Value evaluation method and system for providing multiple auxiliary services through energy storage

Abstract

The invention relates to a value evaluation method and system for providing multiple auxiliary services by energy storage. The method comprises the following steps: step S100, modeling is carried out for the process of providing frequency modulation standby, inertia and voltage regulation auxiliary services by energy storage and a unit; s200, modeling is carried out according to inertia response, frequency modulation and voltage regulation processes of the power system; s300, modeling is carried out for the scheduling problem of the electric power system containing energy storage and providing auxiliary services; step S400, obtaining a dual multiplier of a constraint corresponding to each auxiliary service by solving the power system scheduling problem in the step S300; and step S500, calculating the service cost of each auxiliary service for energy storage based on the dual multiplier of the corresponding constraint of each auxiliary service. Compared with the prior art, the invention provides the value evaluation method for providing multiple auxiliary services for energy storage, so that technical reference is provided for the pricing standard for providing the auxiliary services for energy storage, and the configuration efficiency of auxiliary service resources can be optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage scheduling and ancillary service pricing, and in particular to a value assessment method and system for providing multiple ancillary services provided by energy storage. Background Art

[0002] At present, the penetration rate of renewable energy in China's power system is constantly increasing. The high proportion of new energy access has put forward higher requirements on the safety and reliability of the power system. The participation of energy storage systems in providing auxiliary services has 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 auxiliary service market and improve the efficiency of allocating auxiliary service resources.

[0003] For many years, there have been rich research results at home and abroad on the costs and benefits of energy storage providing auxiliary services. For example, reference 1 "Design of frequency regulation auxiliary service market mechanism and dispatch strategy adapted to energy storage participation" (Lu Qiuyu, Yang Yinguo, Xie Pingping, Chen Yue, Wu Jiekang, Lei Zhen. Power System Technology, 2023, 47(12): 4971-4989.) designed a frequency regulation auxiliary market operation mechanism adapted to energy storage participation, and used subjective and objective weight methods to calculate the weight coefficients of comprehensive frequency regulation performance indicators of different types of frequency regulation resources, characterize the frequency regulation performance differences of multiple types of frequency regulation resources, compare frequency regulation demands in different trading periods horizontally, introduce time relaxation factors to optimize the marginal clearing price of the trading period, and use spatial relaxation factors to quantify the replacement capacity of different frequency regulation resources to form a reasonable compensation for fast and slow frequency regulation resources. Reference 2 "Design of the market mechanism for independent energy storage participating in frequency regulation auxiliary services" (Lin Azhu, Ke Qinghui, Jiang Yuewen. Electric Power Automation Equipment, 2022, 42(12): 26-34.) sets the frequency regulation performance indicators of regulation accuracy, response time, and regulation speed, and introduces efficiency factors to reflect the advantages of fast frequency regulation resources, thereby encouraging the market to actively introduce independent energy storage to participate in frequency regulation to optimize the allocation of frequency regulation resources in the system. Reference 3 "Comprehensive economic benefit analysis of energy storage participating in wind power auxiliary services" (Ma Meiting, Yuan Tiejiang, Chen Guangyu, Cai Gaolei, Peng Shengjiang, Zhang Zengqiang. Power System Technology, 2016, 40(11): 3362-3367.) studies the economic feasibility of battery energy storage power stations participating in wind power auxiliary services based on risk elimination, establishes a comprehensive economic benefit model for its participation in wind power auxiliary services, and evaluates the benefits of energy storage power stations participating in wind power auxiliary services through economic indicators such as the return on investment and investment payback period of energy storage power stations. Reference 4 "Market Clearing Coordination Mechanism for 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.) established a market clearing model for frequency regulation ancillary services, considered capacity quotations and mileage quotations in the ancillary service quotation submission, and calculated the opportunity cost of providing frequency regulation ancillary services to form a comprehensive quotation. The market clearing model including independent energy storage analyzes the benefits and behavior of independent energy storage participating in the market.

[0004] Based on various research results, there have been a number of patent applications involving the cost or pricing of energy storage participating in ancillary services. For example, patent application 1 "Energy Storage Participating in Ancillary Services Cost Model" (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 evaluation method for energy storage participating in ancillary services, including the fixed cost, variable cost, and unit cost of energy storage power stations. The types of ancillary services involved include peak load regulation and frequency regulation services, and their unit cost is mainly obtained by dividing the annual value of the full life cycle cost by the annual power processing or total frequency regulation mileage. Patent application 2 "A coordinated clearing method for the electric energy and frequency regulation ancillary service markets involving energy storage" (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.) constructs clearing models for the electric energy market and the frequency regulation ancillary service market respectively, 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 at the same time, settles the income of energy storage in the frequency regulation market, and realizes the sequential clearing and joint clearing of the electric energy and frequency regulation ancillary service markets. Patent application 3 "A compensation method for battery energy storage participating in grid voltage regulation auxiliary 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 auxiliary services, establishes a cost structure model for battery energy storage participating in grid voltage regulation auxiliary services, including converter loss costs and opportunity costs, considers various situations in which 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 auxiliary services.

