Method for evaluating credible capacity considering energy storage operation strategy and related device

Abstract

This invention belongs to the field of reliable capacity assessment technology, and discloses a reliable capacity assessment method and related apparatus that takes into account energy storage operation strategies. The method includes: classifying energy storage resources; analyzing the operation strategies of energy storage resources by category and establishing an output model; simulating the output of energy storage resources based on the output model and historical or simulated data of the main power generation resources; obtaining an output characteristic model of the energy storage resources based on the simulated data, and conducting a reliable capacity assessment of the energy storage resources. By constructing a simulation of the energy storage resource output data using energy storage operation strategies, this invention proposes a differentiated reliable capacity assessment method based on energy storage operation strategies, providing guidance for energy storage resources to participate in the capacity market, contributing to the advancement of capacity market construction, and improving the reliability of the power system.

Description

Technical Field

[0001] This invention belongs to the field of reliable capacity assessment technology, and specifically relates to a reliable capacity assessment method and related apparatus that take into account energy storage operation strategies. Background Technology

[0002] During the transition from traditional energy to new energy, while new energy sources are clean and low-cost, they present significant challenges to the power grid's flexibility and sufficiency. Energy storage resources offer advantages such as fast response times and flexible configuration, providing inertia support for the power system and supplementing the grid's frequency regulation capabilities. Secondly, energy storage can promote the absorption of new energy sources on the power generation side and enable flexible grid capacity scheduling. The charging and discharging arrangements of energy storage systems help shift daytime power generation to nighttime peak consumption, increasing the grid's peak-shaving capabilities. Similarly, energy storage possesses discharge capabilities, serving as a primary capacity supplier to ensure the reliability of the power system. Furthermore, the synergy between energy storage and new energy sources can enhance the reliable capacity supply of new energy. Therefore, energy storage resources are not only a provider of regulation for the new power system but also a crucial support for capacity sufficiency.

[0003] The electricity market is developing rapidly at present. The willingness of renewable energy entities to configure and utilize energy storage is influenced by market interests. Therefore, it is necessary to assess and analyze the reliable capacity of renewable energy systems after energy storage configuration, in conjunction with energy storage operation strategies. This provides support for power system reliability analysis and electricity market mechanism design, thereby encouraging renewable energy units to actively configure energy storage and fully utilize it to improve their output characteristics. Independent energy storage currently involves significant investment, but it primarily profits from electricity market price differences. It is highly susceptible to electricity price fluctuations and uncertainty, making it difficult to clarify the cost structure and value of energy storage resources. This results in low utilization of the capacity support capabilities of independent energy storage resources, hindering investment incentives and rational utilization.

[0004] The capacity market determines the capacity support capability of various resources through credible capacity assessment and uses this as a basis for clearing pricing. Post-market settlement and evaluation still require assessment based on the credible capacity of the resource entities. Energy storage resources employ diverse operational strategies in the electricity market, resulting in varying output characteristics and different levels of system capacity support. Therefore, it is necessary to classify and assess the credible capacity of energy storage resources based on their different operational strategies. Differentiated credible capacity assessment methods can help energy storage resources actively explore participation in both the electricity and capacity markets. However, current credible capacity assessment methods for energy storage resources rarely consider operational strategies within the context of the electricity market, resulting in insufficient comprehensive consideration of these strategies and hindering the provision of reliable capacity support for energy storage resources participating in the capacity market. Furthermore, to ensure fair competition in the capacity market, the credible capacity assessment of energy storage resources should reference assessment methods used for renewable energy units. Therefore, a credible capacity assessment method that considers energy storage operational strategies is desired. Summary of the Invention

[0005] The purpose of this invention is to provide a reliable capacity assessment method and related apparatus that take into account energy storage operation strategies, so as to solve the above-mentioned problems.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a reliable capacity assessment method taking into account energy storage operation strategies, comprising: Classify energy storage resources; Analyze the operation strategies of energy storage resources by category and establish output models; Based on the output model, the output of energy storage resources is simulated according to the historical operation data or simulation data of the main power generation resources, and the output simulation data is obtained. The output characteristic model of energy storage resources is obtained based on the output simulation data. The reliability index of energy storage resources is calculated based on the output characteristic model of energy storage resources. The reliable capacity assessment of energy storage resources is carried out based on the reliability index of energy storage resources.

