Simulation platform and implementation method of distributed hybrid cloud energy storage participating in power trading market

Abstract

The embodiments of this specification provide a simulation platform and implementation method for distributed hybrid cloud energy storage to participate in the electricity trading market, wherein the simulation platform includes: a configuration module, which is used to set the operation simulation parameters of the operation simulation module and the market simulation parameters of the market simulation module according to the user's input; an operation simulation module, which is used to simulate the operation status of the distributed hybrid energy storage system in the distribution network through a pre-built energy storage model based on the operation simulation parameters and the energy storage system operation strategy, obtain the energy storage planning results and display them to the user, and send the energy storage planning results to the market simulation module through the data interface; a market simulation module, which is used to simulate the trading behavior of the distributed hybrid energy storage system participating in the electricity market in two stages within the day and the day before based on the market simulation parameters and the market bidding strategy through a bidding clearing model, obtain the market simulation results and display them to the user, and transmit the market simulation results to the operation simulation module through the data interface.

Description

Technical Field

[0001] This document relates to the field of energy storage simulation technology, and in particular to a simulation platform and implementation method for distributed hybrid cloud energy storage participating in the electricity trading market. Background Art

[0002] As the construction of new power systems continues to deepen, a high proportion of renewable energy integration and an open, flexible electricity market will become the fundamental characteristics and development trends of the power system. On the one hand, the new distribution network will exhibit a complex, diverse and flexible development trend. The integration of a high proportion of random and volatile renewable energy units will pose new challenges to the safe, stable, and flexible operation of the distribution network system. On the other hand, an open and flexible electricity market will also inject new vitality into the new distribution network, significantly improving the flexibility, reliability, and economic efficiency of system operation. Distributed hybrid energy storage technology, as a key technology in the new power system, will become an important means to address the instability of renewable energy output and ensure the reliable operation of the power grid. It will also become a major player in the new power market.

[0003] Currently, China lacks an advanced distributed hybrid cloud energy storage simulation platform for new power systems. This requires extensive manual calculations, placing a heavy workload on grassroots personnel and making it difficult for power companies to fully understand the operational status of energy storage systems of varying locations and capacities connected to the distribution network. Therefore, a technical solution for a simulation platform that enables distributed hybrid cloud energy storage to participate in power trading markets is urgently needed. Summary of the Invention

[0004] The purpose of the present invention is to provide a simulation platform and implementation method for distributed hybrid cloud energy storage participating in the electricity trading market, aiming to solve the above-mentioned problems in the prior art.

[0005] The present invention provides a simulation platform for distributed hybrid cloud energy storage participating in the power trading market. The platform is constructed using cloud computing technology, supports distributed computing and storage, and supports dynamic resource expansion. The simulation platform specifically includes:

[0006] A configuration module, used to set the operation simulation parameters of the operation simulation module and the market simulation parameters of the market simulation module according to the user's input;

[0007] An operation simulation module is used to simulate the operation status of the distributed hybrid energy storage system in the distribution network through a pre-built energy storage model based on the operation simulation parameters and the energy storage system operation strategy, obtain energy storage planning results and display them to the user, and send the energy storage planning results to the market simulation module through a data interface;

[0008] The market simulation module is used to simulate the trading behavior of the two-stage distributed hybrid energy storage system participating in the power market in the day before and within the day through a bidding clearing model based on the market simulation parameters and market bidding strategy, obtain market simulation results and display them to the user, and transmit the market simulation results to the operation simulation module through the data interface.

[0009] The present invention provides a method for implementing a simulation platform for distributed hybrid cloud energy storage to participate in an electricity trading market, which is used for the simulation platform for distributed hybrid cloud energy storage to participate in an electricity trading market. The method specifically includes:

[0010] Setting the operation simulation parameters of the operation simulation module and the market simulation parameters of the market simulation module according to the user's input;

[0011] Based on the operation simulation parameters and the energy storage system operation strategy, the operation status of the distributed hybrid energy storage system in the distribution network is simulated through a pre-built energy storage model, the energy storage planning results are obtained and displayed to the user, and the energy storage planning results are sent to the market simulation module through the data interface;

[0012] Based on the market simulation parameters and market bidding strategy, the trading behavior of the two-stage distributed hybrid energy storage system participating in the power market is simulated by the bidding clearing model, the market simulation results are obtained and displayed to the user, and the market simulation results are transmitted to the operation simulation module through the data interface.

