A wind and solar energy storage station energy storage configuration method, equipment, medium and product

Abstract

The present invention discloses a method, device, medium and product for configuring energy storage of a wind-solar storage station, and relates to the technical field of wind-solar storage stations. The method comprises: clustering the operation data of the historical wind-solar output of the wind-solar storage station to obtain multiple scenarios; establishing a wind-solar storage station energy storage configuration model including multiple trading modes according to the multiple scenarios; establishing information constraints and configuration constraints for the wind-solar storage station energy storage configuration model; constructing an information interaction model for each trading mode according to the wind-solar storage station energy storage configuration model, information constraints and configuration constraints; constructing a wind power generation, photovoltaic power generation and energy storage coordinated operation mode model for each trading mode according to the wind-solar storage station energy storage configuration model; solving the wind-solar storage station energy storage configuration model, each information interaction model, and each wind power generation, photovoltaic power generation and energy storage coordinated operation mode model with the goal of maximizing benefits, and obtaining the energy storage configuration result of the wind-solar storage station. The present invention improves the reliability of energy storage configuration.

Description

Technical Field

[0001] The present invention relates to the technical field of wind-solar energy storage stations, and in particular to a method, equipment, medium and product for configuring energy storage in a wind-solar energy storage station. Background Art

[0002] At present, new energy has become an important part of energy. Wind, solar and storage stations are key means of new energy. How to consider their production simulation process and configure energy storage for stations in combination with spot market has become the key to development. At present, energy storage configuration is mostly used in peak shaving and valley filling, smoothing fluctuations, improving power supply reliability, delaying upgrades and renovations, etc., but only considering the charging and discharging process of individual energy storage, the form is single. In order to ensure the energy efficiency of the system, it is also necessary to consider the production simulation process of wind, solar and storage synergy interaction within the station and other forms. The production simulation process in the power system is mainly carried out through the simulation system scheduling operation, and the optimal source-side unit power generation, production cost and other production indicators are determined under the premise of meeting the load demand. However, with the continuous increase in capacity, wind, solar and storage stations cannot only be followers of the spot mode in the production simulation process, but also need to consider the interactive strategy of the station participating in the power spot mode. Therefore, conventional time-series production simulation is no longer applicable, and the production simulation of wind, solar and storage stations under the spot mode has become the key to research. In the production simulation process of new energy stations under the spot mode, it is necessary to seek power balance between new energy output and user demand, and to interact information in the power spot mode. However, the energy storage capacity of most stations currently only covers about 2 hours of full-power charging and discharging, which makes it difficult to ensure the reliability of the energy efficiency of wind and solar energy storage stations under the electricity spot model. Summary of the invention

[0003] The purpose of the present invention is to provide a method, device, medium and product for configuring energy storage in a wind-solar storage station, thereby improving the reliability of energy storage configuration.

[0004] To achieve the above-mentioned purpose, the present invention provides the following solution: a method for configuring energy storage in a wind-solar energy storage station, comprising the following steps.

[0005] The operation data of wind and solar power output in the target historical time period of the wind and solar energy storage station are clustered to obtain multiple scenarios.

[0006] A wind-solar-storage station energy storage configuration model including at least two trading modes is established based on multiple scenarios.

[0007] Information constraints and configuration constraints are established for the wind-solar-storage station energy storage configuration model.

[0008] According to the wind-solar energy storage station energy storage configuration model, the information constraints and the configuration constraints, an information interaction model is constructed for each transaction mode.

[0009] According to the energy storage configuration model of the wind-solar-storage station, a coordinated operation model of wind power generation, photovoltaic power generation and energy storage is constructed for each trading mode.

[0010] With the goal of maximizing benefits, the energy storage configuration model of the wind-solar-storage station, the information interaction models, and the wind power generation, photovoltaic power generation and energy storage coordinated operation models are solved to obtain the energy storage configuration result of the wind-solar-storage station; the energy storage configuration power size and the energy storage configuration capacity size.

[0011] A computer device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the wind-solar-storage station energy storage configuration method.

