User side energy storage capacity planning method and device considering frequency modulation and energy management

Abstract

The invention discloses a user side energy storage capacity planning method and device considering frequency modulation and energy management. The method comprises the following steps: constructing a profit model of providing frequency modulation and energy management services by user side energy storage; a user side energy storage two-stage stochastic programming model is constructed, in the stage I, annual average net income maximization of energy management service and frequency modulation auxiliary service is taken as a target, budget constraints and rated power and installed capacity upper and lower limit constraints are considered, and an energy storage optimal configuration scheme is obtained; in the stage II, energy storage operation cost and operation scene uncertainty are considered, and an energy storage optimal operation strategy is obtained by taking monthly expected net income maximization as a target; and solving the user-side energy storage two-stage stochastic programming model to obtain an optimal energy storage programming scheme. According to the energy storage planning scheme obtained by the invention, the synergistic interaction of frequency modulation auxiliary service and energy management service provided by user side energy storage is considered, so that the energy storage condition in actual operation is better simulated in a planning stage, and a more reasonable energy storage capacity and power configuration scheme is obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage control, and particularly to a method and device for planning the capacity of user-side energy storage considering frequency regulation and energy management. Background Art

[0002] Given the current high cost of energy storage systems, reasonably planning the capacity scale of energy storage is crucial for end-users with energy storage requirements. Configuring user-side energy storage can, on the one hand, improve the reliability of their own power consumption and power quality, but reducing the comprehensive electricity cost is the main driving force for users to configure energy storage. The main ways for user-side energy storage to reduce the comprehensive electricity cost are as follows: one is to provide user-side energy management services such as peak-valley price arbitrage and load shifting, and the other is to provide auxiliary services such as demand response, peak shaving, and frequency regulation for the power grid. Among them, the frequency regulation auxiliary service has higher requirements for the regulation performance of the unit, and its compensation price is also higher.

[0003] Existing research on the capacity planning of user-side energy storage usually assumes that the scale of user-side energy storage is small and can only provide a single type of user-side energy management service. However, the energy storage configured by some industrial users can reach the entry threshold for participating in the frequency regulation auxiliary service market. Therefore, it is necessary to consider the synergistic effect of user-side energy management services and frequency regulation auxiliary services in the capacity planning of user-side energy storage to obtain a more reasonable and economical capacity configuration plan. Summary of the Invention

[0004] The purpose of the present invention is to overcome the above-mentioned defects and problems in the prior art, and provide a method and device for planning the capacity of user-side energy storage considering frequency regulation and energy management, which can take into account the synergistic effect of energy storage providing both user-side energy management services and grid-side frequency regulation auxiliary services, so as to better simulate the energy storage situation in actual operation during the planning stage and obtain a more reasonable energy storage capacity and power configuration plan.

[0005] To achieve the above purpose, the technical solution of the present invention is: A method for planning the capacity of user-side energy storage considering frequency regulation and energy management, including:

[0006] Respectively construct the revenue models for user-side energy storage to provide frequency regulation auxiliary services and energy management services;

[0007] Construct a two-stage stochastic programming model for user-side energy storage. In stage I, with the goal of maximizing the annual average net revenue of energy management services and frequency regulation auxiliary services, considering budget constraints and upper and lower limits of rated power and installed capacity, obtain the optimal energy storage configuration plan; in stage II, considering the operation cost and operation scenario uncertainty of energy storage, with the goal of maximizing the monthly expected net revenue, obtain the optimal energy storage operation strategy;

[0008] The K - means clustering method and the forward scenario reduction method are respectively used to generate typical load scenarios and typical frequency regulation price signal scenarios, and the two - stage stochastic programming model of the user - side energy storage is solved to obtain the optimal planning scheme of the energy storage.