[0005] However, the traditional method has the following inherent defects:

[0006] 1. The operating 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, and does not focus on the specific operation process of energy storage providing auxiliary services to the power system. Summary of the invention

[0008] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a value assessment method and system for providing multiple auxiliary services by energy storage, so as to solve or partially solve the problem of unsatisfactory efficiency of auxiliary service resources.

[0009] The purpose of the present invention can be achieved by the following technical solutions:

[0010] One aspect of the present invention provides a method for evaluating the value of multiple auxiliary services provided by energy storage, comprising the following steps:

[0011] Step S100, modeling the process of energy storage and generators providing frequency regulation standby, inertia and voltage regulation auxiliary services;

[0012] Step S200, modeling the inertia response, frequency regulation and voltage regulation process of the power system;

[0013] Step S300, modeling a power system dispatch problem including energy storage providing auxiliary services;

[0014] Step S400, obtaining dual multipliers of constraints corresponding to each auxiliary service by solving the power system dispatch problem of step S300;

[0015] Step S500, based on the dual multipliers of the constraints corresponding to each auxiliary service, the service cost of each auxiliary service of the energy storage is calculated to achieve value evaluation.

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

[0017] The frequency regulation reserve service provided by energy storage and units is modeled as:

[0018] Unit frequency regulation standby power constraints:

[0019] The unit frequency regulation standby power is limited by the unit output:

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

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

[0022] Total frequency regulation energy reserve constraint of energy storage:

[0023] Energy storage total frequency regulation energy recovery constraints: in, It is the frequency regulation reserve capacity of a single thermal power unit. The running status of the unit, 1 means running, 0 means shutdown, It is the maximum frequency regulation capacity that a single thermal power unit can provide. For the output of a single thermal power unit, is the maximum output of a single thermal power unit, The total reserve capacity of energy storage for frequency regulation and inertia services, is the inertia power of energy storage, It is the primary frequency regulation backup for energy storage. and They are the charging power, discharging power and maximum discharging power of a single energy storage unit, is the energy storage level, t reg,dur is the duration of a frequency modulation, η d is the discharge efficiency, The energy required to provide inertia for energy storage, is the minimum energy level of energy storage, t soc,re Requires time for energy recovery;

[0024] The inertia service provided by energy storage and units is modeled as:

[0025] Unit inertia constraint:

[0026] Energy storage inertia power constraint:

[0027] Energy storage inertia energy constraint:

[0028] Energy storage inertia coefficient constraint: in, is the inertia coefficient of the unit, is the inertia coefficient of energy storage, f0 is the nominal frequency of the system, RoCoF max is the maximum allowable frequency change rate, Δf max is the maximum allowable frequency deviation, is the maximum inertia coefficient of energy storage, ESSs is the energy storage set, is the set of running time periods;

[0029] The voltage regulation service provided by energy storage is modeled as:

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

[0031] Energy storage converter capacity constraints:

[0032] Energy storage converter power factor constraint: Among them, ΔQ s Reactive voltage regulation backup provided for energy storage, k Q is the droop control coefficient of the energy storage reactive control loop, Δx U P is the system voltage regulation requirement, that is, the voltage deviation at the grid point exceeds the maximum limit. s,t is the power discharged from the energy storage s at time t, is the maximum capacity of the energy storage grid-connected converter, It is the minimum power factor allowed for the converter operation.

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

[0034] The inertia response of the power system is modeled as:

[0035] Total primary frequency regulation reserve constraints of the unit:

[0036] Total primary frequency regulation reserve constraints of energy storage:

[0037] Total inertia constraint of the unit:

[0038] Constraints on total energy storage inertia: in, is the total frequency regulation capacity of thermal power units, is the total frequency regulation capacity of the energy storage, is the total inertia level of the thermal power unit, is the total inertia level of energy storage;

[0039] The power system frequency dispatch model is:

[0040] Maximum frequency change rate constraint:

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

[0042] Frequency minimum point constraint: in in, is the load deviation of the system, is the maximum allowable quasi-steady-state frequency deviation limit, f D is the damping coefficient, is the total load at time t; is the total inertia of the system, T e is the energy storage frequency modulation time constant, T g is the thermal power frequency modulation time constant;

[0043] The power system voltage regulation model is:

[0044] Voltage deviation constraint:

[0045] System voltage regulation requirements constraints: Among them, ΔU PCC,i is the voltage deviation caused to the grid connection point by the disturbance of node i, is the voltage sensitivity coefficient of node i to the grid connection point, ΔQi is the reactive disturbance occurring at node i, Ω N is the system node set, is the allowable grid-connection point bus voltage deviation specified by the system, Δx U In order to meet the system voltage regulation requirements, the reactive power disturbance conditions of all nodes are taken, and the node disturbance that has the greatest impact on the grid connection point voltage will be considered as the voltage regulation requirement.