[0012] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the wind-solar-storage station energy storage configuration method.

[0013] A computer program product includes a computer program, which, when executed by a processor, implements the steps of the wind-solar-storage station energy storage configuration method.

[0014] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects: the present invention aims at maximizing benefits, solves the energy storage configuration model of the wind-solar-storage station, the information interaction models, and the wind power generation, photovoltaic power generation and energy storage coordinated operation mode models, obtains the energy storage configuration result of the wind-solar-storage station, utilizes the differences of different trading modes to enrich the wind-solar-storage station, and improves the reliability of the energy storage configuration. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 A schematic flow chart of a method for configuring energy storage in a wind-solar energy storage station provided in Example 1 of the present invention.

[0017] Figure 2 Schematic diagram of a double-layer model of the multi-mode wind-solar-storage station energy storage configuration provided in Example 1 of the present invention.

[0018] Figure 3 A schematic diagram of the principle of a wind-solar energy storage station energy storage configuration method provided in Example 1 of the present invention.

[0019] Figure 4This is a diagram of the internal structure of a computer device. DETAILED DESCRIPTION

[0020] 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 only 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 are within the scope of protection of the present invention.

[0021] The purpose of the present invention is to provide a method, device, medium and product for configuring energy storage in a wind-solar storage station, thereby improving the reliability of energy storage configuration.

[0022] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0023] Example 1: Figure 1 As shown, a method for configuring energy storage in a wind-solar energy storage station in this embodiment includes the following steps.

[0024] Step 101: Cluster the operation data of wind and solar power output of the wind and solar energy storage station within the target historical time period to obtain multiple scenarios.

[0025] Step 102: Establish a wind-solar-storage station energy storage configuration model including at least two transaction modes according to multiple scenarios.

[0026] Step 103: Establish information constraints and configuration constraints for the wind-solar-storage station energy storage configuration model.

[0027] Step 104: construct an information interaction model for each transaction mode according to the wind-solar-storage station energy storage configuration model, the information constraints and the configuration constraints.

[0028] Step 105: Based on the wind-solar-storage station energy storage configuration model, a wind power generation, photovoltaic power generation and energy storage coordinated operation model is constructed for each transaction mode.

[0029] Step 106: With the goal of maximizing benefits, solve the energy storage configuration model of the wind-solar-storage station, the information interaction models, and the wind power generation, photovoltaic power generation and energy storage coordinated operation mode models to obtain the energy storage configuration result of the wind-solar-storage station.

[0030] The operating data of wind and solar power output includes the corresponding power generation capacity per hour.

[0031] Among them, the energy storage configuration result of the wind-solar-storage station obtained in step 106 includes result parameters and optimization parameters, the structural parameters include the energy storage configuration power size and the energy storage configuration capacity size, and the optimization parameters include the annual net income of energy storage, the annual investment cost of energy storage, energy storage charging and discharging actions, etc.

[0032] like Figure 2 and Figure 3 As shown, in this embodiment, the historical data of actual operation of a city's load and wind and solar output throughout the year are obtained, and the typical scene of wind and solar output is obtained according to the hierarchical K-means clustering algorithm. Based on different scenes, a two-layer model of wind, solar and storage station energy storage configuration in the day-ahead-real-time multi-mode is established: the upper layer is the energy storage configuration problem in different modes, and the lower layer is the station production simulation problem in different modes. Then, the interaction constraints, configuration constraints, SoC constraints, charging and discharging constraints and other constraints in different modes are considered, and the net surplus of the demand side and the net surplus of the power generation are described by social security. The information interaction model in the day-ahead-real-time mode is constructed with the maximization of social security as the objective function. The hierarchical-partitioning clustering method is used for multi-scenario allocation to realize the production simulation process of wind, solar and storage power stations considering the synergistic interaction between wind, light and storage in different modes. Finally, the corresponding configuration parameters of energy storage are input, and the multi-time scale energy storage configuration-operation model considering the long-time scale production simulation and the short-time scale mode interaction is combined with multi-party constraints to perform planning and solving, and the configuration results of energy storage power and capacity are obtained.

