, Pan Li, Xiao Jun, Yang Weiguo. CN202310677201.4[P]. 2023-10-03.), addresses the clearing of the electric energy market and the frequency regulation ancillary services market. It constructs clearing models for the electric energy market and the frequency regulation market, proposes a comprehensive frequency regulation performance index to quantify the frequency regulation performance of different frequency regulation resources, and considers the impact of mileage cost, capacity cost, and opportunity cost to settle the revenue of energy storage in the frequency regulation market. This achieves sequential and joint clearing of the electric energy and frequency regulation ancillary services markets. Patent application 3, "A Compensation Method for Battery Energy Storage Participating in Grid Voltage Regulation Ancillary Services" (Zhao Jinquan, Geng Simin, Cui Wei, Zhang Zhenan, Shan Ruiqing, Xu Peng. CN202110054615.2[P]. 2021-05-28.), proposes a compensation method for battery energy storage participating in grid voltage regulation ancillary services. It establishes a cost structure model for battery energy storage participating in grid voltage regulation ancillary services, including converter loss costs and opportunity costs. It considers various situations where reactive power leads to a reduction in the actual power or available capacity of active power, and determines different compensation standards for battery energy storage participating in grid voltage regulation ancillary services.

[0005] However, traditional methods have the following inherent drawbacks:

[0006] 1. The operational status of energy storage providing ancillary services is not included in the system scheduling model, making it difficult to accurately represent the process of energy storage providing ancillary services.

[0007] 2. The cost calculation focuses on the cost of energy storage hardware conditions, without addressing the specific operational process of energy storage providing ancillary services to the power system. Summary of the Invention

[0008] The purpose of this invention is to overcome the shortcomings of the existing technology by providing a value assessment method and system for energy storage to provide a variety of ancillary services, so as to solve or partially solve the problem of unsatisfactory efficiency of ancillary service resources.

[0009] The objective of this invention can be achieved through the following technical solutions:

[0010] One aspect of the present invention provides a method for evaluating the value of energy storage providing various ancillary services, comprising the following steps:

[0011] Step S100: Model the process of providing frequency regulation backup, inertia and voltage regulation auxiliary services for energy storage and generating units;

[0012] Step S200: Model the inertial response, frequency regulation, and voltage regulation processes of the power system;

[0013] Step S300: Model the power system dispatch problem, which includes ancillary services provided by energy storage;

[0014] Step S400: By solving the power system scheduling problem in step S300, the dual multipliers of the constraints corresponding to each ancillary service are obtained.

[0015] Step S500: Based on the dual multipliers of the constraints corresponding to each auxiliary service, calculate the service cost of each auxiliary service of energy storage to achieve value assessment.

[0016] As a preferred technical solution, in step S100,

[0017] The model for energy storage and generating units providing frequency regulation backup services is as follows:

[0018] Unit frequency regulation reserve power constraints:

[0019] The unit's frequency regulation reserve power is limited by the unit's output:

[0020] Constraints on the composition of total frequency regulation reserve for energy storage:

[0021] Upper and lower limits of energy storage total frequency regulation reserve:

[0022] Total frequency regulation energy reserve constraints for energy storage:

[0023] Energy storage total frequency regulation energy recovery constraint: in, This is the standby capacity for frequency regulation of a single thermal power unit. This indicates the operating status of the generator unit; 1 represents operation, and 0 represents shutdown. This represents the maximum frequency regulation capacity that a single thermal power unit can provide. For the single unit output of thermal power units, This represents the maximum output of a single thermal power unit. The total reserve capacity for energy storage used for frequency regulation and inertia services. The inertial power for energy storage, For primary frequency regulation backup of energy storage, and These are the charging power, discharging power, and maximum discharging power of a single energy storage unit. For energy storage level, t reg,dur η is the duration of a single frequency modulation. d For discharge efficiency, The energy required to provide inertia for energy storage For the minimum energy level of energy storage, t soc,re Time is required for energy recovery;

[0024] The model for energy storage and generating units providing inertia services is as follows:

[0025] Unit inertia constraints:

[0026] Energy storage inertia power constraint:

[0027] Energy constraint of energy storage inertia:

[0028] Energy storage inertia coefficient constraint: in, The inertia coefficient of the unit. Let f0 be the inertia coefficient of the energy storage, f0 be the nominal frequency of the system, and RoCoF be the inertia coefficient of the energy storage. max Δf is the maximum permissible rate of frequency change. max For the maximum permissible frequency deviation, Let be the maximum inertia coefficient of the energy storage, and ESSs be the energy storage set. A collection of runtime segments;

[0029] The model for providing voltage regulation services for energy storage is as follows:

[0030] Energy storage voltage regulation droop control constraint: ΔQ s =k Q Δx U ;

[0031] Energy storage converter capacity constraints:

[0032] Power factor constraints for energy storage converters: Where, ΔQ s k is the reactive power regulation backup provided for energy storage. Q Δx is the droop control coefficient of the energy storage reactive power control loop. U For system voltage regulation requirements, i.e., the portion of the grid connection point voltage deviation exceeding the maximum limit, P s,t Let be the power of the stored energy s discharged externally at time t, then we have For the maximum capacity of the energy storage grid-connected converter, This is the minimum power factor allowed for converter operation.

