Electricity market simulation deduction system and method

Abstract

The invention discloses an electricity market simulation deduction system and method, and relates to the technical field of electricity markets. The system at least comprises a market subject simulation construction module, a market service model construction module and a swarm intelligence module, so that simulation construction of at least one electricity market subject and attribute information thereof can be realized, and at least one application scene is configured for different electricity market subjects according to the attribute information. According to the simulation deduction method in the electricity market, a model supporting application services which can be realized on an application scene is constructed, and then collective behaviors and interaction effects of market participants are simulated in the application services realized on different application scenes, so that the simulation deduction method in the electricity market is realized. The construction system is not complex, and has subjects, application scenes, application services and group intelligence close to the actual electricity market, so that the operation condition of the electricity market is efficiently simulated and deduced, and a solution is provided.

Description

Technical Field

[0001] The present application relates to the technical field of power market, and in particular to a power market simulation and deduction system and method. Background Art

[0002] As the reform of the electricity market continues to deepen, the flexibility and uncertainty of market players in their power generation and consumption decisions are increasing, bringing new challenges to market supervision and risk management. How to efficiently and simply build an electricity market simulation system to simulate and deduce the operation of the electricity market and provide insights for market regulators and participants is a technical problem that needs to be solved urgently. Summary of the invention

[0003] The present application provides a power market simulation and deduction system and method, the main purpose of which is to have subjects, application scenarios, application services and group intelligence close to the actual power market, so as to efficiently simulate and deduce the operation of the power market, provide insights for market regulators and participants, and provide a solution for effectively realizing power market simulation and deduction.

[0004] In order to achieve the above objectives, this application mainly provides the following technical solutions:

[0005] The first aspect of the present application provides a power market simulation deduction system, the system comprising at least: a market subject simulation construction module, a market service model construction module and a group intelligence module;

[0006] The market subject simulation construction module is used to construct at least one power market subject, and the power market subject corresponds to configuration attribute information;

[0007] The market service model construction module is used to configure at least one application scenario for the power market subject according to the attribute information of the power market subject, and to construct a model that supports the application service corresponding to the application scenario;

[0008] The swarm intelligence module is used to simulate the collective behavior and interactive effects of market participants in the application service implemented in the application scenario, and the market participants are from at least one of the electricity market entities.

[0009] A second aspect of the present application provides a power market simulation deduction method, which is applied to the above power market simulation deduction system, and the method includes:

[0010] Constructing at least one power market subject, the power market subject corresponding to configuration attribute information;

[0011] According to the attribute information of the power market subject, at least one application scenario is configured for the power market subject, and a model supporting the application service corresponding to the application scenario is constructed;

[0012] In the application service implemented in the application scenario, the collective behavior and interactive effects of market participants are simulated, and the market participants are from at least one of the electricity market entities.

[0013] A third aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the power market simulation method as described above is implemented.

[0014] The fourth aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the electricity market simulation method as described above when executed by the processor.

[0015] By means of the above technical solution, the technical solution provided by this application has at least the following advantages:

[0016] The present application provides a power market simulation and deduction system and method, which at least includes: a market subject simulation construction module, a market service model construction module and a group intelligence module, so as to simulate and construct at least one power market subject and its attribute information, configure at least one application scenario to different power market subjects according to the attribute information, and construct a model that supports the application service that can be realized on the application scenario, and then simulate the collective behavior and interactive effects of market participants in the application services realized in different application scenarios, so as to realize the simulation and deduction method in the power market. The power market simulation and deduction system constructed by the present application is not complicated, and has subjects, application scenarios, application services and group intelligence close to the actual power market, so as to efficiently realize the simulation and deduction of the operation of the power market, facilitate the provision of insights to market regulators and participants, and provide a solution for effectively realizing the simulation and deduction of the power market.