[0033] Before step 101, the method further includes: collecting historical data of actual operation of a city's load and wind and solar power output throughout the year.

[0034] Among them, step 101 specifically includes: using a hierarchical K-means clustering algorithm to cluster the operating data of wind and solar power output within a target historical time period of the wind and solar energy storage station to obtain multiple scenarios.

[0035] The transaction mode includes a day-ahead mode and a real-time mode, and the target historical time period is one year. Therefore, as a specific implementation, step 101 specifically includes: based on the historical data of actual operation throughout the year, a hierarchical K-means clustering algorithm is used to cluster the historical data throughout the year to obtain multiple typical scenarios.

[0036] In this embodiment, the scenarios refer to several representative data patterns obtained by clustering the output data of wind and solar power (wind power and photovoltaic power generation) throughout the year. These patterns represent the typical output of wind and solar power generation at different times and under different conditions.

[0037] For example, clustering based on solar radiation intensity and wind speed yields the following four scenarios.

[0038] Scenario 1 is high light and low wind speed. In this scenario, the weather is clear, the solar radiation intensity is high, but the wind speed is relatively low. Under such weather conditions, the output power of photovoltaic power generation may be very high, while the output power of wind power generation is relatively low.

[0039] Scenario 2: Low light and high wind speed: In this scenario, it is cloudy and windy, with insufficient solar radiation but high wind speed. Under such weather conditions, the output power of photovoltaic power generation may decrease, while the output power of wind power generation will increase relatively.

[0040] Scenario 3: Low light and low wind speed: In this scenario, both the solar radiation and wind speed are low. Under such weather conditions, the output power of wind power and photovoltaic power generation is very low.

[0041] Scenario 4: High light and high wind speed: In this scenario, both the solar radiation and wind speed are very high. Under such weather conditions, the output power of wind power and photovoltaic power generation is very high.

[0042] Step 102 specifically includes: establishing a wind-solar-storage station energy storage configuration model in a day-ahead-real-time multi-mode based on different scenarios.

[0043] This embodiment configures the energy storage power and capacity based on the objective function (Formula (1)) of maximizing the energy efficiency of the wind-solar-storage station in multiple scenarios.

[0044] The energy storage configuration model of the wind-solar energy storage station is expressed as formula (1) to formula (4).

[0045] (1).

[0046] (2).

[0047] (3).

[0048] (4).

[0049] Among them, in formula (1) is the annual average energy efficiency of the wind and solar power storage station in the day-ahead mode, is the average annual energy efficiency of the wind and solar storage station in real-time mode, is the average annual investment and construction cost of energy storage in wind and solar energy storage stations; S is a collection of scenes, For the scene s The number of days that appear in the simulation run throughout the year, T is the number of moments in a scene, t For the moment, k It is the interactive section for the discharge of wind and solar storage stations. b Interactive segment for charging wind and solar storage stations, The scene of the wind and solar storage station in the day-ahead mode s Next interactive section k The discharge power at time t, The scene of the wind and solar farm station in the day-ahead mode s Next interactive section b The charging power at time t, represents the marginal electricity price of the day-ahead mode at time t under scenario s, is the difference between two adjacent moments; Scenery and solar farm station in real-time mode s Next interactive section k The discharge power at time t, Scenery and solar farm station in real-time mode s Next interactive section b The charging power at time t, Representation scene s Real-time mode marginal electricity price under ; is the annual interest rate, L is the year of energy storage operation, and represents the rated power of energy storage. Indicates the rated capacity of energy storage, is the unit power investment cost of energy storage, Represents the unit capacity investment cost of energy storage.

[0050] The simulation operation (production simulation operation) mentioned above refers to the concept of production simulation, which divides the 365 days of the year into several scenarios (for example: divided into 3 scenarios, the 3 scenarios correspond to T1=110 days, T2=120 days, T3=135 days). The data of 365 days of the year here are all historical data for production simulation operation of wind, solar and storage stations.