[0009] The revenue model for the user - side energy storage to provide energy management services is as follows:

[0010]

[0011] In the formula, R EM is the electricity cost savings brought to users by the energy storage participating in energy management services; B is the electricity cost of users without energy storage configuration; B BE is the electricity cost of users after configuring the energy storage and performing energy management services; σ PS is the peak - load electricity price; P PD is the initial monthly peak load; P PD，BE is the peak load after configuring the energy storage for energy management; Δt is the time interval of period t; D, H, and T are the total number of days, the total number of hours, and the total number of operation periods respectively; is the electricity price at the t - th period of the h - th hour on the d - th day; P t，h，d is the operating power of the energy storage system at the t - th period of the h - th hour on the d - th day.

[0012] The revenue model for the user - side energy storage to provide frequency regulation ancillary services is as follows:

[0013]

[0014] In the formula, is the frequency regulation revenue of the energy storage for the power grid at the h - th hour when providing frequency regulation ancillary services; is the frequency regulation capacity provided by the energy storage at the h - th hour; C bid，lb is the minimum access capacity of the frequency regulation market; P r is the rated power of the energy storage; is the clearing price of the frequency regulation market at the h - th hour; δ h is the frequency regulation performance index of the energy storage at the h - th hour.

[0015] The objective function of stage Ⅰ in the two - stage stochastic programming model of the user - side energy storage is:

[0016]

[0017] In the formula, ANI is the annual average net revenue; M is the total number of months in a year; R m (x) is the revenue of the energy storage providing services in the m - th month under the operation strategy x; C inv is the annual investment cost of the energy storage; E r and P r are the installed capacity and the rated power of the energy storage respectively; σ E and σP They are the prices per unit capacity and per unit power respectively; r is the annual interest rate; N is the planning period.

[0018] The constraint conditions in Stage I of the two-stage stochastic programming model for the user-side energy storage are as follows:

[0019] σ E E r +σ P P r ≤C B ;

[0020] P lb ≤P r ≤P ub ;

[0021] E lb ≤E r ≤E ub ;

[0022] In the formula, C B is the budget for the user to configure the energy storage; P lb and P ub are the lower and upper limits of the rated power of the energy storage respectively; E lb and E ub are the lower and upper limits of the installed capacity of the energy storage respectively.

[0023] The objective function in Stage II of the two-stage stochastic programming model for the user-side energy storage is:

[0024]

[0025] In the formula, L m is the set of operation scenarios in the m-th month; p(l m ) is the probability of the occurrence of scenario l m ; R m (x) is the revenue from the energy storage providing services in the m-th month under the operation strategy x; x is the operation strategy, is the operating power of the energy storage system at the t-th time period in the h-th hour under scenario l m ; and are the charging power and discharging power of the energy storage system at the t-th time period in the h-th hour under scenario l m respectively; P thr is the monthly peak load; is the power of the energy storage providing frequency modulation auxiliary services at the t-th time period in the h-th hour under scenario l m ; is the power of the energy storage providing energy management services at the t-th time period in the h-th hour under scenario l m ; is the power of the energy storage providing services at the t-th time period in the h-th hour under scenario l mThe binary variable for the energy storage to provide frequency regulation ancillary service or energy management service in the h-th hour, indicating that the energy storage provides frequency regulation ancillary service and the frequency regulation capacity is indicating that the energy storage provides energy management service; R EM (x, l m ) is the revenue of the energy storage providing energy management service under scenario l m and operation strategy x; R FR (x, l m ) is the revenue of the energy storage providing frequency regulation ancillary service under scenario l m and operation strategy x; C OM (x, l m ) is the operating cost of the energy storage under scenario l m and operation strategy x; σ DE is the unit operating cost of the energy storage system; D m is the number of days in the m-th month; η C and η D are the charging efficiency and discharging efficiency of the energy storage; Δt is the time interval of period t.

[0026] The constraint conditions in stage II of the two-stage stochastic programming model of the user-side energy storage include the constraint conditions for the energy storage to provide frequency regulation ancillary service and energy management service and the constraint conditions for the operation of the energy storage itself;

[0027] The constraint condition for the energy storage to provide frequency regulation ancillary service is:

[0028]

[0029] In the formula, C bid，lb is the minimum access capacity of the frequency regulation market; is the frequency regulation capacity provided by the energy storage in the h-th hour under scenario l m ; P r is the rated power of the energy storage;

[0030] The constraint condition for the energy storage to provide energy management service is:

[0031]

[0032] In the formula, is the electricity load in the t-th period of the h-th hour under scenario l m ; P thr is the monthly peak load;

[0033] The constraint condition for the operation of the energy storage itself is:

[0034]

[0035] In the formula, SOC iniis the initial state of charge of the energy storage; SOC ub and SOC lb are respectively the upper and lower limits of the energy storage charge ratio; h′ and t′ are respectively the number of hours and periods that the energy storage has been in operation; E r is the installed capacity of the energy storage.