[0013] The embodiment of the present invention integrates two core functional modules, operation simulation and market simulation, and can comprehensively evaluate the reliability and economic efficiency of distributed hybrid energy storage systems in new power systems. The technical solution of the embodiment of the present invention provides strong technical support and decision-making basis for power grid companies, energy storage operators, and related research institutions through highly integrated and collaborative technical means. It meets the relevant business needs of power companies and supports distributed hybrid energy storage in supporting real-world business needs such as distribution network operation simulation and power market transaction simulation, solving the problem of the lack of simulation tools in China that can visualize topological models and simulation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate one or more embodiments of this specification or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0015] Figure 1Schematic diagram of a simulation platform for distributed hybrid cloud energy storage participating in a power trading market according to an embodiment of the present invention;

[0016] Figure 2 This is a detailed architectural diagram of a simulation platform for distributed hybrid cloud energy storage participating in the power trading market according to an embodiment of the present invention;

[0017] Figure 3 This is a schematic diagram of the operation process of a simulation platform for distributed hybrid cloud energy storage participating in the power trading market according to an embodiment of the present invention;

[0018] Figure 4 This is a data logic and calculation flow chart of the power trading market according to an embodiment of the present invention;

[0019] Figure 5 This is a diagram of the main structure of the power trading market in an embodiment of the present invention;

[0020] Figure 6 It is a flow chart of the implementation method of the simulation platform for distributed hybrid cloud energy storage participating in the electricity trading market in an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below in conjunction with the drawings in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this document.

[0022] Device embodiment

[0023] According to an embodiment of the present invention, a simulation platform for distributed hybrid cloud energy storage participating in the power trading market is provided. The platform is built using cloud computing technology, supports distributed computing and storage, and supports dynamic resource expansion. Figure 1 Schematic diagram of a simulation platform for distributed hybrid cloud energy storage participating in the power trading market according to an embodiment of the present invention. Figure 1 As shown, the simulation platform for distributed hybrid cloud energy storage participating in the power trading market according to an embodiment of the present invention specifically includes:

[0024] The configuration module 10 is used to set the operation simulation parameters of the operation simulation module and the market simulation parameters of the market simulation module according to the user's input; the configuration module 10 is specifically used to: provide a configuration interface for the operation simulation parameters and the market simulation parameters through a visual interface, wherein the operation simulation parameters specifically include: power grid topology, distributed hybrid cloud energy storage system configuration, and simulation time granularity; the market simulation parameters specifically include: market parameters, market rules and simulation time granularity.

[0025] The operation simulation module 12 is used to simulate the operating status of the distributed hybrid energy storage system in the distribution network through a pre-built energy storage model based on the operation simulation parameters and the energy storage system operation strategy, obtain energy storage planning results and display them to the user, and send the energy storage planning results to the market simulation module through the data interface; the operation simulation module 12 is further used to: optimize the energy storage system operation strategy according to the market simulation results; the operation simulation module 12 is specifically used to:

[0026] Based on the market simulation parameters and market bidding strategy, the distributed hybrid energy storage system's trading behavior in the power market is simulated to achieve grid topology construction, energy storage / load / distributed energy operation simulation, demand response mechanism, power trading, real-time electricity price simulation, and user-side response behavior to electricity prices and power supply reliability. Specifically:

[0027] Call the existing power grid architecture and parameters from the database and provide an interface for users to customize the power grid topology structure, enabling users to input and modify node parameters, line parameters and load parameters;

[0028] Freely adjust the time step and / or time resolution during simulation based on user input, depending on the complexity of the specific application scenario and the requirements for result accuracy;

[0029] Constructing detailed energy storage models to simulate key characteristics of these energy storage systems, including the charging and discharging process, efficiency loss, and lifespan degradation. Specifically, the energy storage models include: an electrical energy storage model, a thermal energy storage model, a hydrogen energy storage model, and the coupling models between them.