[0046] As a preferred technical solution, in step S300, the objective function of the power system dispatch problem including energy storage providing auxiliary services is:

[0047]

[0048] Among them, VC represents the total cost related to the unit, WSC represents the total cost related to new energy and energy storage, and Ω G ,Ω w and Ω S Respectively represent the collection of units, new energy and energy storage; They are the unit price of thermal power unit output, no-load cost, startup cost, unit price of primary frequency regulation service, unit price of inertia service, c w 、c s , They are the unit price of new energy output, the unit price of energy storage discharge / power purchase, the unit price of energy storage rapid frequency regulation, and the unit price of energy storage inertia; represents the starting action of unit u at time t, For the output power of new energy, Purchase electrical power for energy storage.

[0049] As a preferred technical solution, in step S300, the constraints of the power system scheduling problem including energy storage providing auxiliary services include:

[0050] Energy storage equipment operation constraints, including:

[0051] Energy storage charging power constraints:

[0052] Energy storage discharge power constraints:

[0053] State of Charge Timing Constraints:

[0054] State of charge upper and lower limit constraints:

[0055] Constraints on consistency throughout the scheduling cycle: SOC s,0 =SOC s,end ;

[0056] Among them, qs,t It represents the charge and discharge flag variable of energy storage s at time t, charging is 1, and discharging is 0. They represent the upper limits of the charging and discharging power of the selected energy storage element s, SOC s,t represents the charge state of the selected energy storage element s at time t, η c , η d Respectively represent the charging efficiency and discharging efficiency of the energy storage element s, SOC s,0 , SOC s,end They respectively represent the charge state of the energy storage element at the beginning and end of the dispatch cycle;

[0057] Unit operating constraints, including:

[0058] Unit active output constraints:

[0059] Reactive power output constraints of the unit:

[0060] Unit climbing constraints:

[0061] Minimum online and offline time constraints for units:

[0062] Logical constraints on unit switch action and online status: in, They represent the active and reactive power output of unit u at time t, RU u , RD u Respectively represent the maximum up and down climbing power of unit u, TU is a 0-1 variable indicating the unit shutdown action, 1 indicates action, u and TD u Respectively represent the minimum online and offline time of unit u.

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

[0064] Step S401, by pre-solving the power system dispatch problem including energy storage providing auxiliary services established in step S300, 0-1 variables representing the start-up, shutdown action and online status of unit u at time t are obtained. The solution of , and the 0-1 variable q representing the charge and discharge state of the energy storage s at time t s,t The solution;

[0065] Step S402, bringing the solution of the 0-1 variable obtained in step S401 into the power system dispatch problem including energy storage providing auxiliary services established in step S300, and converting the non-convex joint optimization problem into a market clearing problem including only continuous variables;

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

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

[0068]

[0069] Among them, ω ro is the dual multiplier of the maximum frequency change rate constraint of the system, ω ss is the dual multiplier of the maximum quasi-steady-state frequency deviation constraint of the system, μ, λ1, λ2 are the dual multipliers corresponding to the constraints of the lowest frequency point of the system, satisfying μ≥0, are the dual multipliers of the total inertia constraint and the total primary frequency regulation constraint of the unit, are the dual multipliers of the total inertia constraint of energy storage and the total primary frequency modulation constraint, ω dr is the dual multiplier of the energy storage voltage droop control constraint, ω ca is the dual multiplier of the energy storage converter capacity constraint, ω fa1 ,ω fa2 is the dual multiplier of the power factor constraint of the energy storage converter, … represents the constraint term of non-auxiliary services.

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

[0071] Step S501, constructing a Lagrangian function of a market clearing model containing only continuous variables;

[0072] Step S502, obtaining the partial derivative of the Lagrangian function constructed in step S501 with respect to the virtual inertia corresponding to each auxiliary service;

[0073] Step S503: obtaining a formula expression of the cost of the virtual inertia corresponding to each auxiliary service.

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

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

[0076]

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

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

[0079]

[0080] in, The cost of providing fast frequency regulation for energy storage, T e is the energy storage time constant, Δf max is the maximum allowable frequency deviation, ω ss is the dual multiplier of the maximum quasi-steady-state frequency deviation constraint of the system, is the dual multiplier of the total primary frequency modulation constraint;

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

[0082]

[0083] in, The cost of providing voltage regulation service for energy storage, ΔQ s,t Reactive voltage regulation backup provided for energy storage, ω dr is the dual multiplier of the energy storage voltage droop control constraint, ω ca is the dual multiplier of the energy storage converter capacity constraint, ω fa1 ,ω fa2 is the dual multiplier of 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 multiple auxiliary services, including:

[0085] Ancillary service modeling module, used to model the process of energy storage and units providing frequency reserve, inertia and voltage regulation auxiliary services;

[0086] The power system modeling module is used to model the inertia response, frequency regulation and voltage regulation process of the power system;

[0087] The power system dispatch modeling module is used to model the power system dispatch problem including the ancillary services provided by energy storage;

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

[0089] The auxiliary service cost calculation module is used to calculate the service cost of each energy storage service based on the dual multiplier of the corresponding constraints of each auxiliary service to achieve value evaluation.

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

[0091] (1) Optimizing the allocation efficiency of ancillary service resources: The present invention more accurately models the energy storage equipment’s participation in inertia response, frequency regulation, and voltage regulation, so that its flexibility can be used for system frequency and voltage regulation and scheduling. The cost of each ancillary service provided by the energy storage is calculated through the Lagrange multipliers of each ancillary service constraint, and the ancillary service pricing is performed, thereby optimizing the allocation efficiency of ancillary service resources.

