A method and system for evaluating power system operation under multi-agent bidding participation

Abstract

The application belongs to the technical field of power systems and simulation deduction, and discloses a power system operation evaluation method and system under multi-element subject bidding participation. The application takes year, quarter, month, day and hour as time dimensions, statistically calculates the average power generation of each type of operation subject, and constructs a multi-time scale power balance analysis model. The maximum load time and the minimum load time in each time scale are identified, the ratio of the output difference of each type of subject at the load peak and valley time to the total load change value is calculated, and the balance contribution degree is obtained. The degree price of each type of subject under different time scales is statistically calculated. Based on the degree price of the new energy subject, the value capture index is obtained. Based on the above multi-dimensional analysis results, the power balance distribution graph, the balance contribution degree proportion graph, the degree price trend graph and the value capture ability comparison graph are generated through the visualization module, the comprehensive evaluation and intuitive presentation of the system operation effect are realized, and the technical problems existing in the prior art are solved.

Description

Technical Field

[0001] This invention belongs to the fields of power system and simulation technology, specifically relating to a power system operation evaluation method and system with multi-entity competitive bidding participation. Background Technology

[0002] With the deepening of power system reform, the participants in the system are becoming increasingly diversified, with conventional energy sources, new energy sources, energy storage, and load-side entities all competing for power. Especially under the background of new power system construction, the proportion of new energy installed capacity continues to increase, and the volatility and uncertainty of its output have a profound impact on power system operation. How to scientifically evaluate the system's operational effectiveness under multi-entity bidding, quantify the contribution of each type of entity to power balance, and assess the changing trends of the cost per kilowatt-hour and the value capture capabilities of different entities have become important supporting requirements for power system mechanism design, strategy formulation, and entity decision-making.

[0003] Traditional power system evaluation methods often focus on a single entity type or a single time scale, and are frequently limited to quantity and price analysis. This means they describe system results by statistically analyzing the transaction volume and prices of various entities, failing to comprehensively reflect the operational characteristics and interactions of multiple entities across different time dimensions. Existing technologies lack a systematic evaluation framework for the power generation, balance contribution, cost per kilowatt-hour, and value capture capabilities of various entities across multiple time scales. Furthermore, they lack objective methods for quantifying operational effectiveness through indicator calculations. This fails to provide comprehensive quantitative technical support for optimizing power system dispatch and control strategies and promoting collaborative operation among multiple entities, leading to technical problems such as insufficient accuracy in power system dispatch decisions, low renewable energy integration rates, and difficulty in ensuring system operational stability. Summary of the Invention

[0004] The purpose of this invention is to address the problem of existing technologies lacking a systematic and quantitative evaluation system for power system operation, which relies on a single subject and time scale. This invention provides a method and system for evaluating power system operation with the participation of multiple subjects through competitive bidding.

[0005] To achieve the above objectives, the present invention employs the following technical solution: The present invention proposes a power system operation evaluation method with multi-entity bidding participation, comprising the following steps: Obtain power system operation data of various types of operating entities within the evaluation period of the target power system, and statistically analyze the average power generation and unit price of electricity of each type of operating entity based on multiple different time dimensions and the power system operation data. A multi-timescale power balance analysis model is constructed based on the average power generation. Based on the multi-timescale power balance analysis model, different load levels at each time scale are obtained. Based on the changes of each operating entity at different load levels and the total load change, the balance contribution is obtained. Based on the statistical results of the unit price of electricity and the overall average unit price of electricity in the power system, the value capture index of new energy entities is calculated. Based on the output results of the multi-time-scale power balance analysis model, the balance contribution, the unit price of electricity, and the value capture index, the power system operation evaluation is realized.

[0006] Preferably, the multi-timescale power balance analysis model is specifically as follows:

[0007] in, Indicates the first Class subject in time scale Average power generation under Time scale The number of statistical periods below For the first Class subject in time period Electricity generation, Indicates time period Belongs to the time scale The statistical scope.

[0008] Preferably, the multi-timescale power balance analysis model obtains the load level times at different time scales, and obtains the balance contribution based on the changes of each operating entity at different load level times and the total load change value, specifically as follows: The different load levels include the maximum load time and the minimum load time within each time scale; The balance contribution rate characterizes the degree of response of a certain type of operating entity's output change to the change in the total load of the power system. It is the ratio of the output change of that type of operating entity between the maximum load time and the minimum load time to the total load change of the power system between the same two times, expressed as follows:

[0009] in, Indicates the first Class subject in Balanced contribution over time scales for The output of this type of entity at the moment of maximum load within a time scale. for The output of this type of entity at the moment of minimum load within a time scale. The maximum load within the time scale t is the maximum load. The minimum load within the time scale t is the minimum load.