[0030] Integrate demand response mechanism to simulate user-side response behavior to electricity prices and power supply reliability.

[0031] The market simulation module 14 is used to simulate the trading behavior of the two-stage distributed hybrid energy storage system participating in the power market through the bidding clearing model based on the market simulation parameters and the market bidding strategy, obtain the market simulation results and display them to the user, and transmit the market simulation results to the operation simulation module through the data interface. The market simulation module 14 is further used to optimize the market bidding strategy according to the energy storage planning results. The market simulation module 14 is specifically used to:

[0032] Based on the market simulation parameters and market bidding strategy, the distributed hybrid energy storage system's trading behavior in the power market is simulated to achieve day-ahead bidding, intraday real-time rolling calculation, and economic simulation functions of market disturbance response. Specifically:

[0033] Build a day-ahead bidding clearing model to perform classified calculations for the energy market and frequency regulation market. Automatically calculate the clearing results based on the declared parameters entered by the user and display the relevant calculation results.

[0034] Real-time rolling calculations are performed intraday to conduct bidding and clearing calculations for each period of the day. The optimization results of the previous period are used as input for the next stage of calculations. The bidding strategy and market clearing results are dynamically adjusted based on real-time market information and simulation results.

[0035] The built-in perturbation program simulates and calculates the market under various perturbation environments and provides risk assessment functions to evaluate the benefits and risks of energy storage systems under different market conditions.

[0036] Through the result display model and report generation tools, chart display, data export and report customization are carried out, and detailed simulation reports and analysis results are generated according to user needs.

[0037] The technical solution of the embodiment of the present invention constructs an application and economic simulation platform based on cloud architecture for distributed hybrid energy storage to participate in supporting the operation of the distribution network. The application function reflects the distributed energy storage operation simulation, and the economic function reflects the distributed energy storage market simulation. The two functional modules cooperate with each other and operate in a coordinated manner, providing strong technical support for the operation control strategy and economic evaluation analysis of the distributed energy storage operator under the optimal profit.

[0038] The technical solutions of the embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0039] Simulating the operation of distributed hybrid energy storage systems supporting distribution network operations requires input of information such as grid topology, operational information of energy storage / loads / distributed energy resources, demand response information, energy trading, and real-time electricity prices. It also supports output of calculation results such as power flow analysis, energy storage's participation in distribution system dispatch / services, and energy / power consumption by all parties. Simulating the power market of distributed hybrid cloud energy storage systems supporting grid operations requires input of demand response information and simulation results of energy storage participating in grid operations from the operational simulation platform, as well as output of calculation results such as trading information, real-time electricity prices, and economic analysis. The operational simulation module requires configuration of the grid structure, node parameters, simulation granularity, and reserve model, including algorithm call nodes and software parameter interaction. The power trading market simulation module includes a two-stage process, day-ahead and intraday, as well as modules for market parameters, a bidding and clearing model, and a results presentation model. The day-ahead bidding and clearing program calculates the subject's declared parameters and clearing results, including the classification of the electric energy market and the frequency regulation market and the corresponding calculation indicators; the intraday real-time rolling calculation program includes the bidding and clearing and operation simulation rules for each period, the overall market settlement rules, etc.; the disturbance program supports the calculation of disturbance parameters and operation simulation stage clearing. The specific operation process is as follows Figure 3 shown.

[0040] The specific technical solutions are as follows:

[0041] The simulation platform for distributed hybrid cloud energy storage participating in the power trading market according to the embodiment of the present invention has the following specific architecture: Figure 2 As shown, the platform integrates two core functional modules: operation simulation and market simulation. It is designed to comprehensively evaluate the reliability and economic efficiency of distributed hybrid energy storage systems in new power systems. Through highly integrated and collaborative technical means, the platform provides strong technical support and decision-making basis for power grid companies, energy storage operators, and related research institutions. Specifically, it includes:

[0042] The platform is built on a cloud architecture using cloud computing technology, supporting distributed computing and storage, ensuring efficient and stable operation under highly concurrent simulation tasks. Furthermore, the platform supports dynamic resource expansion to meet simulation needs of varying scales and complexities.