[0051] Among them, step 103 specifically includes: formulating an interactive strategy (information constraint) based on the energy efficiency model of the wind, solar and storage station in different day-ahead and real-time modes (wind, solar and storage station energy storage configuration model) in step 102.

[0052] The information constraint representation includes formula (5) to formula (8).

[0053] (5).

[0054] (6).

[0055] (7).

[0056] (8).

[0057] Among them, formula (5) represents the upper and lower limit constraints of the information disclosure of wind, solar and storage stations on the power generation side in the upper model, where Indicates that the wind and solar storage field is standing in the scene s Next interactive section k The upper and lower limits of information disclosure are and Formula (6) indicates that the disclosure of segmented information on the power generation side is increasing. Indicates that the wind and solar storage field is standing in the scene s Next interactive section k- 1. Formula (7) represents the upper and lower limit constraints of information disclosure of wind, solar and storage stations on the power consumption side in the upper model, where Indicates that the wind and solar storage field is standing in the scene s Next interactive section b The upper and lower limits of information disclosure are and Formula (8) indicates that the disclosure of segmented information on the power generation side is decreasing. Indicates that the wind and solar storage field is standing in the scene s Next interactive section b -1 Information disclosure.

[0058] Information disclosure specifically refers to the quotation of quantity in the process of participating in the spot market clearing. This embodiment restricts the information interaction strategy of the wind, solar and storage station itself and formulates the information interaction strategy of the wind, solar and storage station itself.

[0059] The configuration constraints include wind and solar energy storage station energy storage configuration constraints, SoC constraints, state of charge constraints, and energy storage charging and discharging constraints.

[0060] Take the day-ahead model as an example: (9).

[0061] (10).

[0062] (11).

[0063] (12).

[0064] (13).

[0065] (14).

[0066] (15).

[0067] (16).

[0068] Among them, formula (9)-formula (10) are the power and capacity constraints of energy storage configuration, To configure the rated power of energy storage, To configure the rated capacity of energy storage, To set an upper limit for power, is the upper limit of the capacity. Formula (11)-Formula (14) are the energy storage SoC constraints, is the energy storage loss coefficient, is the energy storage charge / discharge efficiency; This is the scene in the day-ahead mode s The state of charge of the energy storage at time t is: They are the scenarios in the day-ahead mode. s The energy storage charging and discharging power is This is the scene in the day-ahead mode s The state of charge of the lower energy storage at time t is, and are the upper and lower limits of the state of charge, respectively. and Respectively for scenes s The initial and final charge states of the energy storage. Formula (15)-Formula (16) are expressed by binary variables Constrained scene s The lower storage energy cannot be charged and discharged at the same time.

[0069] The constraints related to the real-time mode are the same as those of the day-ahead mode.

[0070] Among them, in step 106, the goal of maximizing benefits is specifically the goal of maximizing social security, and the information interaction model of the day-ahead model is specifically the objective function of maximizing social security.

[0071] Information interaction model of the day-ahead mode ( Figure 2 The middle and lower level model 1) is expressed as formula (17) to formula (26).

[0072] (17).

[0073] (18).

[0074] (19).

[0075] (20).

[0076] (twenty one).

[0077] (twenty two).

[0078] (twenty three).

[0079] (twenty four).

[0080] (25).

[0081] (26).

[0082] Among them, formula (17) is the objective function of the day-ahead information interaction model with the goal of maximizing social security, Representation scene s Next User j In the interactive section b Disclosure of electricity usage information, This is the scene in the day-ahead mode s Next User j In the interactive section b The interactive segment power; Representation scene s Lower unit i In the interactive section k Disclosure of power generation information, This is the scene in the day-ahead mode s Lower unit i In the interactive section k The interactive segment power.