[0033] As a preferred technical solution, in step S200,

[0034] The inertial response model of a power system is as follows:

[0035] Unit primary frequency regulation standby constraints:

[0036] Energy storage primary frequency regulation reserve constraints:

[0037] Unit total inertia constraint:

[0038] Total inertia constraint of energy storage: in, The total frequency regulation capacity of thermal power units. For the total frequency regulation capacity of energy storage, The total inertia level of the thermal power unit. This represents the total inertia level of energy storage;

[0039] The power system frequency dispatch model is as follows:

[0040] Maximum rate of change constraint:

[0041] Maximum quasi-steady-state frequency deviation constraint:

[0042] Minimum frequency constraint: in in, For the system load deviation, f is the maximum permissible quasi-steady-state frequency deviation limit. D The damping coefficient is... The total load at time t; Let T be the total inertia of the system. e T is the energy storage frequency regulation time constant. g The frequency regulation time constant for thermal power plants;

[0043] The voltage regulation model of the power system is as follows:

[0044] Voltage deviation constraint:

[0045] System voltage regulation requirement constraints: Where, ΔU PCC,i This refers to the voltage deviation at the grid connection point caused by a disturbance at node i. Let ΔQ be the voltage sensitivity coefficient of node i to the grid connection point.i For the reactive power disturbance occurring at node i, Ω N For the system node set, It is the allowable deviation of the grid connection point bus voltage specified by the system, Δx U To meet the system's voltage regulation requirements, all nodes' reactive power disturbances are examined, and the disturbances at the nodes that have the greatest impact on the grid connection voltage are taken into account for the voltage regulation requirements.

[0046] As a preferred technical solution, step S300 includes the objective function of the power system dispatch problem involving energy storage providing ancillary services, which is:

[0047]

[0048] Where VC represents the total cost related to the generating unit, WSC represents the total cost related to new energy sources and energy storage, and Ω G Ω w and Ω S These represent collections of generating units, new energy sources, and energy storage, respectively. These are the unit output price, no-load cost, start-up cost, unit price for primary frequency regulation service, and unit price for inertia service of thermal power units. w c s , These are the unit price of new energy output, the unit price of energy storage discharge / electricity purchase, the unit price of energy storage fast frequency regulation, and the unit price of energy storage inertia. This indicates the startup action of unit u at time t. Power output for new energy sources Purchase power for energy storage.

[0049] As a preferred technical solution, step S300 includes the following constraints on the power system dispatching problem involving energy storage providing ancillary services:

[0050] Energy storage device operating constraints include:

[0051] Energy storage charging power constraints:

[0052] Energy storage discharge power constraints:

[0053] State of charge timing constraints:

[0054] Upper and lower limits of state of charge constraints:

[0055] Consistency constraint from start to finish of scheduling cycle: SOC s,0 =SOC s,end ;

[0056] Where, qs,t This represents the charging and discharging status of energy storage s at time t, with 1 for charging and 0 for discharging. Represent the upper limits of the charging and discharging power of the selected energy storage element s, respectively, and SOC. s,t η represents the state of charge of the candidate energy storage element s at time t. c η d Representing the charging efficiency and discharging efficiency of energy storage element s, respectively, SOC s,0 SOC s,end These represent the state of charge of the energy storage element at the beginning and end of the scheduling cycle, respectively;

[0057] Unit operating constraints include:

[0058] Unit active power output constraints:

[0059] Unit reactive power output constraints:

[0060] Unit ramp-up constraints:

[0061] Minimum online and offline time constraints for the unit:

[0062] Unit switching actions and online status logic constraints: in, RU represents the active and reactive power output of unit u at time t, respectively. u RD u These represent the maximum uphill and downhill ramp power of unit u, respectively. TU is a 0-1 variable representing a unit shutdown action, where 1 indicates the action. u and TD u These represent the minimum online and offline times of unit u, respectively.

[0063] As a preferred technical solution, step S400 includes:

[0064] Step S401: By pre-solving the power system dispatch problem established in step S300, which includes ancillary services provided by energy storage, 0-1 variables representing the start-up, shutdown actions, and online status of unit u at time t are obtained. The solution, and the 0-1 variable q representing the charging and discharging state of the energy storage s at time t. s,t The solution;

[0065] Step S402: Substitute the solution of 0-1 variables obtained in step S401 into the power system dispatch problem established in step S300, which includes ancillary services provided by energy storage, and transform the non-convex joint optimization problem into a market clearing problem that only includes continuous variables.

[0066] Step S403: For the market clearing problem, the dual multipliers of frequency regulation reserve, inertia and voltage regulation auxiliary services are solved by constructing a Lagrangian function.

[0067] As a preferred technical solution, the Lagrange function is constructed as follows:

[0068]

[0069] Where, ω ro ω is the dual multiplier of the system's maximum rate of change of frequency constraint. ss Let μ be the dual multiplier of the constraint on the maximum quasi-steady-state frequency deviation of the system, and let μ, λ1, and λ2 be the dual multipliers of the corresponding terms of the constraint on the lowest frequency point of the system, satisfying μ ≥ 0. These are the dual multipliers of the total inertia constraint and the total primary frequency regulation constraint, respectively. These are the dual multipliers of the total inertia constraint and the total primary frequency regulation constraint, respectively, ω dr ω is the dual multiplier for the voltage droop control constraint of energy storage. ca For the dual multiplier of the capacity constraint of the energy storage converter, ω fa1 ω fa2 For the dual multipliers of the power factor constraint of the energy storage converter, ... denotes the constraint terms that are not ancillary services.

[0070] As a preferred technical solution, step S500 includes:

[0071] Step S501: Construct the Lagrangian function for a market clearing model containing only continuous variables;

[0072] Step S502: Calculate the partial derivative of the Lagrange function constructed in step S501 with respect to the virtual inertia corresponding to each auxiliary service.

[0073] Step S503 yields the formula for the cost of virtual inertia corresponding to each auxiliary service.