[0010] Preferably, when the balance contribution is greater than 0, it indicates that the output of this type of entity increases during peak load periods, playing a positive regulating role in the system balance; when the balance contribution is less than 0, it indicates that the output of this type of entity decreases during peak load periods, exhibiting anti-peak shaving characteristics.

[0011] Preferably, the unit price per kilowatt-hour is specifically: The various time dimensions are year, quarter, month, day, and hour; the various types of operating entities include coal mining machinery, nuclear power, gas turbines, wind power, photovoltaic power, and energy storage. The unit price per kilowatt-hour for coal-fired power, nuclear power, gas-fired power, wind power, photovoltaic power, and energy storage is presented as follows:

[0012] in, Indicates the first Class subject in time scale The unit price of electricity is as follows: For time period The amount of electricity traded. For time period The transaction price; for different time scales, the corresponding unit price of electricity is calculated to form a time series of unit price of electricity, which is used to analyze the multi-scale change trend of unit price of electricity.

[0013] Preferably, the calculation of the value capture index of new energy entities based on the statistical results of the electricity price per kilowatt-hour and the overall average electricity price per kilowatt-hour of the power system is specifically as follows:

[0014] in, Represents the main body of new energy In time scale The value capture index below The unit price per kilowatt-hour for this entity. This represents the total number of subject types participating in the comparison.

[0015] Preferably, the power system operation evaluation method with multi-stakeholder bidding proposed in this invention further includes the following steps: Based on the output results of the multi-timescale power balance analysis model, balance contribution, unit price of electricity, and value capture index, a comprehensive evaluation result of power system operation covering four dimensions: power balance, balance contribution, unit price of electricity, and value capture is constructed. It supports switching analysis of five time scales: year, quarter, month, day, and hour, and provides visualization output through power balance distribution map, balance contribution percentage map, unit price of electricity trend map, and value capture capability comparison map. Based on the comprehensive evaluation results, differentiated operation and adjustment instructions are generated for different types of operating entities, including coal-fired power, nuclear power, gas turbine, wind power, photovoltaic, energy storage, and interconnection lines. Based on the adjustment of demand, the corresponding operating strategies of the operating entities in the power system are adjusted to improve the accuracy of power system dispatching decisions, increase the renewable energy absorption rate, or improve the stability of power system operation.

[0016] This invention proposes a power system operation evaluation system with multi-stakeholder bidding participation, comprising: The data acquisition and statistics module is used to acquire power system operation data of various types of operating entities in the target power system during the evaluation period. Based on multiple different time dimensions, the module combines the power system operation data to calculate the average power generation and unit price of electricity for each type of operating entity. The power balance analysis module is used to construct a multi-timescale power balance analysis model based on the average power generation, obtain different load level times within each time scale based on the multi-timescale power balance analysis model, and then calculate the balance contribution based on the changes of each operating entity at different load level times and the total load change value. The system operation evaluation module is used to calculate the value capture index of new energy entities based on the statistical results of the unit price of electricity and the overall average unit price of electricity in the power system. Then, based on the output results of the multi-time scale power balance analysis model, the balance contribution, the unit price of electricity, and the value capture index, the system operation evaluation of the target power system is realized.

[0017] Preferably, the multi-timescale power balance analysis model is specifically as follows:

[0018] in, Indicates the first Class subject in time scale Average power generation under Time scale The number of statistical periods below For the first Class subject in time period Electricity generation, Indicates time period Belongs to the time scale The statistical scope.

[0019] Preferably, the multi-timescale power balance analysis model obtains the load level times at different time scales, and obtains the balance contribution based on the changes of each operating entity at different load level times and the total load change value, specifically as follows: The different load levels include the maximum load time and the minimum load time within each time scale; The balance contribution rate characterizes the degree of response of a certain type of operating entity's output change to the change in the total load of the power system. It is the ratio of the output change of that type of operating entity between the maximum load time and the minimum load time to the total load change of the power system between the same two times, expressed as follows:

[0020] in, Indicates the first Class subject in Balanced contribution over time scales for The output of this type of entity at the moment of maximum load within a time scale. for The output of this type of entity at the moment of minimum load within a time scale. The maximum load within the time scale t is the maximum load. The minimum load within the time scale t is the minimum load.