[0092] (2) Good safety and reliability of the power system: The present invention adds inertia response, frequency regulation and voltage regulation constraints to the system dispatching model. Compared with the traditional system dispatching model, it can reflect the restrictions of auxiliary 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 dispatching problem in which energy storage participates in ancillary services, the present invention first pre-solves the mixed integer programming and then solves the second-order cone programming to obtain the parameters required to calculate the cost of providing ancillary services by energy storage, thereby ensuring the solution speed and efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0094] Figure 1 A schematic diagram of a value assessment method for providing multiple auxiliary services for energy storage in an embodiment;

[0095] Figure 2 A schematic diagram of a detailed process of a value assessment method for providing multiple auxiliary services for energy storage in an embodiment;

[0096] Figure 3 Schematic diagram of a value assessment system for providing multiple auxiliary services for energy storage in an embodiment. DETAILED DESCRIPTION

[0097] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0098] Example 1

[0099] In view of the problems existing in the above-mentioned prior art, this embodiment provides a value assessment method for energy storage to provide multiple auxiliary services, see Figure 1 and Figure 2 , the method comprises the following steps

[0100] Step S000, see Figure 2, pre-enter the unit parameters, energy storage equipment parameters, system parameters, system frequency parameters and renewable energy output parameters.

[0101] Step S100, an operation model in which energy storage and generator sets provide inertia, frequency regulation standby and voltage regulation services.

[0102] The model includes the frequency reserve model of the unit, the inertia model of the 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, which are reflected as constraints in the optimization model.

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

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

[0105] Reserve power constraints:

[0106] The standby power is limited by the unit output: in, It is the frequency regulation reserve capacity of a single thermal power unit. The running status of the unit, 1 means running, 0 means shutdown, It is the maximum frequency regulation capacity that a single thermal power unit can provide. For the output of a single thermal power unit, It 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 constraint: in, is the inertia coefficient of the unit.

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

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

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

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

[0114] Total frequency regulation energy reserve constraint of energy storage:

[0115] Energy storage total frequency regulation energy recovery constraints: in, The total reserve capacity of energy storage for frequency regulation and inertia services, is the inertia power of energy storage, It is used as a primary frequency regulation backup for energy storage; and They are the charging power, discharging power and maximum discharging power of a single energy storage unit respectively; is the energy storage level, t reg,dur is the duration of a frequency modulation, η d is the discharge efficiency, The energy required to provide inertia for energy storage, is the minimum energy level of energy storage; t soc,re The total frequency regulation energy recovery constraint of energy storage means that the energy consumed by energy storage in frequency regulation service should be charged and replenished in time within the required time, and this additional charging power is borne by the unit.

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

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

[0118] Energy storage inertia power constraint:

[0119] Energy storage inertia energy constraint:

[0120] Energy storage inertia coefficient constraint: in, is the inertia coefficient of energy storage, f0 is the nominal frequency of the system, RoCoF max is the maximum allowable frequency change rate; Δf max is the maximum allowable frequency deviation; is the maximum inertia coefficient of energy storage, ESSs is the energy storage set, A collection of runtime periods.

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

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

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

[0124] Energy storage converter capacity constraints:

[0125] Energy storage converter power factor constraint: Among them, ΔQ s Reactive voltage regulation backup provided for energy storage, k Q is the droop control coefficient of the energy storage reactive control loop, Δx UP is the system voltage regulation requirement, that is, the voltage deviation at the grid point exceeds the maximum limit; s,t is the power discharged from the energy storage s at time t, is the maximum capacity of the energy storage grid-connected converter; It is the minimum power factor allowed for the 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 sorting, it can be restated as the following linear constraint form:

[0127] Energy storage converter power factor constraint (linearization): in, for The corresponding tangent value.

[0128] Step S200: system inertia response, frequency modulation and voltage regulation model.

[0129] Specifically, in this embodiment, the system inertia response, frequency regulation and voltage regulation models include: a system total frequency standby metering model, a system frequency safety model, and a system voltage regulation safety 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] Total primary frequency regulation reserve constraints of the unit:

[0133] Total primary frequency regulation reserve constraints of energy storage:

[0134] Total inertia constraint of the unit:

[0135] Constraints on total energy storage inertia: in, It is the total frequency regulation capacity of thermal power units; Total frequency regulation capacity for energy storage; is the total inertia level of the thermal power unit; is 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 frequency change rate constraint:

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

[0140] Frequency minimum point constraint: in in, is the load deviation of the system; is the maximum allowable quasi-steady-state frequency deviation limit, f D is the damping coefficient, is the total load at time t; is the total inertia of the system, T e is the energy storage frequency modulation time constant, T g is the thermal power frequency modulation time constant.

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

[0142] Frequency minimum point constraint (second-order cone form):

[0143]

[0144] In this embodiment, the frequency minimum point constraint can be further written as a standard form with separate items, which is convenient for solving the subsequent dual multiplier:

[0145]

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

[0147] Voltage deviation constraint: Among them, ΔU PCC,i is the voltage deviation caused to the grid connection point by the disturbance of node i, is the voltage sensitivity coefficient of node i to the grid connection point, ΔQ i is the reactive power disturbance occurring at node i.