[0036] A user-side energy storage capacity planning device considering frequency regulation and energy management, which is applied to the above-mentioned method. The device includes:

[0037] A revenue model construction module for respectively constructing revenue models for the user-side energy storage to provide frequency regulation ancillary services and energy management services;

[0038] A planning model construction module for constructing a two-stage stochastic programming model for the user-side energy storage. In stage I, with the goal of maximizing the annual average net revenue of energy management services and frequency regulation ancillary services, considering budget constraints and upper and lower limits of rated power and installed capacity constraints, an optimal energy storage configuration plan is obtained; in stage II, considering the operation cost and operation scenario uncertainty of the energy storage, with the goal of maximizing the monthly expected net revenue, an optimal energy storage operation strategy is obtained;

[0039] An optimal configuration plan acquisition module for respectively using the K-means clustering method and the forward scenario reduction method to generate typical load scenarios and typical frequency regulation price signal scenarios, and solving the two-stage stochastic programming model of the user-side energy storage to obtain the optimal planning plan of the energy storage.

[0040] A user-side energy storage capacity planning device considering frequency regulation and energy management, including a memory and a processor;

[0041] The memory is used to store computer program code and transmit the computer program code to the processor;

[0042] The processor is used to execute the above-mentioned method according to the instructions in the computer program code.

[0043] A computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned method is implemented.

[0044] Compared with the prior art, the beneficial effects of the present invention are:

[0045] In the method and device for user - side energy storage capacity planning considering frequency modulation and energy management of the present invention, the synergistic effect of the energy storage providing both user - side energy management services and grid - side frequency - modulation auxiliary services can be taken into account, so as to better simulate the energy storage situation in actual operation during the planning stage and obtain a more reasonable energy storage capacity and power configuration plan. Specifically, the revenue models of the energy storage providing both user - side energy management services and grid - side frequency - modulation auxiliary services are theoretically considered and included in the planning model, making the entire planning model more perfect, reasonable and close to the actual situation. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a flowchart of a method for user - side energy storage capacity planning considering frequency modulation and energy management of the present invention.

[0047] Figure 2 is a structural block diagram of a device for user - side energy storage capacity planning considering frequency modulation and energy management of the present invention.

[0048] Figure 3 is a structural block diagram of a device for user - side energy storage capacity planning considering frequency modulation and energy management of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] The present invention will be further described in detail below with reference to the drawings and specific embodiments.

[0050] See Figure 1 , a method for user - side energy storage capacity planning considering frequency modulation and energy management, includes:

[0051] S1. Respectively construct revenue models for the energy storage on the user side to provide frequency - modulation auxiliary services and energy management services to quantify the economic benefits of configuring energy storage on the user side.

[0052] S2. Construct a two - stage stochastic programming model for the energy storage on the user side. In stage I, with the goal of maximizing the annual average net revenue of energy management services and frequency - modulation auxiliary services, considering budget constraints and upper and lower limits of rated power and installed capacity, obtain the optimal energy storage configuration plan; in stage II, considering the operation cost of the energy storage and the uncertainty of operation scenarios, with the goal of maximizing the monthly expected net revenue, obtain the optimal operation strategy of the energy storage.

[0053] S3. Respectively use the K - means clustering method and the forward scenario reduction method to generate typical load scenarios and typical frequency - modulation price signal scenarios, and solve the two - stage stochastic programming model of the energy storage on the user side to obtain the optimal planning plan of the energy storage.