[0021] Preferably, the unit price per kilowatt-hour is specifically: The various time dimensions are year, quarter, month, day, and hour; the various types of operating entities include coal mining machinery, nuclear power, gas turbines, wind power, photovoltaic power, and energy storage. The unit price per kilowatt-hour for coal-fired power, nuclear power, gas-fired power, wind power, photovoltaic power, and energy storage is presented as follows:

[0022] in, Indicates the first Class subject in time scale The unit price of electricity is as follows: For time period The amount of electricity traded. For time period The transaction price; for different time scales, the corresponding unit price of electricity is calculated to form a time series of unit price of electricity, which is used to analyze the multi-scale change trend of unit price of electricity.

[0023] Preferably, the calculation of the value capture index of new energy entities based on the statistical results of the electricity price per kilowatt-hour and the overall average electricity price per kilowatt-hour of the power system is specifically as follows:

[0024] in, Represents the main body of new energy In time scale The value capture index below The unit price per kilowatt-hour for this entity. This represents the total number of subject types participating in the comparison.

[0025] A terminal device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of a power system operation evaluation method with multi-entity competitive bidding participation.

[0026] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of a power system operation evaluation method with multi-entity competitive bidding participation.

[0027] Compared with the prior art, the present invention has the following beneficial effects: This invention proposes a method for evaluating the operation of a power system under multi-entity competitive bidding. First, this method covers all types of operating entities within the target power system, overcoming the limitations of traditional methods that focus only on a single entity type, and comprehensively reflects the operational characteristics of multiple entities. Second, it employs multiple different time dimensions for statistical analysis and constructs a multi-time-scale power balance analysis model based on the statistically obtained average power generation, solving the shortcomings of traditional methods with only a single time scale and fully presenting the operational patterns and interactions of each entity under different time dimensions. Third, based on traditional quantity and price statistics, it introduces two core quantitative indicators: balance contribution and value capture index, respectively quantifying the regulatory contribution of each operating entity in power balance and the value acquisition capability of new energy entities in system competition, overcoming the limitations of traditional methods that are limited to superficial analysis based solely on transaction volume and price statistics. Finally, it integrates the outputs of the multi-time-scale power balance analysis results, balance contribution, unit price per kilowatt-hour, and value capture index to form an integrated comprehensive evaluation system. This achieves a systematic quantitative evaluation of the power system's operational effectiveness under multi-entity competitive bidding, providing comprehensive quantitative support for system mechanism optimization and entity participation strategy formulation.

[0028] This invention proposes a power system operation evaluation system with multi-stakeholder bidding participation. By dividing the system into a data acquisition and statistics module, a power balance analysis module, and a system operation evaluation module, it evaluates the operation of the target power system based on the output results of the multi-timescale power balance analysis model, balance contribution, unit price per kilowatt-hour, and value capture index. The modular approach ensures that each module is independent, facilitating unified management of all modules. Attached Figure Description

[0029] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 This is a flowchart of the power system operation evaluation method under multi-entity competitive bidding, as described in this invention.

[0031] Figure 2 This is a detailed flowchart of the power system operation evaluation method of the present invention.

[0032] Figure 3 The present invention uses an area map to show the power generation composition of various types of entities at different time scales.

[0033] Figure 4 The present invention uses a bar chart to show the proportion of the balance contribution of each type of subject at different time scales.

[0034] Figure 5 The present invention uses bar charts or line charts to compare the value capture index of different new energy entities.

[0035] Figure 6 This is a diagram of a power system operation evaluation system under multi-entity competitive bidding, as described in this invention.