[0148] In this embodiment, the voltage sensitivity coefficient is an element in the sensitivity matrix of the voltage deviation with respect to the reactive disturbance. The relationship between the voltage deviation and the reactive disturbance can be expressed as: ΔU=S0ΔQ, where ΔU is the voltage deviation vector, ΔQ is the reactive 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 of the node susceptance matrix (B ij ) -1 , this embodiment adopts this simplified method.

[0150] System voltage regulation requirements constraints: Among them, Ω N is the system node set, is the allowable grid-connection point bus voltage deviation specified by the system, ΔxU In order to meet the system voltage regulation requirements, the reactive power disturbance conditions of all nodes are taken, and the node disturbance that has the greatest impact on the grid connection point voltage will be considered as the voltage regulation requirement.

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

[0152] In this embodiment, the system voltage regulation demand constraint is a piecewise function, which introduces non-convex factors 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 is the auxiliary variable introduced, y Q is an auxiliary 0-1 variable introduced, M represents a large constant, Δx U Indicates the system's voltage regulation requirements.

[0159] Step S300, including a power system dispatching model for providing auxiliary services with energy storage.

[0160] Specifically, in this embodiment, the objective function of the power system dispatch model including energy storage providing auxiliary services is to minimize the sum of the power of each device and the declared cost of the auxiliary services:

[0161]

[0162] Among them, VC represents the total cost related to the unit, WSC represents the total cost related to new energy and energy storage, and Ω G ,Ω w and Ω S Respectively represent the collection of units, new energy and energy storage; They are the unit price of thermal power unit output, no-load cost, startup cost, unit price of primary frequency regulation service, unit price of inertia service, c w 、c s , They are the unit price of new energy output, the unit price of energy storage discharge / power purchase, the unit price of energy storage rapid frequency regulation, and the unit price of energy storage inertia; represents the starting action of unit u at time t, For the output power of new energy, Purchase electrical power for energy storage.

[0163] In this embodiment, the constraints of the power system dispatch model including energy storage providing auxiliary services include the models described in S100 and S200 above and the energy storage device operation model, the unit operation model, and the system operation model.

[0164] (1) Energy storage equipment operation model.

[0165] Energy storage charging power constraints:

[0166] Energy storage discharge power constraints:

[0167] State of Charge Timing Constraints:

[0168] State of charge upper and lower limit constraints:

[0169] Constraints on consistency throughout the scheduling cycle: SOC s,0 =SOC s,end ;

[0170] Among them, q s,t Indicates the charge and discharge flag variable of energy storage s at time t, charging is 1 and discharging is 0; They represent the upper limits of the charging and discharging power of the selected energy storage element s; SOC s,t represents the charge state of the selected energy storage element s at time t, η c , η d Respectively represent the charging efficiency and discharging efficiency of the energy storage element s; SOC s,0 , SOC s,end They respectively represent the charge state of the energy storage element at the beginning and end of the scheduling cycle.

[0171] (2) Unit operation model.

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

[0173] Unit active output constraints:

[0174] Reactive power output constraints of the unit:

[0175] Unit climbing constraints:

[0176] Minimum online and offline time constraints for units:

[0177] Logical constraints on unit switch action and online status: in, They represent the active and reactive power output of unit u at time t, RU u , RD u Respectively represent the maximum up and down climbing power of unit u. TU is a 0-1 variable indicating the unit shutdown action: 1 indicates action, TU u and TD u Respectively represent the minimum online and offline time of unit u.

[0178] (3) System operation model.

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

[0180] Node voltage constraints:

[0181] Line flow constraints:

[0182] Power balance constraints:

[0183] Second-order cone relaxation constraints: Among them, Ω N represents the set of system nodes, Ω E represents the set of transmission lines in the system, is the auxiliary variable introduced for the second-order cone power flow (no constraints are added to this equation), V i represents the voltage phasor at node i, P ij represents the active power transmitted from node i to node j, Q ij represents the reactive power transmitted from node i to node j, G ij , B ij represents the conductance and susceptance of line ij, Represents the active power generation and active load on the node, Represents the reactive power generation and reactive load on the node.

[0184] Step S400, solving a power system dispatch model including energy storage providing auxiliary services, and obtaining dual multipliers of constraints corresponding to each auxiliary service.

[0185] Specifically, in this implementation example, the value assessment method for various ancillary services provided by energy storage adopts 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 energy storage providing auxiliary services established in step S300 is a mixed integer second-order cone model, which is injected with non-convexity by a large number of 0-1 variables and cannot directly obtain the dual variables of the constraints. A restriction model is selected 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 energy storage providing auxiliary services established in step S300 to obtain the values ​​of 0-1 variables, including 0-1 variables representing the start and stop actions of the unit. A 0-1 variable representing the online status of unit u at time t 0-1 variable q representing the charge and discharge state of energy storage s at time t s,t .