[0083] Formula (18) indicates that the system s The power balance constraint at the next time t. Formula (19)-represents the scenario s The upper and lower power limits of each charging interaction segment of the downstream wind-solar-storage station are as follows: Formula (20) represents the scenario s The upper and lower power limits of each discharge interaction section of the downstream wind-solar-storage station are: They are the upper and lower limits of the power of a single charging section of a wind-solar-storage station, are the upper and lower limits of the power of a single discharge section of the wind-solar-storage station. Formula (21) represents the scenario s The upper and lower limits of the total power of the charging interaction section of the downstream wind-solar-storage station are constrained. Formula (22) represents the scenario s The upper and lower limits of the total power of the downstream wind-solar-storage station discharge interaction section are: They are the upper and lower limits of the total power of the charging section of the wind-solar-storage station, are the upper and lower limits of the total power of the wind-solar-storage station discharge section. Formula (23) is the scenario s Next User j The interactive power upper and lower limits of each load segment are: are the upper and lower limits of the interactive power of each load segment. Formula (24) is the scenario s Conventional unit The interactive power of each output segment is: are the upper and lower limits of the interactive power of each load segment. Formula (25) represents the upper and lower limits of the user's total load, where are the upper and lower limits of the total load respectively. Formula (26) represents the conventional unit i The total output upper and lower limits are constrained, where They are the upper and lower limits of total output respectively.

[0084] The information interaction model in real-time mode is specifically an objective function with the goal of maximizing social security.

[0085] Information interaction model in real-time mode ( Figure 2 The middle and lower level model 2) is expressed as the following formula.

[0086] (27).

[0087] (28).

[0088] (29).

[0089] (30).

[0090] (31).

[0091] (32).

[0092] (33).

[0093] (34).

[0094] (35).

[0095] (36).

[0096] Among them, formula (27) is the objective function of the real-time information interaction model with the goal of maximizing social security, Representation scene s Next User j In the interactive section b The interactive segment power, Representation scene s Conventional unit i In the interactive section k The interactive segment power. Formula (28) represents the real-time mode system in the scene s Next time t The power balance constraint of . Formula (29) represents the scenario in real-time mode s The power upper and lower limits of each charging interaction segment of the wind-solar-storage station are constrained. Formula (30) represents the scenario in real-time mode. sThe upper and lower power limits of each discharge interaction section of the downstream wind-solar-storage station are: They are the upper and lower limits of the power of a single charging section of a wind-solar-storage station, are the upper and lower limits of the power of a single discharge section of the wind-solar-storage station respectively. Formula (31) represents the scenario in real-time mode s The upper and lower limits of the total power of the wind-solar-storage station charging interaction section are as follows: Formula (32) represents the scenarios in real-time mode: s The upper and lower limits of the total power of the wind-solar-storage station discharge interaction section are: They are the upper and lower limits of the total power of the charging section of the wind-solar-storage station, are the upper and lower limits of the total power of the wind-solar-storage station discharge section. Formula (33) is the scenario s Next User j The interactive power upper and lower limits of each load segment are constrained, where are the upper and lower limits of the interactive power of each load segment. Formula (34) is the scenario s Conventional unit i The interactive power of each output segment is: are the upper and lower limits of the interactive power of each load segment. Formula (35) represents the upper and lower limits of the user's total load, where are the upper and lower limits of the total load respectively. Formula (36) represents the conventional unit i The total output upper and lower limits are constrained, where They are the upper and lower limits of total output respectively.

[0097] The model for the coordinated operation of wind power generation, photovoltaic power generation and energy storage in the day-ahead mode is expressed in formulas (37) to (42).

[0098] (37).

[0099] (38).

[0100] (39).

[0101] (40).

[0102] (41).

[0103] (42).