[0036] Figure 7 This is a schematic diagram of the structure of an electronic device according to the present invention. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0038] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0039] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0040] The present invention will now be described in further detail with reference to the accompanying drawings: Example 1 Based on the problems existing in the background technology, this invention aims to provide a power system operation evaluation method with multi-entity competitive bidding participation. It achieves comprehensive evaluation from four dimensions—energy balance, balance contribution, cost per kilowatt-hour, and value capture—covering five time scales: year, quarter, month, day, and hour. It encompasses all types of operating entities, including coal-fired power plants, nuclear power plants, gas-fired power plants, wind power plants, photovoltaic power plants, energy storage systems, and interconnection lines. Through a clear quantitative indicator system and visual output, it comprehensively and objectively reflects the power system's operational effectiveness. This method constructs a multi-dimensional, multi-time-scale, and multi-entity type evaluation indicator system to achieve a systematic quantitative assessment of the power system's operational effectiveness. The overall technical solution includes a data acquisition module, an energy balance analysis module, a balance contribution analysis module, a cost per kilowatt-hour analysis module, a value capture analysis module, and a visualization output module. These modules work collaboratively to form a complete evaluation process. First, the data acquisition module obtains basic data on hourly output, traded electricity volume, traded prices, and operating costs for various types of operating entities (including coal-fired power, nuclear power, gas-fired power, wind power, photovoltaic power, energy storage, and inter-provincial interconnections) within the target power system during the evaluation period. The data is then cleaned, normalized, and time-series aligned to form a standardized basic dataset. Next, the average power generation of each type of system entity is statistically analyzed using year, quarter, month, day, and hour as time dimensions, constructing a multi-time-scale power balance analysis model. Finally, the peak and minimum load times within each time scale are identified, and the output of each type of entity at peak and valley load times is calculated. The ratio of the difference to the total system load change yields the balance contribution; the unit price of electricity for each type of entity at different time scales is statistically analyzed to determine its changing trends; the ratio of the unit price of electricity for renewable energy entities to the average unit price of electricity for all generating units is calculated to obtain the value capture index, assessing the value capture capability of renewable energy in power system competition; finally, based on the above multi-dimensional analysis results, a visualization module generates charts such as a power balance distribution map, a balance contribution ratio map, a unit price trend map, and a value capture capability comparison map, achieving a comprehensive evaluation and intuitive presentation of the system's operating performance. This demonstrates that the power system is a new type of power system with a high proportion of renewable energy entering the market. The following section combines... Figure 1 The method is described as follows: S1. Obtain power system operation data of various types of operating entities in the target power system during the evaluation period. Based on multiple different time dimensions, combine the power system operation data to calculate the average power generation and unit price of electricity for each type of operating entity. The multi-timescale power balance analysis model is specifically as follows:

[0041] in, Indicates the first Class subject in time scale Average power generation under Time scale The number of statistical periods below For the first Class subject in time period Electricity generation, Indicates time period Belongs to the time scale The statistical scope.

[0042] The unit price per kilowatt-hour is as follows: The various time dimensions are year, quarter, month, day, and hour; the various types of operating entities include coal mining machinery, nuclear power, gas turbines, wind power, photovoltaic power, and energy storage. The unit price per kilowatt-hour for coal-fired power, nuclear power, gas-fired power, wind power, photovoltaic power, and energy storage is presented as follows:

[0043] in, Indicates the first Class subject in time scale The unit price of electricity is as follows: For time period The amount of electricity traded. For time period The transaction price; for different time scales, the corresponding unit price of electricity is calculated to form a time series of unit price of electricity, which is used to analyze the multi-scale change trend of unit price of electricity.

[0044] S2. Construct a multi-timescale power balance analysis model based on the average power generation. Based on the multi-timescale power balance analysis model, obtain the different load levels at each time scale. Based on the changes of each operating entity at different load levels and the total load change, obtain the balance contribution. The multi-timescale power balance analysis model obtains the load level at different times within each time scale. Based on the changes in load level of each operating entity at different times and the total load change, the balance contribution is obtained, specifically: The different load levels include the maximum load time and the minimum load time within each time scale; The balance contribution rate characterizes the degree of response of a certain type of operating entity's output change to the change in the total load of the power system. It is the ratio of the output change of that type of operating entity between the maximum load time and the minimum load time to the total load change of the power system between the same two times, expressed as follows:

[0045] in, Indicates the first Class subject in Balanced contribution over time scales for The output of this type of entity at the moment of maximum load within a time scale. for The output of this type of entity at the moment of minimum load within a time scale. The maximum load within the time scale t is the maximum load. The minimum load within the time scale t is the minimum load.

[0046] When the balance contribution is greater than 0, it indicates that the output of this type of entity increases during peak load periods, playing a positive regulating role in the system balance; when the balance contribution is less than 0, it indicates that the output of this type of entity decreases during peak load periods, exhibiting anti-peak shaving characteristics.

[0047] S3. Based on the statistical results of the unit price of electricity and the overall average unit price of electricity in the power system, calculate the value capture index of the new energy subject. Based on the output results of the multi-time scale power balance analysis model, the balance contribution, the unit price of electricity, and the value capture index, realize the power system operation evaluation.

[0048] Based on the statistical results of the electricity price per kilowatt-hour and the overall average electricity price per kilowatt-hour of the power system, the value capture index of new energy entities is calculated as follows:

[0049] in, Represents the main body of new energy In time scale The value capture index below The unit price per kilowatt-hour for this entity. This represents the total number of subject types participating in the comparison.