[0007] Optionally, the classification of energy storage resources includes: Energy storage resources are classified according to their type, capacity, and duration of continuous discharge.

[0008] Optionally, analyze grid-side energy storage operation strategies by category and establish output models, including: The operational strategies for grid-side independent energy storage include peak shaving and valley filling, commercial arbitrage, and supporting system reliability requirements, specifically: Peak shaving and valley filling objective function:

[0009]

[0010] In the formula, For load in Historical data at any given moment; This refers to the output value of independent energy storage on the grid side. , Independent energy storage resources Constant charging and discharging power; The objective function for commercial arbitrage is:

[0011] In the formula, , Independent energy storage on the grid side Constant charging and discharging power; , Independent energy storage on the grid side Market price of electrical energy during constant charging and discharging; The time interval is T; T is the total number of time periods in the optimization period. Support system reliability requirements objective function:

[0012]

[0013] In the formula, The set of daily peak load periods determined by the market to simulate the power output cycle; Power generation for the system Total output value at any given time; For conventional thermal power units Constant output value; For new energy units Constant output value; Optionally, the constraints for optimized operation of grid-side energy storage include: 1) Charge state constraints

[0014]

[0015] 2) Energy storage power constraints

[0016]

[0017]

[0018]

[0019]

[0020] In the formula, For independent energy storage resources State of charge at time t, At minimum state of charge, It is at its maximum state of charge; Minimum charging power for independent energy storage resources This represents the maximum discharge power of an independent energy storage resource. The minimum output value for independent energy storage resources. The upper limit of output for independent energy storage resources; , These refer to the charging and discharging efficiencies of independent energy storage resources, respectively. Rated power capacity for independent energy storage resources.

[0021] Optionally, the step of analyzing the power-side energy storage operation strategy of energy storage resources by category and establishing an output model includes: The operational strategies for power-side energy storage include peak shaving and valley filling, smoothing fluctuations in wind and solar power output, tracking planned wind and solar power output, commercial arbitrage, and supporting system reliability requirements. The energy storage optimization models for each operational strategy are as follows: Peak shaving and valley filling objective function:

[0022]

[0023] In the formula, For load in Historical data at any given moment; New energy generating units equipped with energy storage Initial output value at time; This refers to the total output value of the new energy generating unit and its supporting power-side energy storage. , Independent energy storage resources Constant charging and discharging power; The optimization objective for smoothing fluctuations in wind and solar power output is to minimize the difference between the total output of wind turbines / solar generators and energy storage at adjacent time points. The objective function is as follows:

[0024] In the formula, N represents the total number of time periods in the optimization phase.

[0025] The objective of tracking and optimizing wind and solar power output is to minimize the difference between the actual and planned output of new energy sources and energy storage. The objective function is as follows:

[0026] In the formula, The planned output value of the new energy generating unit with energy storage configured at time t.

[0027] The objective of commercial arbitrage optimization is to maximize the electricity market revenue of renewable energy generating units with energy storage and distribution capabilities. The objective function is:

[0028] In the formula, For the electricity spot market Real-time electricity prices; The capacity of the renewable energy generating units for energy storage exceeds the predicted deviation; Deviation assessment standards for new energy generating units; The objective function for optimizing the reliability requirements of the supporting system is set as minimizing the difference between the system capacity output and the load during peak load periods in the capacity market. Objective function:

[0029]

[0030] In the formula, For new energy generating units without energy storage Total output value at all times.

[0031] Optionally, the constraints for optimized operation of energy storage on the power supply side include: 1) Charge state constraints

[0032] 2) Energy storage power constraints

[0033]

[0034]

[0035]

[0036]

[0037] Under the optimized strategy of commercial arbitrage, the energy storage on the power supply side is charged from the renewable energy unit, and the charging power does not exceed the initial discharge power of the renewable energy unit. Therefore, the energy storage charging power constraint is increased:

[0038] In the formula, The state of charge of energy storage. At minimum state of charge, It is at its maximum state of charge; This represents the minimum charging power for energy storage. This represents the maximum energy storage discharge power. This is the lower limit of energy storage output. This represents the upper limit of energy storage output. This is the rated capacity of the energy storage.