[0104] Wherein, equation (37) represents the scenario s Next time t The power generation capacity of the wind-solar-energy storage station is equal to the sum of the direct power generation of wind and solar energy and the direct power generation of energy storage. Indicates the scenario in the day-ahead mode sThe direct wind power at the next time t is, Indicates the scenario in the day-ahead mode s The direct optical power at the next time t is: This is the scene in the day-ahead mode s Equation (38) represents the direct power generation of energy storage at the next time t. s At the next moment t, the charging power of the wind-solar-storage station is the charging power of the energy storage, where For the scene in the day-ahead mode s Next time t Equation (39) represents the charging power of the external environment to the energy storage in the day-ahead mode in the scenario s Next time t The energy storage charging equation is: the total energy storage charge is equal to the charging power of wind and light to the energy storage , The charging power from the outside to the energy storage The sum of This is the scene in the day-ahead mode s The total energy storage charge at the next time t is: This is the scene in the day-ahead mode s The charging power of the wind energy storage at the next time t is: This is the scene in the day-ahead mode s Equation (40) represents the charging power of the solar energy storage at the next time t. s The energy storage body discharge equation at time t is: The energy storage body discharge is the energy storage direct power. Formula (41) and formula (42) indicate that the total value of wind and solar direct power and wind and solar charging power to energy storage at time t in the day-ahead mode cannot exceed the current wind and solar output. All the above wind power, photovoltaic, and energy storage power values ​​are not less than 0.

[0105] The model of coordinated operation of wind power generation, photovoltaic power generation and energy storage in real-time mode is expressed as formula (43) to formula (48).

[0106] (43).

[0107] (44).

[0108] (45).

[0109] (46).

[0110] (47).

[0111] (48).

[0112] Wherein, equation (43) represents the real-time mode in the scene s The power generation of the wind-solar-energy storage station at the next time t is equal to the sum of its internal wind-solar direct power generation and energy storage direct power generation, where: Represents a scene in real-time mode s The direct wind power at the next time t is, Represents a scene in real-time mode s The direct optical power at the next time t is: For scenes in real-time mode s Equation (44) represents the energy storage direct power at the next time t in real-time mode. s The charging power of the wind-solar-storage station at the next time t is the charging power of the energy storage, where For scenes in real-time mode s At the next moment t, the charging power from the outside to the energy storage is: For scenes in real-time mode s The total energy storage charge at the next time t. Equation (45) represents the scenario in real-time mode s The equation for charging the energy storage at the next time t is: the total energy storage charge is equal to the charging power of wind and light to the energy storage , The charging power from the outside to the energy storage The sum of For scenes in real-time mode s The charging power of the wind energy storage at the next time t is: For scenes in real-time mode s Equation (46) represents the charging power of the light energy storage at the next time t. s The energy storage body discharge equation at time t is: The energy storage body discharge is the energy storage direct power. Formula (47) and formula (48) indicate that the total value of wind and solar direct power and wind and solar charging power to energy storage at time t in real-time mode cannot exceed the current wind and solar output. All the above wind power, photovoltaic, and energy storage power values ​​are not less than 0.

[0113] Among them, step 106: with the goal of maximizing benefits, solve the energy storage configuration model of the wind-solar-storage station, each of the information interaction models, and each of the wind power generation, photovoltaic power generation and energy storage coordinated operation mode models to obtain the energy storage configuration result of the wind-solar-storage station, that is, to solve the double-layer model established in steps 102 to 105, and obtain the energy storage configuration result of the wind-solar-storage station production simulation process under multiple modes. The double-layer model includes an upper model and a lower model, the upper model is the energy storage configuration model of the wind-solar-storage station, and the lower model includes an information interaction model in the day-ahead mode and an information interaction model in the real-time mode.

[0114] The two-layer model is solved using the yalmip and gurobi solvers of MATLAB R2023a.

[0115] The wind-solar-storage station energy storage configuration method designed in the present invention comprehensively considers the differences in interaction strategies between large-scale wind-solar-storage stations and power stations at all levels and users, and promotes the wind-solar-storage station to provide a production simulation operation mode that is beneficial to itself.

[0116] The present invention takes into account the output of wind power and photovoltaic power when designing the charging and discharging process of energy storage, and proposes a wind-photovoltaic-storage coordinated operation method within the station. Compared with the operation of energy storage in a single charging and discharging form, considering the coordinated interaction of wind-photovoltaic-storage is more conducive to promoting the optimization and adjustment of clean energy and effectively improving the overall energy efficiency of the power station.