[0050] Preferably, the power system operation evaluation method with multi-stakeholder bidding proposed in this invention further includes the following steps: Based on the output results of the multi-timescale power balance analysis model, balance contribution, unit price of electricity, and value capture index, a comprehensive evaluation result of power system operation covering four dimensions: power balance, balance contribution, unit price of electricity, and value capture is constructed. It supports switching analysis of five time scales: year, quarter, month, day, and hour, and provides visualization output through power balance distribution map, balance contribution percentage map, unit price of electricity trend map, and value capture capability comparison map. Based on the comprehensive evaluation results, differentiated operation and adjustment instructions are generated for different types of operating entities, including coal-fired power, nuclear power, gas turbine, wind power, photovoltaic, energy storage, and interconnection lines. Based on the adjustment of demand, the corresponding operating strategies of the operating entities in the power system are adjusted to improve the accuracy of power system dispatching decisions, increase the renewable energy absorption rate, or improve the stability of power system operation.

[0051] The following is combined with Figures 2 to 5 The method is described with examples: Step 1: Data Acquisition and Preprocessing The system collects operational data of the target power system during the evaluation period, including hourly output sequences of various types of operating entities (coal-fired power, nuclear power, gas turbine power, wind power, photovoltaic power, energy storage, and interconnection lines). Hourly transaction volume Hourly transaction price Data includes operating costs, etc. The collected data undergoes outlier removal, missing value imputation, and normalization to form a standardized basic dataset.

[0052] Step 2: Multi-timescale charge balance analysis The average power generation of various types of operating entities was statistically analyzed using year, quarter, month, day, and hour as time dimensions, and a multi-time-scale power balance analysis model was constructed. The calculation formula is as follows:

[0053] in, Indicates the first Class subject in time scale Average power generation under Time scale The number of statistical periods below For the first Class subject in time period Electricity generation, Indicates time period Belongs to the time scale The statistical scope.

[0054] In practice, for annual statistics, T is taken as 12 months of the year. =365 or 8760; for quarterly statistics, T is taken as 3 months of the quarter, N T This represents the total number of hours in the quarter, and so on.

[0055] Figure 3 Area maps are used to display the power generation composition of various types of entities at different time scales, intuitively reflecting the power balance structure.

[0056] Step 3: Balanced Contribution Analysis Calculate the proportion of adjustment contribution of each type of operating entity in net load fluctuations, and statistically analyze the balance contribution according to different time scales of hour, day, month, quarter, and year. The calculation formula is as follows:

[0057] in, Indicates the first Class subject in Balanced contribution over time scales for The output of this type of entity at the moment of maximum load within a time scale. for The output of this type of entity at the moment of minimum load within a time scale. The maximum load within the time scale t is the maximum load. The minimum load within the time scale t is the minimum load.

[0058] when When the value is greater than 0, it indicates that this type of entity increases its output during peak load periods, playing a positive regulatory role in system balance; when... When the value is less than 0, it indicates that the output of this type of entity decreases during peak load periods, exhibiting anti-peak shaving characteristics.

[0059] Figure 4 A bar chart is used to display the proportion of the balance contribution of each type of subject at different time scales, which intuitively reflects the role of each type of subject in the system regulation.

[0060] Step 4: Trend Analysis of Price Per kilowatt-hour The unit price per kilowatt-hour for coal-fired power, nuclear power, gas-fired power, wind power, photovoltaic power, and energy storage is statistically analyzed using year, quarter, month, day, and hour as time dimensions, and their changing trends are analyzed. The calculation formula is as follows:

[0061] in, Indicates the first Class subject in time scale The unit price of electricity is as follows: For time period The amount of electricity traded. For time period The transaction price; for different time scales, the corresponding unit price of electricity is calculated to form a time series of unit price of electricity, which is used to analyze the multi-scale change trend of unit price of electricity.

[0062] Step 5: Power Asset Value Capture Analysis The ratio of the unit price of electricity for renewable energy sources such as wind power and solar power to the average unit price of electricity for all generating units is used to assess the value capture capability of renewable energy in the power system competition. The calculation formula is as follows:

[0063] in, Represents the main body of new energy In time scale The value capture index below The unit price per kilowatt-hour for this entity. This represents the total number of entities participating in the comparison, including conventional power sources such as coal-fired power, nuclear power, and gas-fired power. A value capture index greater than 100% indicates that the unit price per kilowatt-hour of this new energy entity is higher than the average level of the power system, indicating a strong value capture capability; a value capture index less than 100% indicates a weak value capture capability.

[0064] Figure 5 Use bar charts or line graphs to compare the value capture index of different new energy entities to assess the asset's ability to capture electricity value.

[0065] Based on the above multi-dimensional analysis results, a comprehensive evaluation index system for power system operation is constructed, and the evaluation results are visualized in the form of charts, including power balance distribution chart, balance contribution ratio chart, unit price trend chart, and value capture capability comparison chart.