[0074] As a preferred technical solution, in step S501, the Lagrange function is:

[0075] The cost of providing virtual inertia assistance services through energy storage is:

[0076]

[0077] in, The cost of providing virtual inertia for energy storage, where f0 is the rated frequency, ω ro ω Heλ1, λ2 are the dual multipliers of the system's maximum frequency change rate constraint and the total inertia constraint of energy storage, respectively; μ, λ1, and λ2 are the dual multipliers of each term corresponding to the system's minimum frequency point constraint.

[0078] The cost of energy storage providing fast frequency regulation ancillary services is:

[0079]

[0080] in, The cost of providing rapid frequency regulation for energy storage, T e Let Δf be the energy storage time constant. max ω is the maximum allowable frequency deviation. ss The dual multiplier for the system's maximum quasi-steady-state frequency deviation constraint. The dual multiplier for the overall first-order frequency modulation constraint;

[0081] The cost of energy storage providing voltage regulation ancillary services is:

[0082]

[0083] in, The cost of providing voltage regulation services for energy storage, ΔQ s,t ω is the reactive power regulation backup provided for energy storage. dr ω is the dual multiplier for the voltage droop control constraint of energy storage. ca For the dual multiplier of the capacity constraint of the energy storage converter, ω fa1 ω fa2 It is the dual multiplier for the power factor constraint of the energy storage converter.

[0084] Another aspect of the present invention provides a value assessment system for energy storage providing various ancillary services, comprising:

[0085] The ancillary services modeling module is used to model the process of providing frequency regulation reserve, inertia and voltage regulation ancillary services for energy storage and generating units.

[0086] The power system modeling module is used to model the inertial response, frequency regulation, and voltage regulation processes of power systems.

[0087] The power system dispatch modeling module is used to model power system dispatch problems, including those involving energy storage providing ancillary services.

[0088] The power system scheduling solution module is used to obtain the dual multipliers of the constraints corresponding to each auxiliary service by solving the power system scheduling problem;

[0089] The ancillary service cost calculation module is used to calculate the service cost of each energy storage service based on the dual multipliers of the constraints corresponding to each ancillary service, thereby realizing value assessment.

[0090] Compared with the prior art, the present invention has at least one of the following beneficial effects:

[0091] (1) Optimize the allocation efficiency of ancillary service resources: This invention performs more accurate modeling of the inertial response, frequency regulation and voltage regulation of energy storage devices, so that their flexibility can be used for system frequency and voltage regulation and scheduling. The cost of energy storage providing each ancillary service is calculated by the Lagrange multiplier of each ancillary service constraint, and the pricing of ancillary services is determined, thereby optimizing the allocation efficiency of ancillary service resources.

[0092] (2) The power system has good safety and reliability: The present invention adds inertial response, frequency regulation and voltage regulation constraints to the system scheduling model. Compared with the traditional system scheduling model, it can reflect the limitations of ancillary services on system operation and increase the safety and reliability of the system.

[0093] (3) Fast solution speed: In the process of solving the power system scheduling problem of energy storage participating in ancillary services, the present invention obtains the parameters required to calculate the cost of energy storage providing ancillary services by first solving the mixed integer programming and then solving the second-order cone programming, thus ensuring the solution speed and efficiency. Attached Figure Description

[0094] Figure 1 This is a schematic diagram illustrating the value assessment method for providing various ancillary services for energy storage in this embodiment.

[0095] Figure 2 This is a schematic diagram illustrating the detailed process of the value assessment method for providing various ancillary services for energy storage in this embodiment;

[0096] Figure 3 This is a schematic diagram of a value assessment system for providing various ancillary services for energy storage in this embodiment. Detailed Implementation

[0097] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0098] Example 1

[0099] To address the problems existing in the aforementioned prior art, this embodiment provides a method for evaluating the value of energy storage providing various ancillary services, see [link to relevant documentation]. Figure 1 and Figure 2 The method includes the following steps

[0100] Step S000, see Figure 2The parameters of the generating unit, energy storage equipment, system, system frequency, and renewable energy output are pre-entered.

[0101] Step S100: The operating model for energy storage and generating units to provide inertia, frequency regulation backup and voltage regulation services.

[0102] The model includes the frequency reserve model of the generating unit, the inertia model of the generating unit, the frequency reserve model of the energy storage, the inertia model of the energy storage, and the voltage regulation model of the energy storage. These are reflected as constraints in the optimization model.

[0103] (1) Frequency standby model of the unit.

[0104] In this embodiment, the frequency reserve model of the unit includes the following constraints:

[0105] Backup power constraints:

[0106] Backup power is limited by the unit's output: in, This is the standby capacity for frequency regulation of a single thermal power unit. This indicates the operating status of the generator unit; 1 represents operation, and 0 represents shutdown. This represents the maximum frequency regulation capacity that a single thermal power unit can provide. For the single unit output of thermal power units, This is the maximum output of a single thermal power unit.

[0107] (2) Inertia model of the unit.

[0108] In this embodiment, the inertia model of the unit includes the following constraints:

[0109] Unit inertia constraints: in, This is the inertia coefficient of the unit.

[0110] (3) Frequency backup model for energy storage.

[0111] In this embodiment, the frequency backup model for energy storage includes the following constraints:

[0112] Constraints on the composition of total frequency regulation reserve for energy storage:

[0113] Upper and lower limits of energy storage total frequency regulation reserve:

[0114] Total frequency regulation energy reserve constraints for energy storage:

[0115] Energy storage total frequency regulation energy recovery constraint: in, The total reserve capacity for energy storage used for frequency regulation and inertia services. The inertial power for energy storage, For primary frequency regulation backup of energy storage; and These are the charging power, discharging power, and maximum discharging power of a single energy storage unit, respectively. For energy storage level, t reg,dur η is the duration of a single frequency modulation. d For discharge efficiency, The energy required to provide inertia for energy storage The minimum energy level for energy storage; t soc,re The energy recovery time requirement refers to the energy consumed by energy storage in frequency regulation services, which must be replenished in a timely manner within the required time. This additional charging power is borne by the generating unit.