[0117] In the simulation of wind, solar and storage production operation dominated by energy storage, the present invention has the flexibility to adapt to fluctuations in different modes, optimizes the operation strategy of the wind, solar and storage station according to the changes in incentives between modes, uses the differences between different modes to enrich the station arbitrage means, and improves the overall profitability reliability of the system.

[0118] The present invention forms a calculation example for simulation based on the actual urban wind, solar and load data. The results show that the change of energy storage power and capacity configuration cost has little effect on the configuration result. Even when the output level of wind, solar and storage stations is very different, there will be a stable configuration result based on the day-ahead-real-time mode: the capacity of the configured energy storage is 3.5-4 hours of full power charging and discharging.

[0119] Example 2

[0120] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for configuring energy storage in a wind-solar-storage station in Example 1.

[0121] Example 3

[0122] A computer program product includes a computer program, which, when executed by a processor, implements the steps of the wind-solar-storage station energy storage configuration method in Example 1.

[0123] Example 4

[0124] A computer device whose internal structure diagram can be shown as Figure 4As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store pending transactions. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the wind and solar storage station energy storage configuration method in Example 1 is implemented.

[0125] It should be noted that the object information (including but not limited to object device information, object personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in the present invention are all information and data authorized by the object or fully authorized by all parties.

[0126] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided by the present invention may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided by the present invention may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0127] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0128] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for configuring energy storage in a wind and solar power storage station, characterized in that: include: Cluster the operating data of wind and solar power output in the target historical time period of the wind and solar energy storage station to obtain multiple scenarios; Establish a wind-solar-storage station energy storage configuration model including at least two trading modes based on multiple scenarios; Establishing information constraints and configuration constraints for the wind-solar-storage station energy storage configuration model; According to the wind-solar-storage station energy storage configuration model, the information constraints and the configuration constraints, an information interaction model is constructed for each transaction mode; According to the energy storage configuration model of the wind-solar-storage station, a coordinated operation model of wind power generation, photovoltaic power generation and energy storage is constructed for each trading mode; With the goal of maximizing benefits, the energy storage configuration model of the wind-solar-storage station, the information interaction models, and the wind power generation, photovoltaic power generation and energy storage coordinated operation mode models are solved to obtain the energy storage configuration result of the wind-solar-storage station, and the energy storage configuration result includes the energy storage configuration power size and the energy storage configuration capacity size; The information constraint is expressed as: ； ； ； ； in, Indicates that the wind and solar storage field is standing in the scene s Next interactive section k Disclosure of information, Standing on the scene for the scenery storage field s Next interactive section k The upper limit of information disclosure, Standing on the scene for the scenery storage field s Next interactive section k The minimum limit of information disclosure, Indicates that the wind and solar storage field is standing in the scene s Next interactive section k- 1. Disclosure of Information, Indicates that the wind and solar storage field is standing in the scene s Next interactive section b Disclosure of information, Indicates that the wind and solar storage field is standing in the scene s Next interactive section b -1 information disclosure, Standing on the scene for the scenery storage field s Next interactive section b The upper limit of information disclosure, Standing on the scene for the scenery storage field s Next interactive section b The minimum limit for information disclosure; k It is the interactive section for the discharge of wind and solar storage stations. b Interactive segment for charging wind and solar storage stations.

2. The method for configuring energy storage for a wind-solar energy storage station according to claim 1, characterized in that: Cluster the operation data of wind and solar power output in the target historical time period of the wind and solar energy storage station to obtain multiple scenarios, including: The hierarchical K-means clustering algorithm is used to cluster the operating data of wind and solar power output in the target historical time period of the wind and solar energy storage station to obtain multiple scenarios.

3. The method for configuring energy storage in a wind-solar energy storage station according to claim 1, characterized in that: The transaction mode includes a day-ahead mode and a real-time mode, and the target historical time period is one year.