[0066] Compared with existing technologies, this invention constructs an evaluation system from four dimensions: power balance, balance contribution, cost per kilowatt-hour, and value capture. This overcomes the shortcomings of traditional methods with their single dimension and can comprehensively reflect the operating characteristics of the power system under the participation of multiple stakeholders. It supports switching analysis at five time scales: year, quarter, month, day, and hour, meeting the differentiated needs of different scenarios for time granularity. It can grasp both long-term trends and locate instantaneous anomalies. It covers all types of stakeholders, including coal-fired power, nuclear power, gas turbines, wind power, photovoltaics, energy storage, and interconnection lines, adapting to the diversified development trend of new power system stakeholders. All indicators are defined with clear mathematical formulas to ensure the objectivity and reproducibility of the evaluation results. The results are output in various visualization forms, such as power balance distribution maps, balance contribution ratio maps, cost per kilowatt-hour trend maps, and value capture comparison maps, making it easy for decision-makers to quickly grasp the operating rules of the power system.

[0067] Therefore, the method proposed in this invention has the following advantages: 1) It constructs a comprehensive evaluation index system covering four dimensions: power balance, balance contribution, unit price per kilowatt-hour, and value capture, and enables flexible switching and coupled analysis across five time scales: annual, quarterly, monthly, daily, and hourly. 2) It proposes a quantitative calculation method for balance contribution, linking the output changes of various entities at peak and valley load times with the total system load changes, and designs a modified formula considering the bidirectional charging and discharging characteristics for energy storage. 3) It constructs a power asset value capture index to achieve a quantitative assessment of the operational competitiveness of new energy entities.

[0068] Example 2 This invention proposes a power system operation evaluation system with multi-stakeholder bidding participation, such as... Figure 6 As shown, it includes a data acquisition and statistics module, a power balance analysis module, and a system operation evaluation module; The data acquisition and statistics module is used to acquire power system operation data of various types of operating entities within the evaluation period of the target power system. Based on multiple different time dimensions, it combines the power system operation data to statistically analyze the average power generation and unit price of electricity for each type of operating entity. The multi-timescale power balance analysis model is specifically as follows:

[0069] in, Indicates the first Class subject in time scale Average power generation under Time scale The number of statistical periods below For the first Class subject in time period Electricity generation, Indicates time period Belongs to the time scale The statistical scope.

[0070] The unit price per kilowatt-hour is as follows: The various time dimensions are year, quarter, month, day, and hour; the various types of operating entities include coal mining machinery, nuclear power, gas turbines, wind power, photovoltaic power, and energy storage. The unit price per kilowatt-hour for coal-fired power, nuclear power, gas-fired power, wind power, photovoltaic power, and energy storage is presented as follows:

[0071] in, Indicates the first Class subject in time scale The unit price of electricity is as follows: For time period The amount of electricity traded. For time period The transaction price; for different time scales, the corresponding unit price of electricity is calculated to form a time series of unit price of electricity, which is used to analyze the multi-scale change trend of unit price of electricity.

[0072] The power balance analysis module is used to construct a multi-timescale power balance analysis model based on the average power generation. Based on the multi-timescale power balance analysis model, it obtains the load level times at different time scales. Based on the changes of each operating entity at different load level times and the total load change value, it obtains the balance contribution. The multi-timescale power balance analysis model obtains the load level at different times within each time scale. Based on the changes in load level of each operating entity at different times and the total load change, the balance contribution is obtained, specifically: The different load levels include the maximum load time and the minimum load time within each time scale; The balance contribution rate characterizes the degree of response of a certain type of operating entity's output change to the change in the total load of the power system. It is the ratio of the output change of that type of operating entity between the maximum load time and the minimum load time to the total load change of the power system between the same two times, expressed as follows:

[0073] in, Indicates the first Class subject in Balanced contribution over time scales for The output of this type of entity at the moment of maximum load within a time scale. for The output of this type of entity at the moment of minimum load within a time scale. The maximum load within the time scale t is the maximum load. The minimum load within the time scale t is the minimum load.

[0074] When the balance contribution is greater than 0, it indicates that the output of this type of entity increases during peak load periods, playing a positive regulating role in the system balance; when the balance contribution is less than 0, it indicates that the output of this type of entity decreases during peak load periods, exhibiting anti-peak shaving characteristics.

[0075] The system operation evaluation module is used to calculate the value capture index of new energy entities based on the statistical results of the unit price of electricity and the overall average unit price of electricity in the power system. Based on the output results of the multi-time scale power balance analysis model, the balance contribution, the unit price of electricity, and the value capture index, the power system operation evaluation is realized.