[0043] The platform features a modular design and consists of two core components: an operation simulation module and a market simulation module. The operation simulation module focuses on simulating the operation of distributed hybrid energy storage systems in distribution networks, including key elements such as grid topology construction, operation simulation of energy storage / load / distributed energy, demand response mechanisms, power trading, and real-time electricity prices. The market simulation module focuses on simulating the trading behavior of energy storage systems in the power market, including economic simulation functions such as day-ahead bidding, intraday real-time rolling calculations, and market disturbance response.

[0044] Data interaction and collaboration: The two functional modules are seamlessly connected through data interfaces, ensuring that the energy storage planning results obtained from the operation simulation can be fed back to the market simulation module in real time, providing data support for the formulation of market bidding strategies. At the same time, the output results of the market simulation module can also provide feedback to the operation simulation module, further optimizing the operation strategy of the energy storage system.

[0045] Highly customizable and visual, the platform supports users to customize simulation scenarios according to specific needs, including grid topology, energy storage system configuration, market rules, etc. At the same time, it provides an intuitive visual interface to display key data, charts, and analysis results during the simulation process, making it easier for users to understand and evaluate the simulation results. In addition, users can input basic topology parameters and algorithm parameters of the simulation platform through the visual interface;

[0046] Intelligent analysis and optimization: The platform has multiple built-in advanced algorithms and models, enabling intelligent analysis and optimization of energy storage system operating strategies and market bidding strategies. These advanced algorithms automatically adjust simulation parameters to improve accuracy and efficiency.

[0047] like Figure 3 As shown, the running simulation module includes building a grid form, node parameters, simulation granularity, energy storage model, etc., including algorithm call nodes and software parameter interactions.

[0048] Grid construction and parameter setting: supports calling existing grids and parameters from the database, and also supports user-defined grid topology, including but not limited to user input and modification of node parameters, line parameters, load parameters and other parameters;

[0049] Provides the function of setting different simulation time granularity. Users can freely adjust the time step or time resolution during the simulation process according to the complexity of the specific application scenario and the requirements for result accuracy, thereby ensuring the accuracy and reliability of the results;

[0050] Energy storage system simulation: building detailed energy storage models, including electrical energy storage models, thermal energy storage models, hydrogen energy storage models, and coupling models between them. Simulating key characteristics of these energy storage systems, such as the charging and discharging process, efficiency loss, and lifespan degradation;

[0051] Demand response and power trading: integrating demand response mechanisms to simulate user-side responses to electricity prices and power supply reliability;

[0052] like Figure 4 and Figure 5 As shown, the market simulation module includes a two-stage process of the day before and the day after, as well as modules such as market parameters, bidding clearing model, and result display model.

[0053] Day-ahead bidding and clearing builds a day-ahead bidding and clearing model, supporting classified calculations for the electricity energy market and the frequency regulation market. Users can enter the declared parameters, and the system automatically calculates the clearing results and displays the relevant calculation results;

[0054] Real-time rolling calculation within the day supports bid-clearing calculations for each period within the day. The optimization results of the previous period are used as input for the next stage of calculation, and the bidding strategy and market clearing results are dynamically adjusted based on real-time market information and simulation results.

[0055] Market disturbance and risk assessment: Built-in disturbance program supports simulation and calculation of the market under various disturbance environments. At the same time, it provides risk assessment function to evaluate the benefits and risks of energy storage systems under different market conditions.

[0056] The results display model provides a rich set of results display models and report generation tools, including chart display, data export, and report customization. Users can generate detailed simulation reports and analysis results according to their needs.