[0017] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0019] Figure 1 A block diagram of a power market simulation system provided in an embodiment of the present application;

[0020] Figure 2 A flow chart of a power market simulation method provided in an embodiment of the present application;

[0021] Figure 3 A block diagram of a power market simulation system provided in an embodiment of the present application;

[0022] Figure 4 The following is a schematic diagram of simulation deduction on intelligent quotation for the embodiment of the present application;

[0023] Figure 5 A flow chart of another method for simulating and deducing an electricity market provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0025] The present application embodiment provides a power market simulation system, such as Figure 1 As shown, it at least includes: a market subject simulation construction module 1, a market service model construction module 2 and a group intelligence module 3;

[0026] A market subject simulation construction module 1 is used to construct at least one power market subject, and the power market subject corresponds to configuration attribute information;

[0027] The electric power market entities include entities within the market and entities outside the market. The differentiated needs of the market entities bring complexity to the setting of the value-added service model. Based on the differentiation of the market entities, the embodiment of the present application configures corresponding attribute information for different market entities. The attribute information represents the characteristics of the market entity itself, which is actually adapted to the needs of the market entity itself. Therefore, the attribute information can be configured based on, but not limited to, the characteristics and needs of the market entity itself. The following is an exemplary explanation of the electric power market entity.

[0028] (1) Market demand

[0029] The market players in the electricity market environment mainly include power generation companies, power grid companies, power trading centers, power sales companies and power users.

[0030] 1) Power generation companies. With the accelerated advancement of my country's power system reform, the implementation of "separation of power plants from the grid, competitive bidding for access to the grid" and the ultimate goal of building a fair and open power market have become the development goals of the power system reform, and the operating environment of power generation companies has undergone tremendous changes. Faced with the introduction of a competitive mechanism, making perfect and reasonable bidding decisions and obtaining maximum profits are the main requirements for power generation companies to participate in market transactions. Therefore, the demand for value-added services for power generation companies lies in predicting transaction electricity prices, comparing various bidding strategies, and making optimal bidding decisions.

[0031] 2) Grid companies. Grid companies in the power market environment are mainly responsible for power transmission and distribution, grid dispatching, and ensuring the basic power demand of various industries. How to reduce the cost of power transmission and distribution and reasonably dispatch power resources are the main needs of grid companies. Therefore, it is necessary to carry out corresponding market transaction data analysis to cooperate with the power transmission and distribution dispatching work of the grid.

[0032] 3) Power trading center. In the market environment, the power trading center is not only the main provider of value-added services, but also the recipient of value-added services from other power trading centers, such as receiving business training from other power trading centers and learning advanced construction experience. Therefore, as the organizing and operating entity of power trading, the power trading center needs to expand its main business scope, simplify the power trading process, improve the business level of related practitioners, and provide corresponding value-added services in a targeted manner.

[0033] 4) Power sales companies. According to the framework of the new round of power system reform, power sales companies will become the most important market players on the power consumption side, and the current profit model of power sales companies is mainly to earn the difference through self-built power sources or external power purchases. After the electricity price is liberalized, how to purchase low-cost electricity, how to solve the difficulties in order financing, how to forecast and manage loads and make optimal decisions on power purchases and sales, how to optimize electricity price packages, and how to innovate business and become a comprehensive enterprise of energy supply and services are the main value-added business needs of new power sales companies. Therefore, it is necessary to carry out corresponding load forecasting, decision support and transaction loan value-added services.

[0034] 5) Electricity users. With the improvement of living conditions, electricity users have gradually developed from the initial basic electricity requirements to diversified service needs. Their demand for value-added services is mainly reflected in the independent participation in market competition, reducing energy costs, ensuring power supply quality and improving energy experience. The power trading center is required to carry out corresponding value-added services such as energy analysis and energy optimization.

[0035] (2) Demand from non-market entities

[0036] In the electricity market environment, non-market entities mainly include government departments, energy investors, power equipment manufacturers, non-industry research institutions and the general public.

[0037] 1) Government departments. With the deepening of power marketization, the power trading mechanism is very different from the past. Due to the information asymmetry between government departments and power trading centers, it may cause the system or policy to be imprecise or difficult to implement. Therefore, the government's demand for value-added services is mainly reflected in timely obtaining relevant information on power trading or market development analysis reports, or regularly obtaining popularization or training on power market knowledge.

[0038] 2) Energy investors and power equipment manufacturers. With the improvement of environmental protection requirements, the development of clean energy and new power equipment, the new energy industry and the intelligent power equipment industry are booming. However, these industries are facing the problem of low product penetration. Therefore, these companies' demand for value-added services in the power industry lies in cooperating with power trading centers with rich user bases and market data information, understanding social energy consumption information, seeking ways to promote products, and increasing market share.