[0054] The main steps of generating typical load scenarios by the K - means clustering method include: obtaining monthly historical load data according to the annual historical load data information; selecting K objects from the monthly historical load data as the initial clustering centers; classifying the objects by calculating the distance from each clustering object to the clustering center; calculating the clustering centers again; calculating the standard measure function until the maximum number of iterations is reached and then stopping; determining the optimal clustering centers, which are the generated typical load scenarios. The K - means clustering method is efficient and easy to implement, and is suitable for reducing the monthly load data scenarios.

[0055] The main steps of generating typical frequency - modulation price signal scenarios by the forward scenario reduction method include: obtaining monthly historical frequency - modulation signal information according to the annual frequency - modulation signal data information; calculating the probability distance between each scenario and other scenarios; selecting the scenario with the largest probability distance as the reduced scenario according to the size of the probability distance; calculating the probability distance between the reduced scenario and other scenarios, and successively selecting the scenarios with the largest probability distance until several typical scenarios are obtained. Since the frequency - modulation signal has a sample point every 5 minutes and the scenario scale is large, the forward scenario reduction method is used to achieve the rapid reduction of large - scale scenarios.

[0056] The present invention can take into account the synergistic effect of energy storage providing user - side energy management services and grid - side frequency - modulation auxiliary services simultaneously, so as to better simulate the energy storage situation in actual operation during the planning stage and obtain a more reasonable energy storage capacity and power configuration plan, in order to solve the problem that the existing user - side energy storage capacity planning method ignores the synergistic effect of user - side energy management services and frequency - modulation auxiliary services. Theoretically, the income model of energy storage providing user - side energy management services and grid - side frequency - modulation auxiliary services simultaneously is specifically considered and included in the planning model, making the entire planning model more perfect, reasonable and close to the actual situation.

[0057] Furthermore, the income model of user - side energy storage providing energy management services is:

[0058] The electricity bill of a user in a certain month without energy storage configuration is:

[0059]

[0060] The electricity bill of a user in a certain month after configuring energy storage and performing energy management services is:

[0061]

[0062] The electricity bill savings brought by energy storage participating in energy management services for users is:

[0063]

[0064] In the formula, R EMThe electricity cost savings brought to users by energy storage participating in energy management services; B is the electricity cost of users without configured energy storage; B BE is the electricity cost of users after configuring energy storage and performing energy management services; σ PS is the peak load electricity price; P PD is the initial monthly peak load; P PD，BE is the peak load after configuring energy storage for energy management; Δt is the time interval of period t; D, H, and T are the total number of days, total number of hours, and total number of operating periods respectively; is the electricity price of the t-th period of the h-th hour of the d-th day; is the electricity load of the t-th period of the h-th hour of the d-th day; P t，h，d is the operating power of the energy storage system in the t-th period of the h-th hour of the d-th day.

[0065] Furthermore, after configuring energy storage and providing frequency regulation ancillary services for the power grid, the revenue model of the user-side energy storage providing frequency regulation ancillary services is:

[0066]

[0067] In the formula, is the frequency regulation revenue of the h-th hour when the energy storage provides frequency regulation ancillary services for the power grid; is the frequency regulation capacity provided by the energy storage in the h-th hour; C bid，lb is the minimum access capacity of the frequency regulation market; P r is the rated power of the energy storage; is the clearing price of the frequency regulation market in the h-th hour; δ h is the frequency regulation performance index of the energy storage in the h-th hour.

[0068] Furthermore, the objective function of stage I in the two-stage stochastic programming model of the user-side energy storage is:

[0069]

[0070] In the formula, ANI is the annual average net revenue; M is the total number of months in a year; R m (x) is the revenue of the energy storage providing services in the m-th month under the operation strategy x; C inv is the annual investment cost of the energy storage; E r and P r are the installed capacity and rated power of the energy storage respectively; σ E and σ P are the prices per unit capacity and per unit power respectively; r is the annual interest rate; N is the planning period.

[0071] Furthermore, the constraint conditions of stage I in the two-stage stochastic programming model of the user-side energy storage are:

[0072] σ E Er +σ P P r ≤C B ;

[0073] P lb ≤P r ≤P ub ;

[0074] E lb ≤E r ≤E ub ;

[0075] Wherein, C B is the budget for the user to configure energy storage; P lb and P ub are respectively the lower and upper limits of the rated power of the energy storage; E lb and E ub are respectively the lower and upper limits of the installed capacity of the energy storage.