[0057] In actual applications, select a calculation example and click it to enter the topology building interface. Voltage source basic properties include basic information. This includes the voltage source name, maximum and minimum node voltage values, actual node voltage values, and node injected active and reactive power. Users can modify and adjust basic property values ​​as needed and click OK to successfully edit. Line basic properties include basic information. This includes resistance, reactance, conductance, susceptance, and maximum line capacity. Users can modify and adjust basic property values ​​as needed and click OK to successfully edit. Photovoltaic basic properties include basic information. This includes the photovoltaic name and output curve. The photovoltaic curve includes the curve entry method, data source, and curve display. Users can modify and adjust basic property values ​​as needed and click OK to successfully edit. Wind turbine basic properties include basic information. This includes the wind turbine name and output curve. The wind turbine curve includes the curve entry method, data source, and curve display. Users can modify and adjust basic property values ​​as needed and click OK to successfully edit. Load basic properties include basic information. Basic information includes load name, electrical load data, and thermal load data; load curves include curve entry method, data source, and curve display. Users can modify and adjust basic attribute values ​​as needed. Click OK to successfully edit. General basic attributes include basic information. Basic information includes general unit name, output upper and lower limits, ramp rate upper and lower limits, and output curve. Derailment unit curves include curve entry method, data source, and curve display. Users can modify and adjust basic attribute values ​​as needed. Click OK to successfully edit.

[0058] After entering and saving the energy storage parameters, the user clicks Run to begin the simulation. The simulation results display an overview, energy storage planning results, node information, and branch information. Select the energy storage parameter settings and enter the specific parameters. Once the system is set up, click Run to begin the simulation. After the simulation is complete, the user can perform market simulation and output the results.

[0059] Method Example

[0060] According to an embodiment of the present invention, a method for implementing a simulation platform for distributed hybrid cloud energy storage to participate in the power trading market is provided, which is used for the above-mentioned simulation platform. Figure 6 Schematic diagram of a method for implementing a simulation platform for distributed hybrid cloud energy storage participating in a power trading market according to an embodiment of the present invention. Figure 6 As shown, the implementation method of the simulation platform for distributed hybrid cloud energy storage participating in the power trading market according to an embodiment of the present invention specifically includes:

[0061] Step S601, setting the operation simulation parameters of the operation simulation module and the market simulation parameters of the market simulation module according to the user's input; specifically, providing a configuration interface for the operation simulation parameters and the market simulation parameters through a visual interface, wherein the operation simulation parameters specifically include: power grid topology, distributed hybrid cloud energy storage system configuration, and simulation time granularity; the market simulation parameters specifically include: market parameters, market rules and simulation time granularity.

[0062] Step S602: Based on the operation simulation parameters and the energy storage system operation strategy, the operation status of the distributed hybrid energy storage system in the distribution network is simulated using a pre-built energy storage model, energy storage planning results are obtained and displayed to the user, and the energy storage planning results are sent to the market simulation module through a data interface; further, the energy storage system operation strategy is optimized according to the market simulation results;

[0063] Step S602 specifically includes: simulating the trading behavior of the distributed hybrid energy storage system in the power market based on the market simulation parameters and market bidding strategy, realizing the construction of the grid topology, the operation simulation of energy storage / load / distributed energy, the demand response mechanism, power trading, real-time electricity price simulation, and the simulation of the user-side response behavior to electricity price and power supply reliability. Specifically: calling the existing grid architecture and parameters from the database, and providing an interface for users to customize the grid topology structure, enabling users to input and modify node parameters, line parameters, and load parameters;

[0064] Freely adjust the time step and / or time resolution during simulation based on user input, depending on the complexity of the specific application scenario and the requirements for result accuracy;

[0065] Constructing detailed energy storage models to simulate key characteristics of these energy storage systems, including the charging and discharging process, efficiency loss, and lifespan degradation. Specifically, the energy storage models include: an electrical energy storage model, a thermal energy storage model, a hydrogen energy storage model, and the coupling models between them.

[0066] Integrate demand response mechanism to simulate user-side response behavior to electricity prices and power supply reliability.

[0067] In step S603, based on the market simulation parameters and market bidding strategy, a bidding-clearing model is used to simulate the trading behavior of the distributed hybrid energy storage system in the electricity market during the day ahead and in the second phase. Market simulation results are obtained and displayed to the user. The market simulation results are transmitted to the operation simulation module via the data interface. Furthermore, the market bidding strategy is optimized based on the energy storage planning results.