[0116] (4) Inertia model for energy storage.

[0117] In this embodiment, the inertia model for energy storage includes the following constraints:

[0118] Energy storage inertia power constraint:

[0119] Energy constraint of energy storage inertia:

[0120] Energy storage inertia coefficient constraint: in, Let f0 be the inertia coefficient of the energy storage, f0 be the nominal frequency of the system, and RoCoF be the inertia coefficient of the energy storage. max Δf is the maximum permissible rate of frequency change. max This represents the maximum permissible frequency deviation. Let be the maximum inertia coefficient of the energy storage, and ESSs be the energy storage set. This is a collection of runtime segments.

[0121] (5) Voltage regulation model for energy storage.

[0122] In this embodiment, the voltage regulation model for energy storage includes the following constraints:

[0123] Energy storage voltage regulation droop control constraint: ΔQ s =k Q Δx U ;

[0124] Energy storage converter capacity constraints:

[0125] Power factor constraints for energy storage converters: Where, ΔQ s k is the reactive power regulation backup provided for energy storage. Q Δx is the droop control coefficient of the energy storage reactive power control loop. UFor system voltage regulation requirements, i.e., the portion of the grid connection point voltage deviation exceeding the maximum limit; P s,t Let be the power of the stored energy s discharged externally at time t, then we have This is the maximum capacity of the grid-connected energy storage converter. This is the minimum power factor allowed for converter operation.

[0126] In this embodiment, the power factor constraint of the energy storage converter introduces non-convex elements such as square roots and quadratic terms. After simplification, it can be reformulated into the following linear constraint form:

[0127] Power factor constraint (linearization) for energy storage converters: in, for The corresponding tangent value.

[0128] Step S200: System inertial response, frequency modulation, and voltage regulation model.

[0129] Specifically, in this embodiment, the system inertia response, frequency modulation, and voltage regulation models include: a system total frequency backup metering model, a system frequency security model, and a system voltage regulation security model.

[0130] (1) System total frequency backup metering model.

[0131] In this embodiment, the system total frequency reserve metering model includes the following constraints:

[0132] Unit primary frequency regulation standby constraints:

[0133] Energy storage primary frequency regulation reserve constraints:

[0134] Unit total inertia constraint:

[0135] Total inertia constraint of energy storage: in, The total frequency regulation capacity of thermal power units; Total frequency regulation capacity for energy storage; The total inertia level of the thermal power unit; This represents the total inertia level of energy storage.

[0136] (2) System frequency security model.

[0137] In this embodiment, the system frequency security model includes the following constraints:

[0138] Maximum rate of change constraint:

[0139] Maximum quasi-steady-state frequency deviation constraint:

[0140] Minimum frequency constraint: in in, This refers to the system's load deviation. f is the maximum permissible quasi-steady-state frequency deviation limit. D The damping coefficient is... The total load at time t; Let T be the total inertia of the system. e T is the energy storage frequency regulation time constant. g This is the time constant for frequency regulation in thermal power plants.

[0141] In this embodiment, the constraint at the lowest frequency point contains a quadratic term, but it can be transformed into a second-order cone form without violating convexity:

[0142] Minimum frequency point constraint (second-order cone form):

[0143]

[0144] In this embodiment, the minimum frequency constraint can be further written in a standard form that separates the terms, facilitating the subsequent solution of the dual multipliers:

[0145]

[0146] (3) System voltage regulation safety model.

[0147] Voltage deviation constraint: Where, ΔU PCC,i This refers to the voltage deviation at the grid connection point caused by a disturbance at node i. Let ΔQ be the voltage sensitivity coefficient of node i to the grid connection point. i The reactive power disturbance occurring at node i.

[0148] In this embodiment, the voltage sensitivity coefficient is an element in the sensitivity matrix of voltage deviation with respect to reactive power disturbance. The relationship between voltage deviation and reactive power disturbance can be expressed as: ΔU=S0ΔQ, where ΔU is the voltage deviation vector, ΔQ is the reactive power disturbance vector, and S0 is the sensitivity matrix.

[0149] In this embodiment, when the phase angle difference between the two ends of the line is small, the voltage sensitivity matrix S0 can be simplified to the inverse matrix (B) of the nodal susceptance matrix. ij ) -1 This embodiment uses this simplified method.

[0150] System voltage regulation requirement constraints: Among them, Ω N For the system node set, It is the allowable deviation of the grid connection point bus voltage specified by the system, ΔxU To meet the system's voltage regulation requirements, all nodes' reactive power disturbances are examined, and the disturbances at the nodes that have the greatest impact on the grid connection voltage are taken into account for the voltage regulation requirements.

[0151] In this embodiment, the following variables are introduced: The system voltage regulation requirement constraint can then be further expressed as: Δx U =max(A Q ,0).

[0152] In this embodiment, the system voltage regulation requirement constraint is a piecewise function, which introduces a non-convex factor and is processed using separation constraints:

[0153] Separation constraints of system voltage regulation requirements:

[0154] M(y Q -1)≤A Q ≤My Q ;

[0155] Δx U ≤A Q y Q ;

[0156] Δx U ≥-My Q ;

[0157] Δx U ≥A Q -M(1-y Q ).

[0158] Among them, A Q As an auxiliary variable introduced, y Q The introduced auxiliary 0-1 variable, M, represents a very large constant, Δx. U This indicates the system's voltage regulation requirements.

[0159] Step S300, including the power system dispatch model that provides ancillary services through energy storage.