[0039] 3) Research institutions outside the industry. As a pillar industry closely related to the national economy, the power industry requires data analysis from research institutions outside the industry to evaluate the development of the industry and even the entire society. For example, economic think tank research institutes and securities industry research institutions need to use macro data of electricity as an indicator to measure the production and operation activities of the entire society and the development of the industry; natural gas companies, comprehensive energy companies and other industries related to the power industry need to conduct linkage analysis of power trading data and the actual situation of the industry.

[0040] 4) The public. The public’s attitude towards a company will have a huge impact on the company’s image and marketing activities. The public’s demand for value-added services from the power trading center often focuses on information disclosure from the trading center, popularization of energy-saving knowledge, and analysis of electricity fee collection rules.

[0041] As described above, in the embodiment of the present application, the market entity simulation construction module 1 is used to simulate and construct the market entities that may exist in the electricity market simulation and deduction system. The market entities are actually the types of participants in the electricity market. Therefore, under each market entity, detailed participants can be further simulated and constructed, so that the electricity market simulation and deduction system can be closer to the actual electricity market.

[0042] The market service model construction module 2 is used to configure at least one application scenario for the power market subject according to the attribute information of the power market subject, and to construct a model that supports the application scenario to realize the application service.

[0043] For example, in the embodiment of the present application, according to the actual operating rules of the power market and the behavior of the participants (i.e., the participants from which market entity), such as according to the attribute information of a certain power market entity, at least one application scenario is configured, such as but not limited to, supply and demand scenarios, price formation mechanism scenarios, and transaction rule scenarios, and different model algorithms are used based on different scenarios to train a scenario model that can realize the application service in the scenario. For the market service model construction module 2, in fact, the embodiment of the present application provides a model to assist in realizing the application service in the power market simulation system, and the application service is a scenario service that can be provided under different market entities.

[0044] Another example is the main players in the electricity market: electricity sales companies; configured application scenarios, such as wholesale and retail of electricity products, electricity consumption consultation, provision of customized electricity price packages, energy-saving electricity use, etc.

[0045] The swarm intelligence module 3 is used to simulate the collective behavior and interaction effects of market participants in the application services implemented in the application scenario, and the market participants are from at least one power market entity.

[0046] In the embodiments of the present application, swarm intelligence algorithms, such as particle swarm optimization, ant colony algorithm, etc., can be used but are not limited to simulate the collective behavior and interactive effects of a large number of market participants.

[0047] Swarm intelligence algorithm is a bionic technology that simulates the evolution and intelligent behavior of nature, based on the behavior of the group, and produces high-quality solutions through mutual cooperation between individuals. These algorithms include ant colony algorithm, particle swarm algorithm, genetic algorithm and other types. They can solve complex problems and show broad application prospects in optimization, intelligent control, machine learning and other fields.

[0048] For example, simulating the behavior of market participants: In the electricity market, market participants include power generators, electricity users, electricity traders, etc. Their behavior is affected by many factors, such as price, supply and demand, policies, etc. Through swarm intelligence algorithms, the behavior of these market participants can be simulated, their decision-making process can be analyzed, and their market response can be predicted.

[0049] For example, simulated interactive effects: The interactive effects in the electricity market refer to the mutual influence and constraints between market participants. For example, the quotations of power generators will affect the purchasing decisions of power users, and the changes in the demand of power users will in turn affect the power supply strategies and quotations of power generators.

[0050] As mentioned above, the use of swarm intelligence algorithms can simulate this complex interactive relationship, analyze the market equilibrium state under different market conditions, and the strategic interactions between market participants.

[0051] As the above Figure 1 The implementation of the system shown in the figure (a power market simulation deduction system composed of a market subject simulation construction module 1, a market service model construction module 2 and a group intelligence module 3), the embodiment of the present application provides a power market simulation deduction method. The method embodiment corresponds to the aforementioned system embodiment. For ease of reading, the present device embodiment will no longer repeat the details of the aforementioned system embodiment one by one, but it should be clear that the method in this embodiment can correspond to all the contents of the aforementioned system embodiment, such as Figure 2 As shown, the following specific steps are provided for this embodiment of the present application;

[0052] 101. Construct at least one electricity market entity, and the electricity market entity corresponds to configuration attribute information.