[0188] Step S402: bring the solution of the 0-1 variable into the original scheduling model, that is,

[0189] Step S403: All unknown 0-1 variables in the original model are replaced by the results obtained by pre-solving, 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 the auxiliary services can be obtained by solving the market clearing model containing only continuous variables. The dual multipliers are expressed in the Lagrangian function as follows:

[0191]

[0192] Among them, ω ro is the dual multiplier of the maximum frequency change rate constraint of the system; ω ss is the dual multiplier of the maximum quasi-steady-state frequency deviation constraint of the system; μ, λ1, λ2 are the dual multipliers corresponding to the constraints of the lowest frequency point of the system, satisfying μ ≥ 0, are the dual multipliers of the total inertia constraint and the total primary frequency regulation constraint of the unit respectively; are the dual multipliers of the total inertia constraint of energy storage and the total primary frequency modulation constraint respectively; ω dr is the dual multiplier of the energy storage voltage droop control constraint; ω ca is the dual multiplier of the energy storage converter capacity constraint; ω fa1 ,ω fa2is the dual multiplier of the power factor constraint of the energy storage converter; ... represents other constraints related to non-auxiliary services, such as node voltage constraints:

[0193] Step S500, the cost of providing auxiliary services by energy storage is calculated by the dual multipliers of the corresponding constraints of each auxiliary service. The marginal pricing theory is adopted, and the condition that the optimal gradient is 0 in the Karush-Kuhn-Tucker (KKT) condition is used to obtain the partial derivative of the Lagrangian function of the optimization problem with respect to the auxiliary service resource variable, and the calculation formula of each auxiliary service cost is derived, so as to calculate the cost of providing auxiliary services by energy storage by the dual multipliers of the corresponding constraints of each auxiliary service.

[0194] Specifically, in this embodiment, the value assessment method for energy storage to provide a variety of auxiliary services adopts the marginal pricing method to obtain the virtual inertia provided by the energy storage. Take this as an example, the specific steps are as follows:

[0195] Step S501, construct the Lagrangian function of the market clearing model containing only continuous variables. It can be expressed as Among them, F total is the objective function, For other variables, Contains virtual inertia The constraint, λ i is the corresponding dual multiplier, Does not include virtual inertia Constraint, μ i is the corresponding dual multiplier.

[0196] Step S502, obtaining the Lagrangian function for the virtual inertia Since the convex optimization model satisfies the KKT condition at the optimal solution, and the stationarity condition in the KKT condition requires that the gradient of the Lagrangian function at the optimal solution is 0, the Lagrangian function is about The partial derivative of is also 0, so

[0197] Step S503, deriving virtual inertia Marginal price formula. Virtual inertia The marginal price should be the objective function F total right The derivative of Since the Lagrangian function L contains F total ,according to It can be deduced Virtual inertia The marginal price formula.

[0198] In this embodiment, the cost of the auxiliary service can be obtained by the above-mentioned marginal pricing method, and the formula of the auxiliary service cost is derived based on the Lagrangian function in step S400.

[0199] In this embodiment, the cost of providing virtual inertia auxiliary service by energy storage is:

[0200]

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

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

[0203]

[0204] in, The cost of providing fast frequency regulation for energy storage, T e is the energy storage time constant, Δf max The maximum frequency deviation allowed.

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

[0206]

[0207] in, The cost of providing voltage regulation service for energy storage, ΔQ s,t Provide reactive voltage regulation backup for energy storage.

[0208] This method has the following characteristics:

[0209] (1) This method adds inertia response, frequency regulation, and voltage regulation constraints to the traditional system scheduling model. Compared with the traditional system scheduling model, it can reflect the restrictions 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 energy storage devices participating in inertia response, frequency modulation, and voltage regulation, so that their flexibility can be utilized for system frequency and voltage regulation and scheduling.

[0211] (3) This method solves the power system dispatch model in which energy storage participates in ancillary services. The solution process first pre-solves the mixed integer programming and then solves 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 to provide multiple auxiliary services, including:

[0214] The auxiliary service modeling module is used to model the process of providing frequency regulation standby, inertia and voltage regulation auxiliary services for energy storage and units, specifically, to implement the process of step S100 in Example 1.

[0215] The power system modeling module is used to model the inertia response, frequency regulation and voltage regulation process of the power system, specifically, to implement the process of step S200 in embodiment 1.

[0216] The power system dispatch modeling module is used to model the power system dispatch problem including energy storage providing auxiliary services, specifically, to implement the process of step S300 in Example 1.

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

[0218] The auxiliary service cost evaluation module is used to calculate the service cost of each energy storage service based on the dual multiplier of the corresponding constraint of each auxiliary service to achieve value evaluation. Specifically, it implements the process of step S500 in Example 1.

[0219] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for evaluating the value of energy storage providing multiple auxiliary services, characterized in that: The steps include: Step S100, modeling the process of energy storage and units providing frequency regulation standby, inertia and voltage regulation auxiliary services; Step S200, modeling the inertia response, frequency regulation and voltage regulation process of the power system; Step S300, modeling a power system dispatch problem including energy storage providing auxiliary services; Step S400, obtaining dual multipliers of constraints corresponding to each auxiliary service by solving the power system dispatch problem of step S300; Step S500, based on the dual multipliers of the constraints corresponding to each auxiliary service, the service cost of each auxiliary service of the energy storage is calculated to achieve value evaluation.