4. The method for configuring energy storage for a wind and solar power storage station according to claim 2, characterized in that: The energy storage configuration model of the wind-solar storage station is expressed as: ； ； ； ； in, is the annual average energy efficiency of the wind and solar power storage station in the day-ahead mode, is the average annual energy efficiency of the wind and solar storage station in real-time mode, is the average annual investment and construction cost of energy storage in wind and solar energy storage stations; S is a collection of scenes, For the scene s The number of days that appear in the full-year simulation run, T is the number of moments in a scene, The scene of the wind and solar farm station in the day-ahead mode s Next interactive section k The discharge power at time t, The scene of the wind and solar farm station in the day-ahead mode s Next interactive section b The charging power at time t, represents the marginal electricity price of the day-ahead mode at time t in scenario s, is the difference between two adjacent moments; Scenery and solar farm station in real-time mode s Next interactive section k The discharge power at time t, Scenery and solar farm station in real-time mode s Next interactive section b The charging power at time t, Representation scene s Real-time mode marginal electricity price under ; is the annual interest rate, L is the year of energy storage operation, Indicates the rated power of energy storage, Indicates the rated capacity of energy storage, is the unit power investment cost of energy storage, Represents the unit capacity investment cost of energy storage.

5. The method for configuring energy storage for a wind-solar energy storage station according to claim 4, characterized in that: The configuration constraints include wind and solar energy storage station energy storage configuration constraints, SoC constraints, state of charge constraints, and energy storage charging and discharging constraints.

6. The method for configuring energy storage in a wind-solar energy storage station according to claim 5, characterized in that: The information interaction model of the day-ahead mode is expressed as: ； in, For the scene s Next User j In the interactive section b Disclosure of electricity usage information, This is the scene in the day-ahead mode s Next User j In the interactive section b The interactive segment power; Representation scene s Lower unit i In the interactive section k Disclosure of power generation information, This is the scene in the day-ahead mode s Lower unit i In the interactive section k The interactive segment power; The information interaction model of real-time mode is expressed as: ； in, Represents a scene in real-time mode s Next User j In the interactive section b Interactive segment power of the time period, Represents a scene in real-time mode s Lower unit i In the interactive section k The interactive segment power.

7. The method for configuring energy storage in a wind-solar energy storage station according to claim 6, characterized in that: The coordinated operation model of wind power generation, photovoltaic power generation and energy storage in the day-ahead mode is expressed as: ； ； ； ； ； ； in, Indicates the scenario in the day-ahead mode s The direct wind power at the next time t is, Indicates the scenario in the day-ahead mode s The direct optical power at the next time t is: This is the scene in the day-ahead mode s The energy storage direct power at the next time t is: This is the scene in the day-ahead mode s The charging power from the outside to the energy storage at the next time t; This is the scene in the day-ahead mode s The total energy storage charge at the next time t is: This is the scene in the day-ahead mode s The total energy storage discharge at the next time t is: This is the scene in the day-ahead mode s The charging power of the wind energy storage at the next time t is: This is the scene in the day-ahead mode s The charging power of light to the energy storage at the next time t, Indicates the scenario in the day-ahead mode s The wind power output at the next time t is, Indicates the scenario in the day-ahead mode s The light energy output at the next time t; The model of coordinated operation of wind power generation, photovoltaic power generation and energy storage in real-time mode is expressed as: ； ； ； ； ； ； in, Represents a scene in real-time mode s The direct wind power at the next time t is, Represents a scene in real-time mode s The direct optical power at the next time t is: For scenes in real-time mode s The total energy storage discharge at the next time t is: For scenes in real-time mode s The energy storage direct power at the next time t is: For scenes in real-time mode s The charging power from the outside to the energy storage at the next time t; For scenes in real-time mode s The total energy storage charge at the next time t is: For scenes in real-time mode s The charging power of the wind energy storage at the next time t is: For scenes in real-time mode s The charging power of light to the energy storage at the next time t; Represents a scene in real-time mode s The wind power output at the next time t is, Represents a scene in real-time mode s The light energy output at the next time t.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method for configuring energy storage in a wind-solar-storage station as described in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for configuring energy storage in a wind-solar-storage station are implemented as described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method for configuring energy storage in a wind-solar-storage station are implemented as described in any one of claims 1 to 7.

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