[0160] Specifically, in this embodiment, the objective function of the power system dispatch model including energy storage to provide ancillary services is to minimize the sum of the electrical energy of each device and the cost of ancillary service requests:

[0161]

[0162] Where VC represents the total cost related to the generating unit, WSC represents the total cost related to new energy sources and energy storage, and Ω G Ω w and Ω S These represent collections of generating units, new energy sources, and energy storage, respectively. These are the unit output price, no-load cost, start-up cost, unit price for primary frequency regulation service, and unit price for inertia service of thermal power units. w c s , These are the unit price of new energy output, the unit price of energy storage discharge / electricity purchase, the unit price of energy storage fast frequency regulation, and the unit price of energy storage inertia. This indicates the startup action of unit u at time t. Power output for new energy sources Purchase power for energy storage.

[0163] In this embodiment, the constraints of the power system dispatch model that includes energy storage to provide ancillary services include the models described in S100 and S200 above, as well as the energy storage device operation model, the unit operation model, and the system operation model.

[0164] (1) Operation model of energy storage equipment.

[0165] Energy storage charging power constraints:

[0166] Energy storage discharge power constraints:

[0167] State of charge timing constraints:

[0168] Upper and lower limits of state of charge constraints:

[0169] Consistency constraint from start to finish of scheduling cycle: SOC s,0 =SOC s,end ;

[0170] Where, q s,t This represents the charging and discharging flag variable of energy storage s at time t, where 1 indicates charging and 0 indicates discharging. These represent the upper limits of the charging and discharging power of the selected energy storage element s, respectively; SOC s,t η represents the state of charge of the candidate energy storage element s at time t. c η d These represent the charging efficiency and discharging efficiency of the energy storage element s, respectively; SOC s,0 SOC s,end These represent the state of charge of the energy storage element at the beginning and end of the scheduling cycle, respectively.

[0171] (2) Unit operation model.

[0172] In this embodiment, the unit operating constraints include:

[0173] Unit active power output constraints:

[0174] Unit reactive power output constraints:

[0175] Unit ramp-up constraints:

[0176] Minimum online and offline time constraints for the unit:

[0177] Unit switching actions and online status logic constraints: in, RU represents the active and reactive power output of unit u at time t, respectively. u RD u These represent the maximum uphill and downhill ramp power of unit u, respectively. TU is a 0-1 variable representing a unit shutdown action: 1 represents the action. u and TD u These represent the minimum online and offline times of unit u, respectively.

[0178] (3) System operation model.

[0179] The steady-state operation of the power system is modeled using optimal power flow with second-order cone relaxation. In this embodiment, the system network constraints include:

[0180] Node voltage constraints:

[0181] Power flow constraints on the line:

[0182] Power balance constraints:

[0183] Second-order cone relaxation constraint: Among them, Ω N Ω represents the set of system nodes. E Represents the set of transmission lines in the system. The auxiliary variable introduced for the second-order cone power flow (this equation does not include constraints), V i P represents the voltage phasor of node i. ij Q represents the active power transmitted from node i to node j in the system. ij G represents the reactive power transmitted from node i to node j in the system. ij B ij This represents the conductance and susceptance of line ij. This represents the active power generation and active load at the node. This represents the reactive power generation and reactive load at the node.

[0184] Step S400: Solve the power system dispatch model that includes energy storage to provide ancillary services, and obtain the dual multipliers of the constraints corresponding to each ancillary service.

[0185] Specifically, in this implementation example, the value assessment method for providing various ancillary services through energy storage adopts the marginal pricing theory, which requires optimizing the convexity of the model and obtaining the marginal price of resources through the dual variables of the constraints.

[0186] In this implementation example, the power system dispatch model with ancillary services provided by energy storage established in step S300 is a mixed integer second-order cone model. It is non-convex due to the injection of numerous 0-1 variables, making it impossible to directly obtain the dual variables of the constraints. Therefore, a restricted model is chosen to handle the non-convex pricing method, and the steps are as follows:

[0187] Step S401: Pre-solve the power system dispatch model with 0-1 variables and ancillary services provided by energy storage established in step S300 to obtain the values ​​of the 0-1 variables, including 0-1 variables representing unit start-up and shutdown actions. A 0-1 variable representing the online status of unit u at time t. The 0-1 variable q represents the charging and discharging state of energy storage s at time t. s,t .

[0188] Step S402: Substitute the obtained solution of 0-1 variables into the original scheduling model, that is, let

[0189] In step S403, all the unknown 0-1 variables in the original model are replaced by the results obtained from the pre-solution, and the non-convex joint optimization model is transformed into a market clearing model containing only continuous variables.

[0190] In this implementation example, the dual multipliers of the constraints corresponding to each ancillary service can be obtained by solving a market clearing model containing only continuous variables. The dual multipliers are represented in the Lagrange function as follows:

[0191]

[0192] Where, ω ro The dual multiplier constrained by the system's maximum rate of change of frequency; ω ss Let μ be the dual multiplier of the constraint on the maximum quasi-steady-state frequency deviation of the system; μ, λ1, and λ2 are the dual multipliers of the corresponding terms of the constraint on the lowest frequency point of the system, satisfying μ ≥ 0. These are the dual multipliers of the total inertia constraint and the total primary frequency regulation constraint of the unit, respectively; These are the dual multipliers of the total energy storage inertia constraint and the total primary frequency regulation constraint, respectively; ω dr The dual multiplier for the voltage droop control constraint of energy storage; ω ca The dual multiplier for the capacity constraint of the energy storage converter; ω fa1 ω fa2For the dual multiplier of the power factor constraint of the energy storage converter; ... denotes other constraints not related to ancillary services, such as node voltage constraints:

[0193] Step S500: The cost of providing ancillary services to energy storage is calculated using the dual multipliers of the constraints corresponding to each ancillary service. Marginal pricing theory is employed, utilizing the condition that the gradient of the optimum is zero under the Karush-Kuhn-Tucker (KKT) conditions. The partial derivative of the Lagrangian function of the optimization problem with respect to the ancillary service resource variables is obtained, deriving the calculation formula for the cost of each ancillary service. Thus, the cost of providing ancillary services to energy storage is calculated using the dual multipliers of the constraints corresponding to each ancillary service.