[0076] Based on the statistical results of the electricity price per kilowatt-hour and the overall average electricity price per kilowatt-hour of the power system, the value capture index of new energy entities is calculated as follows:

[0077] in, Represents the main body of new energy In time scale The value capture index below The unit price per kilowatt-hour for this entity. This represents the total number of subject types participating in the comparison.

[0078] Example 3 Please see Figure 7 As shown, the present invention also provides an electronic device 100 for a power system operation evaluation method with the participation of multiple entities in bidding; the electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and capable of running on the at least one processor 102, and at least one communication bus 104.

[0079] The memory 101 can be used to store the computer program 103. The processor 102 implements the steps of the power system operation evaluation method under multi-entity bidding participation described in Embodiment 1 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101. The memory 101 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device 100 (such as audio data), etc. In addition, the memory 101 may include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0080] The at least one processor 102 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. The processor 102 may be a microprocessor or any conventional processor. The processor 102 is the control center of the electronic device 100, connecting various parts of the electronic device 100 via various interfaces and lines.

[0081] The memory 101 in the electronic device 100 stores multiple instructions to implement a power system operation evaluation method under multi-entity competitive bidding, and the processor 102 can execute the multiple instructions to achieve the following: Obtain operational data of various types of operating entities in the target power system during the evaluation period. Based on multiple different time dimensions, combine the power system operation data to statistically analyze the average power generation and unit price of electricity for each type of operating entity. A multi-timescale power balance analysis model is constructed based on the average power generation. Based on the multi-timescale power balance analysis model, different load levels at each time scale are obtained. Based on the changes of each operating entity at different load levels and the total load change, the balance contribution is obtained. Based on the statistical results of the unit price of electricity and the overall average unit price of electricity in the power system, the value capture index of new energy entities is calculated. Based on the output results of the multi-time-scale power balance analysis model, the balance contribution, the unit price of electricity, and the value capture index, the power system operation evaluation is realized.

[0082] Example 4 If the modules / units integrated in the electronic device 100 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0083] 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.

[0084] 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.

[0085] 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.

[0086] 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.

[0087] 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 method for evaluating the operation of a power system under multi-stakeholder bidding, characterized in that, Includes the following steps: Obtain power system operation data of various types of operating entities within the evaluation period of the target power system, and statistically analyze the average power generation and unit price of electricity of each type of operating entity based on multiple different time dimensions and the power system operation data. A multi-timescale power balance analysis model is constructed based on the average power generation. Based on the multi-timescale power balance analysis model, different load levels at each time scale are obtained. Based on the changes of each operating entity at different load levels and the total load change, the balance contribution is obtained. Based on the statistical results of the unit price of electricity and the overall average unit price of electricity in the power system, the value capture index of new energy entities is calculated. Based on the output results of the multi-time-scale power balance analysis model, the balance contribution, the unit price of electricity, and the value capture index, the power system operation evaluation is realized.

2. The power system operation evaluation method under multi-entity competitive bidding as described in claim 1, characterized in that, The multi-timescale power balance analysis model is specifically as follows: in, Indicates the first Class subject in time scale Average power generation under, Time scale The number of statistical periods below For the first Class subject in time period Electricity generation, Indicates time period Belongs to the time scale The statistical scope.

3. The power system operation evaluation method under multi-entity competitive bidding as described in claim 1, characterized in that, The multi-timescale power balance analysis model obtains the load level at different times within each time scale. Based on the changes in load level of each operating entity at different times and the total load change, the balance contribution is obtained, specifically: The different load levels include the maximum load time and the minimum load time within each time scale; The balance contribution rate characterizes the degree of response of a certain type of operating entity's output change to the change in the total load of the power system. It is the ratio of the output change of that type of operating entity between the maximum load time and the minimum load time to the total load change of the power system between the same two times, expressed as follows: in, Indicates the first Class subject in Balance contribution over time scale for The output of this type of entity at the moment of maximum load within a time scale. for The output of this type of entity at the moment of minimum load within a time scale. The maximum load within the time scale t is the maximum load. The minimum load within the time scale t is the minimum load.

4. The power system operation evaluation method under multi-entity competitive bidding as described in claim 3, characterized in that, When the balance contribution is greater than 0, it indicates that the output of this type of entity increases during peak load periods, playing a positive regulating role in the system balance; when the balance contribution is less than 0, it indicates that the output of this type of entity decreases during peak load periods, exhibiting anti-peak shaving characteristics.