2. A method for evaluating the value of energy storage providing multiple auxiliary services according to claim 1, characterized in that: In the step S100, The frequency regulation reserve service provided by energy storage and units is modeled as: Unit frequency regulation standby power constraints: The unit frequency regulation standby power is limited by the unit output: Constraints on the total frequency regulation and reserve composition of energy storage: The upper and lower limits of total frequency regulation reserve of energy storage: Total frequency regulation energy reserve constraints of energy storage: Energy storage total frequency regulation energy recovery constraint: in, It is the frequency regulation reserve capacity of a single thermal power unit. The running status of the unit, 1 means running, 0 means shutdown, It is the maximum frequency regulation capacity that a single thermal power unit can provide. For the output of a single thermal power unit, is the maximum output of a single thermal power unit, The total reserve capacity of energy storage for frequency regulation and inertia services, is the inertia power of energy storage, It is the primary frequency regulation backup for energy storage. and They are the charging power, discharging power and maximum discharging power of a single energy storage unit, is the energy storage level, t reg,dur is the duration of a frequency modulation, η d is the discharge efficiency, The energy required to provide inertia for energy storage, is the minimum energy level of energy storage, t soc,re Requires time for energy recovery; The inertia service provided by energy storage and units is modeled as: Unit inertia constraint: Energy storage inertia power constraint: Energy storage inertia energy constraint: Energy storage inertia coefficient constraint: in, is the inertia coefficient of the unit, is the inertia coefficient of energy storage, f0 is the nominal frequency of the system, RoCoF max is the maximum allowable frequency change rate, Δf max is the maximum allowable frequency deviation, is the maximum inertia coefficient of energy storage, ESSs is the energy storage set, is the set of running time periods; The voltage regulation service provided by energy storage is modeled as: Energy storage voltage regulation droop control constraint: ΔQ s =k Q Δx u ; Energy storage converter capacity constraints: Energy storage converter power factor constraint: Among them, ΔQ s Reactive voltage regulation backup provided for energy storage, k Q is the droop control coefficient of the energy storage reactive control loop, Δx U P is the system voltage regulation requirement, that is, the voltage deviation at the grid point exceeds the maximum limit. s,t is the power discharged from the energy storage s at time t, is the maximum capacity of the energy storage grid-connected converter, It is the minimum power factor allowed for the converter operation.

3. The value assessment method for providing multiple auxiliary services by energy storage according to claim 2 is characterized in that: In the step S200, The inertia response of the power system is modeled as: Total primary frequency regulation reserve constraints of the unit: Total primary frequency regulation reserve constraints of energy storage: Total inertia constraint of the unit: Energy storage total inertia constraint: in, is the total frequency regulation capacity of thermal power units, is the total frequency regulation capacity of the energy storage, is the total inertia level of the thermal power unit, is the total inertia level of energy storage; The power system frequency dispatch model is: Maximum frequency change rate constraint: Maximum quasi-steady-state frequency deviation constraint: Frequency minimum point constraint: in in, is the load deviation of the system, is the maximum allowable quasi-steady-state frequency deviation limit, f D is the damping coefficient, is the total load at time t; is the total inertia of the system, T e is the energy storage frequency modulation time constant, T g is the thermal power frequency modulation time constant; The power system voltage regulation model is: Voltage deviation constraint: System voltage regulation requirements constraints: Among them, ΔU PCC,i is the voltage deviation caused to the grid connection point by the disturbance of node i, is the voltage sensitivity coefficient of node i to the grid connection point, ΔQ i is the reactive disturbance occurring at node i, Ω N is the system node set, is the allowable grid-connection point bus voltage deviation specified by the system, Δx U In order to meet the system voltage regulation requirements, the reactive power disturbance conditions of all nodes are taken, and the node disturbance that has the greatest impact on the grid connection point voltage will be considered as the voltage regulation requirement.

4. The value assessment method for providing multiple auxiliary services by energy storage according to claim 3 is characterized in that: In step S300, the objective function of the power system dispatch problem including energy storage providing auxiliary services is: min.(VC+WSC) Among them, VC represents the total cost related to the unit, WSC represents the total cost related to new energy and energy storage, and Ω G ,Ω w and Ω S Respectively represent the collection of units, new energy and energy storage; They are the unit price of thermal power unit output, no-load cost, startup cost, unit price of primary frequency regulation service, unit price of inertia service, c w 、c s , They are the unit price of new energy output, the unit price of energy storage discharge / power purchase, the unit price of energy storage rapid frequency regulation, and the unit price of energy storage inertia; represents the starting action of unit u at time t, For the new energy output power, Purchase electrical power for energy storage.