[0194] Specifically, in this embodiment, the value assessment method for the various ancillary services provided by energy storage adopts the marginal pricing method to determine the virtual inertia provided by energy storage. For example, the specific steps are as follows:

[0195] Step S501: Construct the Lagrangian function for a market clearing model containing only continuous variables. This can be represented as... Where F total Let be the objective function. For other variables, For containing virtual inertia Constraints, λ i For the corresponding dual multipliers, For those without virtual inertia Constraints, μ i For the corresponding dual multiplier.

[0196] Step S502: Calculate the Lagrangian function with respect to the virtual inertia. The partial derivative of . Since the convex optimization model satisfies the KKT conditions at the optimal solution, and the stationarity condition in the KKT conditions requires that the gradient of the Lagrangian function at the optimal solution be 0, then the Lagrangian function with respect to The partial derivative is also 0, therefore...

[0197] Step S503, Derive the virtual inertia The marginal price formula. Virtual inertia. The marginal price should be the objective function F total right derivative Because the Lagrange function L contains F total ,according to It can be deduced Virtual inertia The marginal price formula.

[0198] In this embodiment, the cost of ancillary services can be obtained through the marginal pricing method described above, and the formula for the cost of ancillary services is derived based on the Lagrange function in step S400.

[0199] In this embodiment, the cost of providing virtual inertia assistance services through energy storage is:

[0200]

[0201] in, The cost of providing virtual inertia for energy storage, where f0 is the rated frequency.

[0202] In this embodiment, the cost of energy storage providing fast frequency regulation auxiliary services is:

[0203]

[0204] in, The cost of providing rapid frequency regulation for energy storage, T e Let Δf be the energy storage time constant. max This represents the maximum allowable frequency deviation.

[0205] In this embodiment, the cost of the energy storage providing voltage regulation auxiliary services is:

[0206]

[0207] in, The cost of providing voltage regulation services for energy storage, ΔQ s,t Reactive power regulation backup provided for energy storage.

[0208] This method has the following characteristics:

[0209] (1) This method adds inertial response, frequency modulation and voltage regulation constraints to the traditional system scheduling model. Compared with the traditional system scheduling model, it can reflect the limitations of auxiliary services on system operation and increase the safety and reliability of the system.

[0210] (2) This method can achieve more accurate modeling of the inertial response, frequency regulation and voltage regulation of energy storage devices, so that its flexibility can be used for system frequency and voltage regulation and scheduling.

[0211] (3) This method solves the power system dispatch model for energy storage to participate in ancillary services. The solution process involves pre-solving the mixed integer programming and then solving the second-order cone programming to obtain the parameters required to calculate the cost of energy storage providing ancillary services.

[0212] Example 2

[0213] Based on Example 1, see Figure 3This embodiment provides a value assessment system for energy storage providing various ancillary services, including:

[0214] The ancillary service modeling module is used to model the process of providing frequency regulation backup, inertia and voltage regulation ancillary services for energy storage and generating units. Specifically, it implements the process of step S100 in Example 1.

[0215] The power system modeling module is used to model the inertial response, frequency regulation, and voltage regulation processes of the power system. Specifically, it implements the process of step S200 in Example 1.

[0216] The power system dispatch modeling module is used to model the power system dispatch problem that includes ancillary services provided by energy storage. Specifically, it implements the process of step S300 in Example 1.

[0217] The power system scheduling solution module is used to obtain the dual multipliers of the constraints corresponding to each auxiliary service by solving the power system scheduling problem. Specifically, it implements the process of step S400 in Example 1.

[0218] The ancillary service cost assessment module is used to calculate the service cost of each energy storage service based on the dual multipliers of the constraints corresponding to each ancillary service, and to realize value assessment. Specifically, it implements the process of step S500 in Example 1.

[0219] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for evaluating the value of energy storage providing multiple ancillary services, characterized in that, Includes the following steps: Step S100: Modeling is performed for the process of providing frequency regulation reserve, inertia, and voltage regulation auxiliary services for energy storage and generating units. The modeling for providing frequency regulation reserve for energy storage and generating units includes constraints on the power of the generating unit's frequency regulation reserve, the power of the generating unit's frequency regulation reserve being limited by the generating unit's output, constraints on the composition of the total frequency regulation reserve of energy storage, constraints on the upper and lower limits of the total frequency regulation reserve of energy storage, constraints on the energy reserve of the total frequency regulation of energy storage, and constraints on the energy recovery of the total frequency regulation of energy storage. The modeling for providing inertia services for energy storage and generating units includes constraints on the inertia of generating units, constraints on the power of energy storage inertia, constraints on the energy of energy storage inertia, and constraints on the energy storage inertia coefficient. The modeling for providing voltage regulation services for energy storage includes constraints on the voltage droop control of energy storage, constraints on the capacity of energy storage converters, and constraints on the power factor of energy storage converters. Step S200 involves modeling the inertial response, frequency regulation, and voltage regulation processes of the power system. The inertial response modeling includes constraints on the total primary frequency regulation reserve of generating units, the total primary frequency regulation reserve of energy storage, the total inertia of generating units, and the total inertia of energy storage. The frequency regulation modeling includes constraints on the maximum rate of frequency change, the maximum quasi-steady-state frequency deviation, and the minimum frequency point. The voltage regulation modeling includes constraints on voltage deviation and system voltage regulation demand. Step S300: Model the power system dispatch problem that includes ancillary services provided by energy storage. The objective function of the dispatch includes minimizing the cost related to generating units and the total cost related to new energy and energy storage. In the modeling, the operating constraints of energy storage equipment include energy storage charging power constraints, energy storage discharging power constraints, state of charge timing constraints, upper and lower limits of state of charge constraints, and consistency constraints at the beginning and end of the dispatch cycle. The operating constraints of generating units include active power output constraints, reactive power output constraints, unit ramping constraints, minimum online / offline time constraints, and logic constraints of unit switching actions and online status. Step S400: By solving the power system dispatching problem in step S300, the solution of the 0-1 variables obtained is substituted into the power system dispatching problem, and the non-convex joint optimization problem is transformed into a market clearing problem that only includes continuous variables. The dual multipliers of frequency regulation reserve, inertia and voltage regulation ancillary services are solved. Step S500: Based on the dual multipliers of the constraints corresponding to each auxiliary service, calculate the service cost of each energy storage auxiliary service to achieve value assessment. Step S500 includes: Step S501: Construct the Lagrangian function for a market clearing model containing only continuous variables; Step S502: Calculate the partial derivative of the Lagrange function constructed in step S501 with respect to the virtual inertia corresponding to each auxiliary service. Step S503 yields the formula for the cost of virtual inertia corresponding to each auxiliary service.