[0068] Step S603 specifically includes: simulating the trading behavior of the distributed hybrid energy storage system in the power market based on the market simulation parameters and market bidding strategy, realizing the economic simulation functions of day-ahead bidding, intraday real-time rolling calculation, and market disturbance response. Specifically: constructing a day-ahead bidding clearing model, performing classified calculations for the electric energy market and the frequency regulation market, automatically calculating the clearing results based on the declared parameters entered by the user, and displaying the relevant calculation results;

[0069] Real-time rolling calculations are performed intraday to conduct bidding and clearing calculations for each period of the day. The optimization results of the previous period are used as input for the next stage of calculations. The bidding strategy and market clearing results are dynamically adjusted based on real-time market information and simulation results.

[0070] The built-in perturbation program simulates and calculates the market under various perturbation environments and provides risk assessment functions to evaluate the benefits and risks of energy storage systems under different market conditions.

[0071] Through the result display model and report generation tools, chart display, data export and report customization are carried out, and detailed simulation reports and analysis results are generated according to user needs.

[0072] In summary, the embodiments of the present invention meet the relevant business needs of power companies, support distributed hybrid energy storage to participate in supporting real business needs such as distribution network operation simulation and power market transaction simulation, and solve the problem of the lack of simulation tools for topological models and visualization of simulation results in China.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than 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 they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A simulation platform for distributed hybrid cloud energy storage participating in the electricity trading market, characterized by: Built using cloud computing technology, it supports distributed computing and storage, as well as dynamic resource expansion. The simulation platform specifically includes: A configuration module, used to set the operation simulation parameters of the operation simulation module and the market simulation parameters of the market simulation module according to the user's input; An operation simulation module is used to simulate the operation status of the distributed hybrid energy storage system in the distribution network through a pre-built energy storage model based on the operation simulation parameters and the energy storage system operation strategy, obtain energy storage planning results and display them to the user, and send the energy storage planning results to the market simulation module through a data interface; The market simulation module is used to simulate the trading behavior of the distributed hybrid energy storage system in the power market in two stages within the day ahead through a bidding clearing model based on the market simulation parameters and market bidding strategy, obtain market simulation results and display them to the user, and transmit the market simulation results to the operation simulation module through the data interface; the market simulation module is specifically used to: Based on the market simulation parameters and market bidding strategy, the trading behavior of the distributed hybrid energy storage system participating in the power market is simulated to realize the economic simulation functions of day-ahead bidding, intraday real-time rolling calculation, and market disturbance response. Specifically, a day-ahead bidding clearing model is constructed to perform classified calculations for the electricity energy market and the frequency regulation market. According to the declared parameters input by the user, the clearing results are automatically calculated and the relevant calculation results are displayed. Intraday real-time rolling calculation is performed to perform bidding clearing calculations for each period of the day. The optimization results of the previous period are used as input for the next stage of calculation. According to the real-time market information and the operation simulation results, the bidding strategy and market clearing results are dynamically adjusted. Through the built-in disturbance program, the market is simulated and calculated under various disturbance environments, and a risk assessment function is provided to evaluate the benefits and risks of the energy storage system under different market conditions. Through the result display model and report generation tool, chart display, data export and report customization are performed, and detailed simulation reports and analysis results are generated according to user needs.

2. The simulation platform according to claim 1, characterized in that: The operation simulation module is further used to: optimize the energy storage system operation strategy according to the market simulation results; The market simulation module is further used to optimize the market bidding strategy according to the energy storage planning result.

3. The simulation platform according to claim 1, characterized in that: The configuration module is specifically used to provide a configuration interface for operation simulation parameters and market simulation parameters through a visual interface, wherein the operation simulation parameters specifically include: power grid topology, distributed hybrid cloud energy storage system configuration, and simulation time granularity; the market simulation parameters specifically include: market parameters, market rules and simulation time granularity.