[0076] Furthermore, the objective function of stage II in the two-stage stochastic programming model of the user-side energy storage is:

[0077]

[0078] Wherein, L m is the set of operation scenarios in the m-th month; p(l m ) is the probability of the occurrence of scenario l m ; R m (x) is the revenue of the energy storage providing services in the m-th month under the operation strategy x; x is the operation strategy, is the operating power of the energy storage system at the t-th time period of the h-th hour under scenario l m ; and are respectively the charging power and discharging power of the energy storage system at the t-th time period of the h-th hour under scenario l m ; P thr is the monthly peak load; is the power of the energy storage providing frequency regulation ancillary services at the t-th time period of the h-th hour under scenario l m ; is the power of the energy storage providing energy management services at the t-th time period of the h-th hour under scenario l m ; is a binary variable of the energy storage providing frequency regulation ancillary services or energy management services at the h-th hour under scenario l m , indicating that the energy storage provides frequency regulation ancillary services and the frequency regulation capacity is indicating that the energy storage provides energy management services; R EM (x, l m ) is for scenario l mThe revenue of the energy storage providing energy management services under operation strategy x; R FR (x, l m ) is the revenue of the energy storage providing frequency regulation ancillary services under scenario l m and operation strategy x; C OM (x, l m ) is the operating cost of the energy storage under scenario l m and operation strategy x; σ DE is the unit operating cost of the energy storage system; D m is the number of days in the m-th month; η C and η D are the charging efficiency and discharging efficiency of the energy storage; Δt is the time interval of period t.

[0079] Furthermore, the constraint conditions in stage II of the two-stage stochastic programming model of the user-side energy storage include the constraint conditions for the energy storage to provide frequency regulation ancillary services and energy management services, as well as the constraint conditions for the operation of the energy storage itself;

[0080] When , the constraint condition for the energy storage to provide frequency regulation ancillary services is:

[0081]

[0082] In the formula, C bid，lb is the minimum access capacity of the frequency regulation market; is the frequency regulation capacity provided by the energy storage in the h-th hour under scenario l m ; P r is the rated power of the energy storage;

[0083] When , the constraint condition for the energy storage to provide energy management services is:

[0084]

[0085] In the formula, is the electricity load in the t-th period of the h-th hour under scenario l m ; P thr is the monthly peak load;

[0086] The constraint condition for the operation of the energy storage itself is:

[0087]

[0088] In the formula, SOC ini is the initial state of charge of the energy storage; SOC ub and SOC lb are the upper and lower limits of the state-of-charge ratio of the energy storage respectively; h' and t' are the number of hours and periods that the energy storage has been operating respectively; E r is the installed capacity of the energy storage.

[0089] See Figure 2 , a user - side energy storage capacity planning device considering frequency regulation and energy management. This device is applied to the above - mentioned user - side energy storage capacity planning method considering frequency regulation and energy management. The device includes:

[0090] A revenue model construction module, used to construct revenue models for the user - side energy storage to provide frequency regulation ancillary services and energy management services respectively;

[0091] A planning model construction module, used to construct a two - stage stochastic programming model for the user - side energy storage. In stage I, with the goal of maximizing the annual average net revenue of energy management services and frequency regulation ancillary services, considering budget constraints and upper and lower limits of rated power and installed capacity, the optimal energy storage configuration plan is obtained; in stage II, considering the operating cost of the energy storage and the uncertainty of operating scenarios, with the goal of maximizing the monthly expected net revenue, the optimal energy storage operation strategy is obtained;

[0092] An optimal configuration plan acquisition module, used to generate typical load scenarios and typical frequency regulation price signal scenarios respectively by using the K - means clustering method and the forward scenario reduction method, and solve the two - stage stochastic programming model of the user - side energy storage to obtain the optimal energy storage planning plan.