[0039] Optionally, the step of simulating the output of energy storage resources based on the output model, using historical operating data or simulation data of the main power generation resource entity, includes: Based on historical data statistics of the output characteristics of conventional generating units, new energy generating units, and system load, output probability models of various resource entities are established. Output data of conventional generating units and new energy generating units are generated by stochastic production simulation method, and output data of energy storage resources are simulated according to the above operation strategy.

[0040] Optionally, the step of obtaining the output characteristic model of the energy storage resource based on simulation data and conducting a reliable capacity assessment of the energy storage resource includes: Based on simulated operational output data of energy storage resources, the output characteristics of similar energy storage resources are statistically analyzed, an output probability model of energy storage resources is established, and the reliable capacity of energy storage resources is evaluated. First, a system containing both conventional and renewable energy units is used as the basic scenario, and the reliability index of the basic scenario is calculated in combination with the system load output characteristics. Then, the energy storage resources to be evaluated are added to the system, and the system reliability index after the addition of energy storage resources is calculated. Based on scenarios involving energy storage, the system load output is adjusted, and the system reliability indicators are iteratively calculated until the system reliability indicators are reached. Equal to the basic scenario reliability index, the increased system load output value at this time is the equivalent reliable capacity of the energy storage resources.

[0041] Secondly, the present invention provides a reliable capacity assessment system that takes into account energy storage operation strategies, comprising: The classification module is used to classify energy storage resources; The output model building module is used to analyze the operation strategies of energy storage resources by category and build output models; The output simulation module is used to simulate the output of energy storage resources based on the output model and the historical or simulation data of the main power generation resources, and to obtain output simulation data. The evaluation module is used to obtain the output characteristic model of energy storage resources based on the output simulation data, calculate the reliability index of energy storage resources based on the output characteristic model of energy storage resources, and evaluate the reliable capacity of energy storage resources based on the reliability index of energy storage resources.

[0042] Thirdly, the present invention provides a computer device including 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 reliable capacity assessment method taking into account energy storage operation strategies.

[0043] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the reliable capacity assessment method taking into account energy storage operation strategies.

[0044] Compared with the prior art, the present invention has the following technical effects: This invention categorizes energy storage resources based on characteristics such as application scenarios, resource types, capacity scale, and continuous discharge duration. It analyzes operational strategies for grid-side and power-side energy storage, establishing output models for energy storage resources based on strategies such as peak shaving and valley filling, commercial arbitrage, and supporting system reliability requirements. Then, based on historical or simulated operational data of the main power generation resources, output simulation is performed using the energy storage resource output models. Finally, characteristic analysis is conducted on the simulated output of energy storage resources, and a reliable capacity assessment is performed. By constructing simulated output data of energy storage resources based on operational strategies, a differentiated reliable capacity assessment method based on energy storage operational strategies is proposed. This provides guidance for energy storage resources to participate in the capacity market, contributing to the advancement of capacity market construction and improving power system reliability. Attached Figure Description

[0045] Figure 1 This is a diagram summarizing the energy storage operation strategy of this invention.

[0046] Figure 2 This is a logical block diagram of the reliable capacity assessment based on the energy storage operation strategy of this invention.

[0047] Figure 3 This is a flowchart of the present invention. Detailed Implementation

[0048] The present invention will be further described below with reference to the accompanying drawings: Example 1, please refer to Figure 3 This invention provides a reliable capacity assessment method considering energy storage operation strategies, comprising: Classify energy storage resources; Analyze the grid-side and power-side energy storage operation strategies of energy storage resources by category and establish output models; Based on the output model, the output of energy storage resources is simulated according to the historical operation data or simulation data of the main power generation resources, and the output simulation data is obtained. Based on the output simulation data, an output characteristic model of the energy storage resource is obtained. Based on the output characteristic model, the reliability index of the energy storage resource is calculated. Based on the reliability index, the reliable capacity assessment of the energy storage resource is performed. Example 2: This invention provides a reliable capacity assessment method considering energy storage operation strategies, specifically including: This study investigates reliable capacity assessment methods for energy storage resources by combining operational strategies with the research. First, energy storage resources need to be categorized. Then, operational strategies for each category are analyzed, and output models are established. Next, historical operational data is used to model the output characteristics of conventional generating units, renewable energy generating units, and other resources, simulating the output of various resources, including energy storage resources. Based on the simulated data, the output characteristic models of energy storage resources are analyzed to conduct reliable capacity assessments.