2. The method for evaluating the value of energy storage providing multiple ancillary services according to claim 1, characterized in that, In step S100, The model for energy storage and generating units providing frequency regulation backup services is as follows: Unit frequency regulation reserve power constraints: ; The unit's frequency regulation reserve power is limited by the unit's output: ; Constraints on the composition of total frequency regulation reserve for energy storage: ; Upper and lower limits of energy storage total frequency regulation reserve: ; Total frequency regulation energy reserve constraints for energy storage: ; Energy storage total frequency regulation energy recovery constraint: ; in, Let u be the standby frequency regulation capacity of a single thermal power unit at time t. This indicates the operating status of the generator unit; 1 represents operation, and 0 represents shutdown. This represents the maximum frequency regulation capacity that a single thermal power unit can provide. For the single unit output of thermal power units, This represents the maximum output of a single thermal power unit. The total reserve capacity for energy storage used for frequency regulation and inertia services. The inertial power of the energy storage s For primary frequency regulation backup of energy storage, , and These are the charging power, discharging power, and maximum discharging power of a single energy storage unit, respectively. For energy storage level, The duration of one frequency modulation. For discharge efficiency, The energy required to provide inertia for energy storage For the minimum energy level of energy storage, Time is required for energy recovery; The model for energy storage and generating units providing inertia services is as follows: Unit inertia constraints: ; Energy storage inertia power constraints: ; Energy constraint of energy storage inertia: ; Energy storage inertia coefficient constraint: ; in, The inertia coefficient of the unit. The inertia coefficient of energy storage, The nominal frequency of the system. The maximum permissible rate of change of frequency. For the maximum permissible frequency deviation, The maximum inertia coefficient for energy storage. For energy storage collection, A collection of runtime segments. Let u be the inertia coefficient of unit u at time t; The model for providing voltage regulation services for energy storage is as follows: Energy storage voltage regulation droop control constraints: ; Energy storage converter capacity constraints: ; Power factor constraints for energy storage converters: ; in, Reactive power regulation backup provided for energy storage This represents the droop control coefficient of the energy storage reactive power control loop. For system voltage regulation requirements, i.e., the portion of the grid connection point voltage deviation that exceeds the maximum limit, Let be the power of the stored energy s discharged externally at time t, then we have , For the maximum capacity of the energy storage grid-connected converter, This is the minimum power factor allowed for converter operation. Reactive power regulation backup provided for energy storage.

3. The method for evaluating the value of energy storage providing multiple ancillary services according to claim 2, characterized in that, In step S200, The inertial response model of a power system is as follows: Unit primary frequency regulation standby constraints: ; Energy storage primary frequency regulation reserve constraints: ; Unit total inertia constraint: ; Total inertia constraint of energy storage: ; in, The total frequency regulation capacity of thermal power units. For the total frequency regulation capacity of energy storage, The total inertia level of the thermal power unit. This represents the total inertia level of energy storage; The power system frequency dispatch model is as follows: Maximum rate of change constraint: ; Maximum quasi-steady-state frequency deviation constraint: ; Minimum frequency constraint: ,in ; in, For the system load deviation, This is the maximum permissible quasi-steady-state frequency deviation limit. The damping coefficient is... The total load at time t; The total inertia of the system, For energy storage frequency regulation time constant, The frequency regulation time constant for thermal power plants; The voltage regulation model of the power system is as follows: Voltage deviation constraint: ; System voltage regulation requirement constraints: ; in, This refers to the voltage deviation at the grid connection point caused by a disturbance at node i. Let be the voltage sensitivity coefficient of node i to the grid connection point. For the reactive power disturbance occurring at node i, For the system node set, It is the allowable deviation of the grid connection point bus voltage as specified by the system. To meet the system's voltage regulation requirements, all nodes' reactive power disturbances are examined, and the disturbances at the nodes that have the greatest impact on the grid connection voltage are taken into account for the voltage regulation requirements.

4. The method for evaluating the value of energy storage providing multiple ancillary services according to claim 3, characterized in that, In step S300, the objective function of the power system dispatch problem involving energy storage providing ancillary services is: in, This represents the total cost associated with the generator unit. This represents the total cost related to new energy and energy storage. , and These represent collections of generating units, new energy sources, and energy storage, respectively. , , , , These are the unit output price, no-load cost, start-up cost, unit price for primary frequency regulation service, and unit price for inertia service of thermal power units. , , , These are the unit price of new energy output, the unit price of energy storage discharge / electricity purchase, the unit price of energy storage fast frequency regulation, and the unit price of energy storage inertia. This indicates the startup action of unit u at time t. Power output for new energy sources Purchase power for energy storage Let be the discharge power of the energy storage element s to be selected at time t.