5. The value assessment method for providing multiple auxiliary services by energy storage according to claim 3 is characterized in that: In step S300, the constraints of the power system dispatch problem including energy storage providing auxiliary services include: Energy storage equipment operation constraints, including: Energy storage charging power constraints: Energy storage discharge power constraints: State of charge timing constraints: State of charge upper and lower limit constraints: Constraints on consistency throughout the scheduling cycle: SOC s,0 =SOC s,end ; Among them, q s,t It represents the charge and discharge flag variable of energy storage s at time t, charging is 1, and discharging is 0. They represent the upper limits of the charging and discharging power of the selected energy storage element s, SOC s,t represents the charge state of the selected energy storage element s at time t, η c , η d Respectively represent the charging efficiency and discharging efficiency of the energy storage element s, SOC s,0 , SOC s,end They respectively represent the charge state of the energy storage element at the beginning and end of the dispatch cycle; Unit operating constraints, including: Unit active output constraints: Reactive power output constraints of the unit: Unit climbing constraints: Minimum online and offline time constraints for units: Logical constraints on unit switch action and online status: in, They represent the active and reactive power output of unit u at time t, RU u , RD u Respectively represent the maximum up and down climbing power of unit u, TU is a 0-1 variable indicating the unit shutdown action, 1 indicates action, u and TD u Respectively represent the minimum online and offline time of unit u.

6. A method for evaluating the value of energy storage providing multiple auxiliary services according to claim 5, characterized in that: The step S400 includes: Step S401, by pre-solving the power system dispatch problem including energy storage providing auxiliary services established in step S300, 0-1 variables representing the start-up, shutdown action and online status of unit u at time t are obtained. The solution of , and the 0-1 variable q representing the charge and discharge state of the energy storage s at time t s,t The solution; Step S402, bringing the solution of the 0-1 variable obtained in step S401 into the power system dispatch problem including energy storage providing auxiliary services established in step S300, and converting the non-convex joint optimization problem into a market clearing problem including only continuous variables; Step S403, for the market clearing problem, by constructing a Lagrangian function, solving the dual multipliers of frequency regulation reserve, inertia and voltage regulation auxiliary services.

7. A method for evaluating the value of energy storage providing multiple auxiliary services according to claim 6, characterized in that: The Lagrangian function is constructed as follows: Among them, ω ro is the dual multiplier of the maximum frequency change rate constraint of the system, ω ss is the dual multiplier of the maximum quasi-steady-state frequency deviation constraint of the system, μ, λ1, and λ2 are the dual multipliers corresponding to the constraints of the lowest frequency point of the system, satisfying μ ≥ 0, are the dual multipliers of the total inertia constraint and the total primary frequency regulation constraint of the unit, are the dual multipliers of the total inertia constraint of energy storage and the total primary frequency modulation constraint, ω dr is the dual multiplier of the energy storage voltage droop control constraint, ω ca is the dual multiplier of the energy storage converter capacity constraint, ω fa1 ,ω fa2 is the dual multiplier of the power factor constraint of the energy storage converter, … represents the constraint term of non-auxiliary services.

8. The value assessment method for providing multiple auxiliary services by energy storage according to claim 1 is characterized in that: The step S500 includes: Step S501, constructing a Lagrangian function of a market clearing model containing only continuous variables; Step S502, obtaining the partial derivative of the Lagrangian function constructed in step S501 with respect to the virtual inertia corresponding to each auxiliary service; Step S503: obtaining a formula expression of the cost of the virtual inertia corresponding to each auxiliary service.

9. A method for evaluating the value of energy storage providing multiple auxiliary services according to claim 8, characterized in that: In the step S503, The cost of energy storage providing virtual inertia auxiliary services is: in, The cost of providing virtual inertia for energy storage, f0 is the rated frequency, ω ro , are the dual multipliers of the system maximum frequency change rate constraint and the total inertia constraint of energy storage, respectively; μ, λ1, and λ2 are the dual multipliers corresponding to each item of the system minimum frequency constraint; The cost of energy storage providing fast frequency regulation ancillary services is: in, The cost of providing fast frequency regulation for energy storage, T e is the energy storage time constant, Δf max is the maximum allowable frequency deviation, ω ss is the dual multiplier of the maximum quasi-steady-state frequency deviation constraint of the system, is the dual multiplier of the total primary frequency modulation constraint; The cost of energy storage providing voltage regulation auxiliary services is: in, The cost of providing voltage regulation service for energy storage, ΔQ s,t Reactive voltage regulation backup provided for energy storage, ω dr is the dual multiplier of the energy storage voltage droop control constraint, ω ca is the dual multiplier of the energy storage converter capacity constraint, ω fa1 ,ω fa2 is the dual multiplier of the power factor constraint of the energy storage converter.

10. A value assessment system for energy storage providing multiple auxiliary services, characterized in that: include: Ancillary service modeling module, used to model the process of energy storage and units providing frequency reserve, inertia and voltage regulation auxiliary services; The power system modeling module is used to model the inertia response, frequency regulation and voltage regulation process of the power system; The power system dispatch modeling module is used to model the power system dispatch problem with energy storage providing ancillary services; The power system dispatching solution module is used to obtain the dual multipliers of the corresponding constraints of each auxiliary service by solving the power system dispatching problem; The auxiliary service cost calculation module is used to calculate the service cost of each energy storage service based on the dual multiplier of the corresponding constraints of each auxiliary service to achieve value evaluation.

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