[0049] Energy storage, with its discharge function, can be considered a primary source of power generation. Considering the diverse participants in the capacity market, the focus should be on power source-side and grid-side energy storage resources. Based on the capacity market definition, the reliable capacity of energy storage should primarily focus on its capacity support capability during peak load periods. However, the capacity limitations of energy storage resources affect its support capability, and the different energy storage deployment methods and priorities under different operating strategies lead to variations in energy storage output during peak load periods, directly impacting its reliable capacity. Therefore, it is necessary to model energy storage operating strategies and simulate output, and evaluate the reliable capacity of energy storage based on the simulated output during peak load periods. The detailed evaluation process is as follows: Energy storage resources are classified according to their capacity limitations and types. Determine the operation strategy based on the type of energy storage resources and establish a scheduling operation optimization model; The output of energy storage resources is simulated based on historical or simulation data of the main power generation resources. Based on the simulated operational output data of energy storage resources, the reliable capacity of energy storage resources is assessed.

[0050] The credible capacity of the capacity market is defined as the capacity that market participants can be equivalent to an ideal generating unit during peak load periods. The capacity support capability of energy storage resources is affected by their capacity and continuous discharge time. Therefore, energy storage resources are classified according to their type, capacity scale, and continuous discharge duration, and the credible capacity of energy storage is assessed accordingly.

[0051] The operational strategy of energy storage resources determines the output characteristics of energy storage. Operational strategies are determined based on the type of energy storage resource, and a scheduling and operation control strategy model is established. In practical applications, typical operational strategies for energy storage systems include peak shaving and valley filling, smoothing fluctuations in wind and solar power output, tracking wind and solar power output, commercial arbitrage, and supporting system reliability requirements.

[0052] The operation strategies for grid-side independent energy storage mainly focus on peak shaving and valley filling, commercial arbitrage, and supporting system reliability requirements. The energy storage optimization models for each operation strategy are as follows: I. Peak shaving and valley filling Grid-side independent energy storage systems reduce electricity demand during peak load periods and increase electricity consumption or store energy during off-peak periods to achieve peak shaving and valley filling, balancing grid supply and demand and reducing the peak-valley difference. Currently, most grid-side independent energy storage systems in my country are directly accessed by power operators; therefore, the main objective of peak shaving and valley filling is to minimize the daily peak-valley difference of the system load after considering grid-side independent energy storage.

[0053] Objective function:

[0054]

[0055] In the formula, For load in Historical data at any given moment; This refers to the output value of independent energy storage on the grid side. , Independent energy storage resources Constant charging and discharging power.

[0056] II. Commercial Arbitrage Under the electricity market model, grid-side independent energy storage resources can participate in market competition and arbitrage as market players to determine charging and discharging plans. At present, my country's energy storage resources can participate in the electricity market and ancillary service market and profit from them. Considering that the electricity market and ancillary service market in various provinces and cities are clearing up separately at present, we will consider studying the operation strategy of energy storage resources based on a single electricity market clearing model.

[0057] In a single electricity market environment, the way for energy storage systems to benefit is "low storage and high generation". Assuming that energy storage resources do not affect the electricity market price and can accurately predict the electricity market price, the optimization objective of the energy storage resource operation simulation is set to maximize the revenue in the electricity market, while considering the constraints of power system operation and energy storage operation.

[0058] The objective function is:

[0059] In the formula, , Independent energy storage on the grid side Constant charging and discharging power; , Independent energy storage on the grid side Market price of electrical energy during constant charging and discharging; denoted as the time interval; T represents the total number of time periods during the optimization period.

[0060] III. Reliability Requirements of Supporting Systems Grid-side energy storage resources possess reliability support capabilities. During peak load periods, the higher the energy storage support capacity, the higher its reliable capacity, resulting in better support for system reliability and higher corresponding capacity market revenue. Considering that reliable capacity assessment in the capacity market essentially determines the peak load period, the optimization objective function for grid-side independent energy storage resources is set to minimize the difference between system capacity output and load during peak load periods in the capacity market, based on the considerations of supporting system reliability and maximizing reliable capacity.