5. The method for evaluating the value of energy storage providing multiple ancillary services according to claim 3, characterized in that, In step S300, the constraints of the power system dispatch problem involving energy storage providing ancillary services include: Energy storage device operating constraints include: Energy storage charging power constraints: ; Energy storage discharge power constraints: ; State of charge timing constraints: ; Upper and lower limits of state of charge constraints: ; Consistency constraint from beginning to end of scheduling cycle: ; in, This represents the charging and discharging status of energy storage s at time t, with 1 for charging and 0 for discharging. , These represent the upper limits of the charging and discharging power of the selected energy storage element s, respectively. This represents the state of charge of the candidate energy storage element s at time t. , Let S represent the charging efficiency and discharging efficiency of the energy storage element S, respectively. , These represent the state of charge of the energy storage element at the beginning and end of the dispatch cycle, respectively. , These represent the charging and discharging power of the energy storage element s at time t, respectively; Unit operating constraints include: Unit active power output constraints: ; Unit reactive power output constraints: ; Unit ramp-up constraints: , ; Minimum online and offline time constraints for the unit: , , A collection of generator units. This represents the lower limit of the active power of the generator unit. , These are the lower and upper limits of the unit's reactive power, respectively. Unit switching actions and online status logic constraints: ; in, , These represent the active and reactive power output of unit u at time t, respectively. , These represent the maximum uphill and downhill ramp power of unit u, respectively. This is a 0-1 variable representing the unit shutdown action, where 1 indicates the action. and These represent the minimum online and offline times of unit u, respectively. This refers to the startup action of unit u at time t.

6. The method for evaluating the value of energy storage providing multiple ancillary services according to claim 5, characterized in that, Step S400 includes: Step S401: By pre-solving the power system dispatch problem established in step S300, which includes ancillary services provided by energy storage, 0-1 variables representing the start-up, shutdown actions, and online status of unit u at time t are obtained. , , The solution, and the 0-1 variables representing the charging and discharging states of the energy storage s at time t. The solution; Step S402: Substitute the solution of 0-1 variables obtained in step S401 into the power system dispatch problem established in step S300, which includes ancillary services provided by energy storage, and transform the non-convex joint optimization problem into a market clearing problem that only includes continuous variables. Step S403: For the market clearing problem, the dual multipliers of frequency regulation reserve, inertia and voltage regulation auxiliary services are solved by constructing a Lagrangian function.

7. The method for evaluating the value of energy storage providing multiple ancillary services according to claim 6, characterized in that, The Lagrange function is constructed as follows: in, The dual multiplier for the system's maximum rate of change of frequency constraint. The dual multiplier for the system's maximum quasi-steady-state frequency deviation constraint. , , These are the dual multipliers corresponding to the constraints at the system's lowest frequency point, satisfying... , , , These are the dual multipliers of the total inertia constraint and the total primary frequency regulation constraint, respectively. , These are the dual multipliers for the total energy storage inertia constraint and the total primary frequency regulation constraint, respectively. The dual multiplier for the voltage regulation droop control constraint in energy storage. For the dual multiplier of the capacity constraint of the energy storage converter, , For the dual multiplier of the power factor constraint of the energy storage converter, Indicates constraints that are not ancillary services. Let be the objective function. This represents the maximum output of a single thermal power unit (u). This is the minimum power factor allowed for converter operation. ,for The corresponding tangent value.

8. The method for evaluating the value of energy storage providing multiple ancillary services according to claim 1, characterized in that, In step S503, The cost of providing virtual inertia assistance services through energy storage is: ； in, The cost of providing virtual inertia for energy storage For the rated frequency, , These are the dual multipliers of the system's maximum rate of change of frequency constraint and the total inertia constraint of energy storage, respectively. , , These are the dual multipliers corresponding to the constraints at the lowest system frequency points. Let be the objective function. Virtual inertia provided for energy storage; The cost of energy storage providing fast frequency regulation ancillary services is: ； in, The price of providing rapid frequency regulation for energy storage, The energy storage time constant, This is the maximum allowable frequency deviation. The dual multiplier for the system's maximum quasi-steady-state frequency deviation constraint. The dual multiplier of the unit's primary frequency regulation constraint. Total frequency regulation capacity for energy storage; The cost of energy storage providing voltage regulation ancillary services is: ； in, The cost of providing voltage regulation services for energy storage Reactive power regulation backup provided for energy storage The dual multiplier for the voltage regulation droop control constraint in energy storage. For the dual multiplier of the capacity constraint of the energy storage converter, , It is the dual multiplier for the power factor constraint of the energy storage converter.

9. A value assessment system for energy storage providing multiple ancillary services, characterized in that, A method for assessing the value of providing multiple ancillary services through energy storage as described in any one of claims 1-8, comprising: The ancillary services modeling module is used to model the process of providing frequency regulation reserve, inertia and voltage regulation ancillary services for energy storage and generating units. The power system modeling module is used to model the inertial response, frequency regulation, and voltage regulation processes of power systems. The power system dispatch modeling module is used to model power system dispatch problems that include ancillary services provided by energy storage. The power system scheduling solution module is used to obtain the dual multipliers of the constraints corresponding to each auxiliary service by solving the power system scheduling problem; The ancillary service cost calculation module is used to calculate the service cost of each energy storage service based on the dual multipliers of the constraints corresponding to each ancillary service, thereby realizing value assessment.

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