[0053] 102. Based on the attribute information of the power market entity, at least one application scenario is configured for the power market entity, and a model that supports the implementation of application services corresponding to the application scenario is constructed.

[0054] 103. In the application services implemented in the application scenario, the collective behavior and interactive effects of market participants are simulated. Market participants are from at least one electricity market entity.

[0055] As mentioned above, the embodiment of the present application provides a system and method for simulating and deducing an electric power market. The system includes at least: a market subject simulation construction module, a market service model construction module and a group intelligence module, so as to simulate and construct at least one electric power market subject and its attribute information, configure at least one application scenario to different electric power market subjects according to the attribute information, and construct a model that supports the application service that can be realized on the application scenario, and then simulate the collective behavior and interactive effects of market participants in the application services realized in different application scenarios, so as to realize the simulation and deduction method in the electric power market. The electric power market simulation and deduction system constructed by the embodiment of the present application is not complicated, and has subjects, application scenarios, application services and group intelligence close to the actual electric power market, so as to efficiently realize the simulation and deduction of the operation of the electric power market, facilitate the provision of insights to market regulators and participants, and provide a solution for effectively realizing the simulation and deduction of the electric power market.

[0056] In some modified embodiments, Figure 3 As shown, the system also includes: an evaluation module 4, a data integration module 5 and a market prediction module 6, and a plurality of agent submodules are constructed in the group intelligence module 3, such as module 31, module 32, module 33...module N, to obtain the following Figure 3 The electricity market simulation system shown.

[0057] The evaluation module 4 is used to randomly sample the data results output by the swarm intelligence module using the Monte Carlo method, so as to evaluate the impact on the power market in terms of preset factor dimensions.

[0058] The Monte Carlo method is a numerical calculation method based on probability statistics, which solves problems through random sampling and statistical analysis. In the electricity market, the Monte Carlo method can be used for random sampling to evaluate the impact of various uncertain factors in market operations on market results.

[0059] Exemplarily, the embodiment of the present application adopts but is not limited to the following steps of applying the Monte Carlo method in the electricity market:

[0060] (1) Determine the random variable:

[0061] According to the uncertain factors in the electricity market, the random variables that need to be simulated are determined. These variables may include electricity demand, fuel costs, equipment failure rates, policy changes, etc.

[0062] (2) Establish probability distribution:

[0063] Model the probability distribution of each random variable. This can be determined based on historical data or expert judgment. Common probability distributions include normal distribution, uniform distribution, exponential distribution, etc.

[0064] (3) Perform random sampling:

[0065] Random sampling is performed based on the established probability distribution to generate a set of random numbers, which will represent the possible values ​​of various uncertain factors in the electricity market.

[0066] (4) Simulation analysis:

[0067] The generated random numbers are brought into the electricity market model for simulation analysis. This can be a complex mathematical model used to describe the operation mechanism of the electricity market and the interaction between various factors.

[0068] (5) Statistical analysis:

[0069] Statistical analysis of multiple simulation results is performed to obtain risk assessment and reliability indicators for the power market, which can include volatility of power prices, stability of power supply, and benefits of market participants.

[0070] For example, the embodiment of the present application also provides an example of the application of the Monte Carlo method in the power market. Assuming that the impact of power demand uncertainty on power market prices is to be evaluated, the following steps can be taken:

[0071] (1) Determine the uncertainty factors of power demand:

[0072] Consider seasonal factors (such as summer peak and winter trough), socio-economic factors (such as GDP growth rate and changes in industrial structure), etc.

[0073] (2) Establishing the probability distribution of electricity demand:

[0074] Determine the probability distribution of electricity demand based on historical data or expert judgment. For example, a normal distribution can be used to describe the volatility of electricity demand.

[0075] (3) Perform random sampling:

[0076] Random sampling is performed according to the probability distribution of power demand to generate a set of random numbers of power demand.