[0061] Objective function:

[0062]

[0063] In the formula, The set of daily peak load periods determined by the market to simulate the power output cycle; Power generation for the system Total output value at any given time; For conventional thermal power units Constant output value; For new energy units Constant output value.

[0064] The constraints for optimized operation of grid-side energy storage include: 1) Charge state constraints

[0065]

[0066] 2) Energy storage power constraints

[0067]

[0068]

[0069]

[0070]

[0071] In the formula, For independent energy storage resources State of charge at time t, At minimum state of charge, It is at its maximum state of charge; Minimum charging power for independent energy storage resources This represents the maximum discharge power of an independent energy storage resource. The minimum output value for independent energy storage resources. The upper limit of output for independent energy storage resources; , These refer to the charging and discharging efficiencies of independent energy storage resources, respectively. Rated power capacity for independent energy storage resources.

[0072] Power-side energy storage primarily serves as supporting storage for wind turbines and photovoltaic (PV) units, optimizing the output of these renewable energy units. Renewable energy units and power-side energy storage are typically considered as a whole for reliable capacity assessment and analysis. The operational strategies for power-side energy storage mainly include peak shaving and valley filling, smoothing fluctuations in wind and solar output, tracking planned wind and solar output, commercial arbitrage, and supporting system reliability requirements. The energy storage optimization models for each operational strategy are as follows: I. Peak shaving and valley filling Energy storage on the power supply side can store excess electricity during peak periods of renewable energy output and discharge it during off-peak periods. Therefore, the main purpose of energy storage on the power supply side for peak shaving and valley filling is to cooperate with renewable energy units to reduce the load peak-valley difference.

[0073] Objective function:

[0074]

[0075] In the formula, For load in Historical data at any given moment; New energy generating units equipped with energy storage Initial output value at time; This refers to the total output value of the new energy generating unit and its supporting power-side energy storage. , Independent energy storage resources Constant charging and discharging power.

[0076] II. Smoothing fluctuations in wind and solar power output Energy storage resources on the power supply side can assist wind turbines and photovoltaic units, smoothing out fluctuations in wind and solar power output, making the overall power generation output of new energy units more stable, and improving the stability and reliability of the power system. The optimization objective for smoothing out fluctuations in wind and solar power output is to minimize the difference between the total output of wind turbines / photovoltaic units and energy storage at adjacent times.

[0077] The objective function is as follows:

[0078] In the formula, N represents the total number of time periods in the optimization phase.

[0079] III. Tracking the output of wind and solar power Energy storage on the power supply side can also track the planned output based on the predicted output of new energy sources, thereby reducing the deviation between the actual output and the predicted output of wind and solar power, and minimizing prediction errors. The optimization goal of energy storage tracking the planned output is to minimize the difference between the actual output and the planned output of new energy sources and energy storage.

[0080] The objective function is as follows:

[0081] In the formula, The planned output value of the new energy generating unit with energy storage configured at time t.

[0082] IV. Commercial Arbitrage In the electricity market, energy storage resources on the power generation side work in conjunction with renewable energy generating units to improve electricity revenue. This involves charging the renewable energy units during peak power generation periods and discharging during peak load periods to achieve higher revenue. However, the configured energy storage and renewable energy generating units should be considered as a whole, taking into account the impact of predicted output deviations from the renewable energy generating units. Therefore, assuming that the renewable energy generating units with energy storage accept market prices, the optimization objective of grid-side energy storage resources is to maximize the electricity market revenue of the renewable energy generating units with energy storage.

[0083] The objective function is:

[0084] In the formula, For the electricity spot market Real-time electricity prices; The capacity of the renewable energy generating units for energy storage exceeds the predicted deviation; This serves as the deviation assessment standard for new energy power units.

[0085] V. Reliability Requirements of Supporting Systems Although the output of renewable energy units is uncertain, they still provide some support for system reliability. When renewable energy units are combined with power-side energy storage, the uncertainty of renewable energy unit output can be mitigated to a certain extent, improving power supply reliability. Therefore, renewable energy units with energy storage can be used to support system reliability requirements. In the capacity market, reliable capacity assessment is based on capacity supply during peak load periods. Therefore, the optimization objective function of power-side energy storage is set as minimizing the difference between the system capacity output and load during peak load periods in the capacity market.