[0093] See Figure 3 , a user - side energy storage capacity planning device considering frequency regulation and energy management, including a memory and a processor;

[0094] The memory is used to store computer program code and transmit the computer program code to the processor;

[0095] The processor is used to execute the above - mentioned user - side energy storage capacity planning method according to the instructions in the computer program code.

[0096] A computer - readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the above - mentioned user - side energy storage capacity planning method considering frequency regulation and energy management.

[0097] Generally speaking, the computer instructions for implementing the method of the present invention can be carried by any combination of one or more computer - readable storage media. A non - transient computer - readable storage medium can include any computer - readable medium except the signal itself in transient propagation.

[0098] A computer-readable storage medium may, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (a non-exhaustive list) of the computer-readable storage medium include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0099] Computer program code for performing the operations of the present invention may be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. In particular, the Python language suitable for neural network computing and platform frameworks based on TensorFlow, PyTorch, etc. can be used. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or connected to an external computer (e.g., connected through the Internet using an Internet service provider).

[0100] For the above-mentioned devices and non-transitory computer-readable storage media, reference may be made to the specific description of a user-side energy storage capacity planning method and beneficial effects considering frequency modulation and energy management, which will not be elaborated here.

[0101] Although the embodiments of the present invention have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for planning user-side energy storage capacity taking into account frequency regulation and energy management, characterized in that: include: Construct revenue models for user-side energy storage to provide frequency regulation auxiliary services and energy management services respectively; A two-stage stochastic programming model for user-side energy storage is constructed. In stage I, the goal is to maximize the average annual net benefits of energy management services and frequency regulation auxiliary services, and the optimal energy storage configuration scheme is obtained by considering budget constraints and upper and lower limits of rated power and installed capacity. In stage II, the energy storage operation cost and operation scenario uncertainty are considered, and the optimal energy storage operation strategy is obtained by maximizing the expected monthly net benefits. The K-means clustering method and forward scenario reduction method are used to generate typical load scenarios and typical frequency regulation price signal scenarios, respectively, and the two-stage stochastic programming model of user-side energy storage is solved to obtain the optimal planning scheme for energy storage.

2. A user-side energy storage capacity planning method taking into account frequency modulation and energy management according to claim 1, characterized in that: The revenue model of energy management services provided by user-side energy storage is: In the formula, R EM B is the electricity cost savings brought to users by energy storage participating in energy management services; B is the electricity cost of users when no energy storage is configured; B BE The user's electricity fee after configuring energy storage and providing energy management services; PS is the peak load electricity price; P PD is the monthly initial peak load; P PD，BE is the peak load after energy storage is configured for energy management; Δt is the time interval of period t; D, H and T are the total number of days, total hours and total number of operating time periods respectively; is the electricity price at the hth hour of the tth period on the dth day; P t，h，d is the operating power of the energy storage system in the tth period of the hth hour on the dth day.

3. A user-side energy storage capacity planning method taking into account frequency modulation and energy management according to claim 1, characterized in that: The revenue model of the frequency regulation auxiliary service provided by the user-side energy storage is: In the formula, The frequency regulation revenue at hour h when energy storage provides frequency regulation auxiliary services to the power grid; The frequency regulation capacity provided by energy storage for the hth hour; C bid，lb is the minimum access capacity of the frequency modulation market; P r is the rated power of the energy storage; is the FM market clearing price at hour h; h It is the frequency regulation performance index of energy storage in the hth hour.

4. A user-side energy storage capacity planning method taking into account frequency modulation and energy management according to claim 1, characterized in that: The objective function of stage I in the two-stage stochastic programming model of user-side energy storage is: In the formula, ANI is the average annual net income; M is the total number of months in a year; R m (x) The revenue from providing energy storage services in the mth month under operation strategy x; C inv is the annual investment cost of energy storage; E r and P r are the installed capacity and rated power of energy storage respectively; σ E and σ P are the prices per unit capacity and per unit power respectively; r is the annual interest rate; N is the planning period.