5. The power system operation evaluation method under multi-entity competitive bidding as described in claim 1, characterized in that, The unit price per kilowatt-hour is as follows: The various time dimensions are year, quarter, month, day, and hour; the various types of operating entities include coal mining machinery, nuclear power, gas turbines, wind power, photovoltaic power, and energy storage. The unit price per kilowatt-hour for coal-fired power, nuclear power, gas-fired power, wind power, photovoltaic power, and energy storage is presented as follows: in, Indicates the first Class subject in time scale The unit price of electricity is as follows: For time period The amount of electricity traded. For time period The transaction price; for different time scales, the corresponding unit price of electricity is calculated to form a time series of unit price of electricity, which is used to analyze the multi-scale change trend of unit price of electricity.

6. The power system operation evaluation method under multi-entity competitive bidding as described in claim 1, characterized in that, Based on the statistical results of the electricity price per kilowatt-hour and the overall average electricity price per kilowatt-hour of the power system, the value capture index of new energy entities is calculated as follows: in, Represents the main body of new energy In time scale The value capture index below The unit price per kilowatt-hour for this entity. This represents the total number of subject types participating in the comparison.

7. A power system operation evaluation system with multi-entity competitive bidding participation, characterized in that, include: The data acquisition and statistics module is used to acquire power system operation data of various types of operating entities in the target power system during the evaluation period. Based on multiple different time dimensions, the module combines the power system operation data to calculate the average power generation and unit price of electricity for each type of operating entity. The power balance analysis module is used to construct a multi-timescale power balance analysis model based on the average power generation, obtain different load level times within each time scale based on the multi-timescale power balance analysis model, and then calculate the balance contribution based on the changes of each operating entity at different load level times and the total load change value. The system operation evaluation module is used to calculate the value capture index of new energy entities based on the statistical results of the unit price of electricity and the overall average unit price of electricity in the power system. Then, based on the output results of the multi-time scale power balance analysis model, the balance contribution, the unit price of electricity, and the value capture index, the system operation evaluation of the target power system is realized.

8. The power system operation evaluation system with multi-entity bidding participation as described in claim 7, characterized in that, The multi-timescale power balance analysis model is specifically as follows: in, Indicates the first Class subject in time scale Average power generation under, Time scale The number of statistical periods below For the first Class subject in time period Electricity generation, Indicates time period Belongs to the time scale The statistical scope.

9. The power system operation evaluation system with multi-entity competitive bidding participation as described in claim 7, characterized in that, The multi-timescale power balance analysis model obtains the load level at different times within each time scale. Based on the changes in load level of each operating entity at different times and the total load change, the balance contribution is obtained, specifically: The different load levels include the maximum load time and the minimum load time within each time scale; The balance contribution rate characterizes the degree of response of a certain type of operating entity's output change to the change in the total load of the power system. It is the ratio of the output change of that type of operating entity between the maximum load time and the minimum load time to the total load change of the power system between the same two times, expressed as follows: in, Indicates the first Class subject in Balance contribution over time scale for The output of this type of entity at the moment of maximum load within a time scale. for The output of this type of entity at the moment of minimum load within a time scale. The maximum load within the time scale t is the maximum load. The minimum load within the time scale t is the minimum load.

10. The power system operation evaluation system with multi-entity bidding participation as described in claim 7, characterized in that, The unit price per kilowatt-hour is as follows: The various time dimensions are year, quarter, month, day, and hour; the various types of operating entities include coal mining machinery, nuclear power, gas turbines, wind power, photovoltaic power, and energy storage. The unit price per kilowatt-hour for coal-fired power, nuclear power, gas-fired power, wind power, photovoltaic power, and energy storage is presented as follows: in, Indicates the first Class subject in time scale The unit price of electricity is as follows: For time period The amount of electricity traded. For time period The transaction price; for different time scales, the corresponding unit price of electricity is calculated to form a time series of unit price of electricity, which is used to analyze the multi-scale change trend of unit price of electricity.

11. The power system operation evaluation system with multi-entity bidding participation as described in claim 7, characterized in that, Based on the statistical results of the electricity price per kilowatt-hour and the overall average electricity price per kilowatt-hour of the power system, the value capture index of new energy entities is calculated as follows: in, Represents the main body of new energy In time scale The value capture index below The unit price per kilowatt-hour for this entity. This represents the total number of subject types participating in the comparison.

12. A terminal 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 power system operation evaluation method under multi-entity competitive bidding as described in any one of claims 1 to 6.

13. 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 power system operation evaluation method under multi-entity competitive bidding as described in any one of claims 1 to 6.

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