[0086] Objective function:

[0087]

[0088] In the formula, For new energy generating units without energy storage Total output value at all times.

[0089] The constraints for optimized operation of energy storage on the power supply side include: 1) Charge state constraints

[0090] 2) Energy storage power constraints

[0091]

[0092]

[0093]

[0094]

[0095] Under the optimized strategy of commercial arbitrage, the energy storage on the power supply side is charged from the renewable energy unit, and the charging power does not exceed the initial discharge power of the renewable energy unit. Therefore, the energy storage charging power constraint is increased:

[0096] In the formula, The state of charge of energy storage. At minimum state of charge, It is at its maximum state of charge; This represents the minimum charging power for energy storage. This represents the maximum energy storage discharge power. This is the lower limit of energy storage output. This represents the upper limit of energy storage output. This is the rated capacity of the energy storage.

[0097] After determining the energy storage resource operation strategy, the output of the energy storage resources is simulated based on the historical operation data or simulation data of the power generation resource entities. Based on the output characteristics of conventional units, new energy units, and system load statistically based on historical data, output probability models of various resource entities are established. Output data of conventional units and new energy units are generated by stochastic production simulation method, and the output data of energy storage resources is simulated according to the above operation strategy.

[0098] Based on simulated operational output data of energy storage resources, the output characteristics of similar energy storage resources are statistically analyzed, an output characteristic model of energy storage resources is established, and the reliable capacity of energy storage resources is evaluated. First, a system including conventional and renewable energy units is used as the basic scenario, and reliability indicators of the basic scenario are calculated based on the system load output characteristics. Then, the energy storage resources to be evaluated are added to the system, and the system reliability index after the addition of energy storage resources is calculated. Based on scenarios involving energy storage, the system load output is gradually adjusted, and the system reliability indicators are iteratively calculated until the system reliability indicators are met. The reliability index is basically equal to that of the basic scenario. At this time, the increased system load output value is the equivalent reliable capacity of the energy storage resources.

[0099] This invention classifies energy storage resources based on characteristics such as application scenarios, resource types, capacity scale, and continuous discharge duration. Secondly, it analyzes operational strategies for grid-side and power-side energy storage, establishing energy storage resource output models for operational strategies such as peak shaving and valley filling, commercial arbitrage, and supporting system reliability requirements. Then, based on historical or simulated data from the main power generation resources, it simulates the output of energy storage resources using these output models. Finally, it analyzes the characteristics of the simulated output of energy storage resources and conducts a reliable capacity assessment. This invention classifies energy storage resources and conducts reliable capacity assessments for different types and operational strategies, which is beneficial for incorporating energy storage resources into the capacity market and promoting the development of the capacity market.

[0100] In another embodiment of the present invention, a reliable capacity assessment system considering energy storage operation strategies is provided, which can be used to implement the above-mentioned reliable capacity assessment method considering energy storage operation strategies. Specifically, the system includes: The classification module is used to classify energy storage resources; The output model building module is used to analyze the grid-side energy storage and power-side energy storage operation strategies of energy storage resources by category and to build output models. The output simulation module is used to simulate the output of energy storage resources based on the output model and the historical or simulation data of the main power generation resources, and to obtain output simulation data. The evaluation module is used to obtain the output characteristic model of energy storage resources based on the output simulation data, calculate the reliability index of energy storage resources based on the output characteristic model of energy storage resources, and evaluate the reliable capacity of energy storage resources based on the reliability index of energy storage resources.

[0101] The module division in this embodiment of the invention is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in the various embodiments of the invention can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0102] In another embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to achieve corresponding method flows or corresponding functions. The processor described in this embodiment of the present invention can be used for the operation of a reliable capacity assessment method considering energy storage operation strategies.

[0103] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the reliable capacity assessment method considering energy storage operation strategies in the above embodiments.