5. A user-side energy storage capacity planning method taking into account frequency regulation and energy management according to claim 4, characterized in that: The constraints of stage I in the two-stage stochastic programming model for user-side energy storage are: s E E r +s P P r ≤C B ; P lb ≤P r ≤P ub ; AND lb ≤E r ≤E ub ; In the formula, C B Configure energy storage budget for users; lb and P ub are the lower and upper limits of the energy storage rated power respectively; E lb and E ub They are the lower and upper limits of energy storage installed capacity respectively.

6. A user-side energy storage capacity planning method taking into account frequency regulation and energy management according to claim 1, characterized in that: The objective function of stage II in the two-stage stochastic programming model for user-side energy storage is: Where, L m is the set of running scenarios in the mth month; p(l m ) is scene l m Probability of occurrence; R m (x) is the revenue of energy storage services provided in the mth month under operation strategy x; x is the operation strategy, For scene l m The operating power of the energy storage system in the tth period of the next hth hour; and The scene l m The charging power and discharging power of the energy storage system in the tth period of the next hth hour; P thr is the monthly peak load; For scene l m The power of frequency regulation auxiliary service provided by energy storage in the next h-th hour and t-th period; For scene l m The power of energy management services provided by the energy storage in the next h-th hour and t-th period; For scene l m The binary variable that the energy storage provides frequency regulation auxiliary service or energy management service in the next hour h, Indicates that energy storage provides auxiliary frequency regulation services and the frequency regulation capacity is Indicates that energy storage provides energy management services; R EM (x,l m ) is scene l m The revenue of energy storage providing energy management services under operation strategy x; R FR (x,l m ) is scene l m The revenue of energy storage providing frequency regulation auxiliary services under operation strategy x; C OM (x,l m ) is scene l m and the operating cost of energy storage under operation strategy x; σ DE is the unit operating cost of the energy storage system; D m is the number of days in the mth month; η C and η D is the charging efficiency and discharging efficiency of energy storage; Δt is the time interval of time period t.

7. A user-side energy storage capacity planning method taking frequency regulation and energy management into account according to claim 6, characterized in that: The constraints of stage II in the two-stage stochastic programming model of user-side energy storage include the constraints of the energy storage providing frequency regulation auxiliary services and energy management services and the constraints of the energy storage's own operation; The constraints for energy storage to provide frequency regulation auxiliary services are: In the formula, C bid，lb It is the minimum entry capacity for the frequency modulation market; For scene l m The frequency regulation capacity provided by the energy storage in the next h hour; Pγ is the rated power of the energy storage; The constraints for the energy storage to provide energy management services are: In the formula, For scene l m The power load in the tth period of the next hth hour; P thr is the monthly peak load; The constraints for the energy storage operation itself are: In the formula, SOC ini SOC is the initial state of charge of energy storage; ub and SOC lb are the upper and lower limits of the energy storage charge ratio respectively; h′ and t′ are the number of hours and time periods that the energy storage has been running respectively; E r The installed capacity of energy storage.

8. A user-side energy storage capacity planning device taking into account frequency regulation and energy management, characterized in that: The device is applied to the method described in any one of claims 1 to 7, and the device comprises: A revenue model building module, used to build revenue models for frequency regulation auxiliary services and energy management services provided by user-side energy storage; The planning model building module is used to build a two-stage stochastic planning model for user-side energy storage. Phase I aims to maximize the average annual net benefits of energy management services and frequency regulation auxiliary services, taking into account budget constraints and upper and lower limits of rated power and installed capacity to obtain the optimal energy storage configuration plan; Phase II considers energy storage operation costs and operation scenario uncertainties, takes monthly expected net benefits as the goal, and obtains the optimal energy storage operation strategy; The optimal configuration scheme acquisition module is used to generate typical load scenarios and typical frequency regulation price signal scenarios using the K-means clustering method and the forward scenario reduction method respectively, and solve the two-stage random programming model of user-side energy storage to obtain the optimal planning scheme for energy storage.

9. A user-side energy storage capacity planning device taking into account frequency regulation and energy management, characterized in that: including memory and processor; The memory is used to store computer program code and transmit the computer program code to the processor; The processor is configured to execute the method according to any one of claims 1 to 7 according to instructions in the computer program code.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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