4. The simulation platform according to claim 1, characterized in that: The operation simulation module is specifically used for: Based on the market simulation parameters and market bidding strategy, the trading behavior of the distributed hybrid energy storage system participating in the power market is simulated to realize the grid topology construction, operation simulation of energy storage / load / distributed energy, demand response mechanism, electricity trading, real-time electricity price simulation and simulation of the user side's response behavior to electricity price and power supply reliability.

5. The simulation platform according to claim 4, characterized in that: The operation simulation module is specifically used for: Call the existing power grid architecture and parameters from the database and provide an interface for users to customize the power grid topology structure, enabling users to input and modify node parameters, line parameters and load parameters; Freely adjust the time step and / or time resolution during simulation based on user input, depending on the complexity of the specific application scenario and the requirements for result accuracy; Constructing detailed energy storage models to simulate key characteristics of these energy storage systems, including the charging and discharging process, efficiency loss, and lifespan degradation. Specifically, the energy storage models include: an electrical energy storage model, a thermal energy storage model, a hydrogen energy storage model, and the coupling models between them. Integrate demand response mechanism to simulate user-side response behavior to electricity prices and power supply reliability.

6. A method for implementing a simulation platform for distributed hybrid cloud energy storage to participate in the power trading market, characterized in that: For use in a simulation platform according to any one of claims 1 to 5, the method specifically comprises: Setting the operation simulation parameters of the operation simulation module and the market simulation parameters of the market simulation module according to the user's input; Based on the operation simulation parameters and the energy storage system operation strategy, the operation status of the distributed hybrid energy storage system in the distribution network is simulated through a pre-built energy storage model, the energy storage planning results are obtained and displayed to the user, and the energy storage planning results are sent to the market simulation module through the data interface; Based on the market simulation parameters and market bidding strategy, a bidding clearing model is used to simulate the trading behavior of the distributed hybrid energy storage system participating in the power market in two stages within the day before, and a market simulation result is obtained and displayed to the user, and the market simulation result is transmitted to the operation simulation module through the data interface; Based on the market simulation parameters and market bidding strategy, simulating the trading behavior of the distributed hybrid energy storage system participating in the power market in two stages within the day before through the bidding clearing model, obtaining the market simulation results and displaying them to the user, and transmitting the market simulation results to the operation simulation module through the data interface specifically includes: Build a day-ahead bidding clearing model to perform classified calculations for the energy market and frequency regulation market. Automatically calculate the clearing results based on the declared parameters entered by the user and display the relevant calculation results. Real-time rolling calculations are performed intraday to conduct bidding and clearing calculations for each period of the day. The optimization results of the previous period are used as input for the next stage of calculations. The bidding strategy and market clearing results are dynamically adjusted based on real-time market information and simulation results. The built-in perturbation program simulates and calculates the market under various perturbation environments and provides risk assessment functions to evaluate the benefits and risks of energy storage systems under different market conditions. Through the result display model and report generation tools, chart display, data export and report customization are carried out, and detailed simulation reports and analysis results are generated according to user needs.

7. The method according to claim 6, characterized in that The method further comprises: Optimizing the energy storage system operation strategy according to the market simulation results; The market bidding strategy is optimized according to the energy storage planning results.

8. The method according to claim 6, characterized in that Based on the operation simulation parameters and the energy storage system operation strategy, the operation status of the distributed hybrid energy storage system in the distribution network is simulated by the pre-built energy storage model, specifically including: Setting the operation simulation parameters of the operation simulation module and the market simulation parameters of the market simulation module according to the user's input; Call the existing power grid architecture and parameters from the database and provide an interface for users to customize the power grid topology structure, enabling users to input and modify node parameters, line parameters and load parameters; Freely adjust the time step and / or time resolution during simulation based on user input, depending on the complexity of the specific application scenario and the requirements for result accuracy; Constructing detailed energy storage models to simulate key characteristics of these energy storage systems, including the charging and discharging process, efficiency loss, and lifespan degradation. Specifically, the energy storage models include: an electrical energy storage model, a thermal energy storage model, a hydrogen energy storage model, and the coupling models between them. Integrate demand response mechanism to simulate user-side response behavior to electricity prices and power supply reliability.

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