[0104] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0105] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0106] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0107] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0108] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A reliable capacity assessment method considering energy storage operation strategies, characterized in that, include: Classify energy storage resources; Analyze the operation strategies of energy storage resources by category and establish output models; Based on the output model, the output of energy storage resources is simulated according to the historical operation data or simulation data of the main power generation resources, and the output simulation data is obtained. The output characteristic model of energy storage resources is obtained based on the output simulation data. The reliability index of energy storage resources is calculated based on the output characteristic model of energy storage resources. The reliable capacity assessment of energy storage resources is carried out based on the reliability index of energy storage resources. Analyze the operation strategies of energy storage resources by category and establish output models, where grid-side energy storage includes: The operational strategies for grid-side independent energy storage include peak shaving and valley filling, commercial arbitrage, and supporting system reliability requirements, specifically: Peak shaving and valley filling objective function: In the formula, For load in Historical data at any given moment; This refers to the output value of independent energy storage on the grid side. , Independent energy storage resources Constant charging and discharging power; The objective function for commercial arbitrage is: In the formula, , Independent energy storage on the grid side Constant charging and discharging power; , Independent energy storage on the grid side Market price of electrical energy during constant charging and discharging; The time interval is T; T is the total number of time periods in the optimization period. Support system reliability requirements objective function: In the formula, The set of daily peak load periods determined by the market to simulate the power output cycle; Power generation for the system Total output value at any given time; For conventional thermal power units Constant output value; For new energy units Constant output value; The process of obtaining an output characteristic model of energy storage resources based on output simulation data, calculating energy storage resource reliability indicators based on the output characteristic model, and assessing the reliable capacity of energy storage resources based on the energy storage resource reliability indicators includes: Based on the output simulation data of energy storage resources, the output characteristics of similar energy storage resources are statistically analyzed, an output characteristic model of energy storage resources is established, and the reliable capacity of energy storage resources is evaluated. First, a system containing both conventional and new energy units is used as the basic scenario, and the reliability index of the basic scenario is calculated in conjunction with the output characteristic model of energy storage resources. Then, the energy storage resource to be evaluated is added to the energy storage resource output characteristic model, and the reliability index after adding the energy storage resource is calculated. Based on scenarios involving energy storage, the output characteristic model of energy storage resources is adjusted according to load output, and the system reliability index is iteratively calculated. Until reliability indicators Equal to the basic scenario reliability index, the increased system load output value at this time is the equivalent reliable capacity of the energy storage resources.

2. The reliable capacity assessment method considering energy storage operation strategies according to claim 1, characterized in that, The classification of energy storage resources includes: Energy storage resources are classified according to their type, capacity, and duration of continuous discharge.

3. The reliable capacity assessment method considering energy storage operation strategies according to claim 1, characterized in that, The constraints for optimized operation of grid-side energy storage include: 1) Charge state constraints 2) Energy storage power constraints In the formula, For independent energy storage resources State of charge at time t, At minimum state of charge, It is at its maximum state of charge; Minimum charging power for independent energy storage resources This represents the maximum discharge power of an independent energy storage resource. The minimum output value for independent energy storage resources. The upper limit of output for independent energy storage resources; , These refer to the charging and discharging efficiencies of independent energy storage resources, respectively. Rated power capacity for independent energy storage resources.

4. The reliable capacity assessment method considering energy storage operation strategies according to claim 1, characterized in that, The analysis of energy storage resource operation strategies by category and the establishment of output models include power source-side energy storage: The operational strategies for power-side energy storage include peak shaving and valley filling, smoothing fluctuations in wind and solar power output, tracking planned wind and solar power output, commercial arbitrage, and supporting system reliability requirements. The energy storage optimization models for each operational strategy are as follows: Peak shaving and valley filling objective function: In the formula, For load in Historical data at any given moment; New energy generating units equipped with energy storage Initial output value at time; This refers to the total output value of the new energy generating unit and its supporting power-side energy storage. , Independent energy storage resources Constant charging and discharging power; The optimization objective for smoothing fluctuations in wind and solar power output is to minimize the difference between the total output of wind turbines / solar generators and energy storage at adjacent time points. The objective function is as follows: In the formula, N is the total number of time periods in the optimization phase; The objective of optimizing the output of wind and solar power is to minimize the difference between the actual output and the planned output of new energy sources and energy storage. The objective function is as follows: In the formula, The planned output value of the new energy generating unit with energy storage configured at time t; The objective of commercial arbitrage optimization is to maximize the electricity market revenue of renewable energy generating units with energy storage and distribution capabilities. The objective function is: In the formula, For the electricity spot market Real-time electricity prices; The capacity of the renewable energy generating units for energy storage exceeds the predicted deviation; Deviation assessment standards for new energy generating units; The objective function for optimizing the reliability requirements of the supporting system is set as minimizing the difference between the system capacity output and the load during peak load periods in the capacity market. Objective function: In the formula, For new energy generating units without energy storage Total output value at all times.

5. The reliable capacity assessment method considering energy storage operation strategies according to claim 4, characterized in that, The constraints for optimized operation of energy storage on the power supply side include: 1) Charge state constraints 2) Energy storage power constraints Under the optimized strategy of commercial arbitrage, the energy storage on the power supply side is charged from the renewable energy unit, and the charging power does not exceed the initial discharge power of the renewable energy unit. Therefore, the energy storage charging power constraint is increased: In the formula, The state of charge of energy storage. At minimum state of charge, It is at its maximum state of charge; This represents the minimum charging power for energy storage. This represents the maximum energy storage discharge power. This is the lower limit of energy storage output. This represents the upper limit of energy storage output. This is the rated capacity of the energy storage.

6. The reliable capacity assessment method considering energy storage operation strategies according to claim 1, characterized in that, The output simulation data, based on the output model and using historical or simulation data of the main power generation resources, includes: Based on historical data statistics of the output characteristics of conventional generating units, new energy generating units, and system load, output probability models of various resource entities are established. Output data of conventional generating units and new energy generating units are generated by stochastic production simulation method, and output data of energy storage resources are simulated according to the above operation strategy.

7. A reliable capacity assessment system considering energy storage operation strategies, characterized in that, include: The classification module is used to classify energy storage resources; The output model building module is used to analyze the operation strategies of energy storage resources by category and build output models; The output simulation module is used to simulate the output of energy storage resources based on the output model and the historical or simulation data of the main power generation resources, and to obtain output simulation data. The evaluation module is used to obtain the output characteristic model of the energy storage resource based on the output simulation data, calculate the reliability index of the energy storage resource based on the output characteristic model of the energy storage resource, and evaluate the reliable capacity of the energy storage resource based on the reliability index of the energy storage resource. Analyze the operation strategies of energy storage resources by category and establish output models, where grid-side energy storage includes: The operational strategies for grid-side independent energy storage include peak shaving and valley filling, commercial arbitrage, and supporting system reliability requirements, specifically: Peak shaving and valley filling objective function: In the formula, For load in Historical data at any given moment; This refers to the output value of independent energy storage on the grid side. , Independent energy storage resources Constant charging and discharging power; The objective function for commercial arbitrage is: In the formula, , Independent energy storage on the grid side Constant charging and discharging power; , Independent energy storage on the grid side Market price of electrical energy during constant charging and discharging; The time interval is T; T is the total number of time periods in the optimization period. Support system reliability requirements objective function: In the formula, The set of daily peak load periods determined by the market to simulate the power output cycle; Power generation for the system Total output value at any given time; For conventional thermal power units Constant output value; For new energy units Constant output value; The process of obtaining an output characteristic model of energy storage resources based on output simulation data, calculating energy storage resource reliability indicators based on the output characteristic model, and assessing the reliable capacity of energy storage resources based on the energy storage resource reliability indicators includes: Based on the output simulation data of energy storage resources, the output characteristics of similar energy storage resources are statistically analyzed, an output characteristic model of energy storage resources is established, and the reliable capacity of energy storage resources is evaluated. First, a system containing both conventional and new energy units is used as the basic scenario, and the reliability index of the basic scenario is calculated in conjunction with the output characteristic model of energy storage resources. Then, the energy storage resource to be evaluated is added to the energy storage resource output characteristic model, and the reliability index after adding the energy storage resource is calculated. Based on scenarios involving energy storage, the output characteristic model of energy storage resources is adjusted according to load output, and the system reliability index is iteratively calculated. Until reliability indicators Equal to the basic scenario reliability index, the increased system load output value at this time is the equivalent reliable capacity of the energy storage resources.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the reliable capacity assessment method considering energy storage operation strategies as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the reliable capacity assessment method taking into account energy storage operation strategies as described in any one of claims 1 to 6.

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