[0077] (4) Simulation of electricity market operation:

[0078] The generated random number of electricity demand is brought into the electricity market model for simulation analysis. The model can include the cost function of the electricity supplier, the price elasticity of electricity demand, etc.

[0079] (5) Statistical analysis of simulation results:

[0080] Statistical analysis is performed on multiple simulation results to obtain indicators such as the volatility of electricity market prices and the profits of electricity suppliers.

[0081] The data integration module 5 is used to integrate real-time power market data into the system.

[0082] In the embodiments of the present application, not only data mining technology is used to extract valuable information from historical data to provide input parameters and verification basis for market simulation, but also real-time market data is integrated into the simulation system to improve the real-time and accuracy of the simulation.

[0083] Among them, multiple agent sub-modules 31 are also constructed in the group intelligence module 3, and each agent sub-module 31 represents a market participant, so as to simulate the market transaction process through interaction between each agent sub-module 31, so as to realize the collective behavior and interactive effect of simulated market participants.

[0084] Agents play the role of market participants in power market simulation. They have certain autonomy, intelligence and interactivity. By simulating the behavior and decision-making of these agents, the complexity and dynamics of the power market can be more realistically reflected.

[0085] In the embodiment of the present application, the agent submodule 31 is constructed to characterize the market participants. The steps of constructing the market participant Agent may include but are not limited to the following:

[0086] (1) Determine the type and number of agents:

[0087] According to the actual situation of the power market, determine the types of agents that need to be simulated, such as power generation companies, power grid companies, retailers, consumers, etc. According to the market size and complexity, determine the number of each type of agent.

[0088] (2) Design the Agent's attributes and behavior rules:

[0089] Design relevant attributes for each Agent, such as capacity, cost, demand, price elasticity, etc. Set behavioral rules for each Agent according to the operation mechanism of the power market, such as bidding strategy, power generation plan, demand response, etc.

[0090] (3) Establish an interaction mechanism between agents:

[0091] Design the interaction mode between agents, such as power trading, information sharing, competition and cooperation, etc. Determine the frequency and rules of interaction to ensure the authenticity and effectiveness of the simulation.

[0092] (4) Integrate Agent into the power market simulation model:

[0093] Integrate the designed Agents into the power market simulation model to ensure that they can operate according to the set rules. Debug and optimize the simulation model to ensure its accuracy and stability.

[0094] This realizes that the role of Agent in power market simulation can include but is not limited to the following:

[0095] (1) Simulate market behavior:

[0096] Agents can simulate the behaviors of market participants such as power generators, power grid companies, retailers and consumers, such as power generation, transmission, sales and consumption. Through the interaction and competition of agents, dynamic changes such as price fluctuations and supply and demand balance in the power market can be simulated.

[0097] (2) Evaluate market strategy:

[0098] By adjusting the agent's behavior rules and properties, the impact of different market strategies and policy changes on the electricity market can be simulated. This helps policymakers and market participants evaluate the effects of different strategies and make more informed decisions.

[0099] (3) Optimize resource allocation:

[0100] Agents can autonomously adjust their power generation plans and electricity consumption behaviors according to market signals and demand changes. This helps to achieve optimal allocation of power resources and improve market efficiency and stability.

[0101] As mentioned above, building market participant agents plays an important role in power market simulation. By simulating and predicting the actual operation of the power market, it can provide valuable reference and decision support for policy makers and market participants. Figure 4 The embodiment of the present application cites a schematic diagram of simulation deduction on intelligent bidding, including: multiple agents participate, that is, market participants come from electricity sellers and electricity buyers, and the application scenario is an electricity trading simulation mode of intelligent bidding.

[0102] The market prediction module 6 is used to predict the data of the preset future period of the application service provided in the application scenario in the power market according to the data information output by the swarm intelligence module.

[0103] Power market forecasting is the basis for the stable operation of the power market. Accurate forecasting can help the power grid balance supply and demand and avoid resource waste and shortages. By collecting data such as meteorology, historical load, date type, and pre-processing the data such as cleaning, fusion, normalization, and exception handling, the data quality and integrity can be improved. Power market supply and demand forecasting is a key link to ensure the stable operation of the power system. Time series forecasting models, such as long short-term memory networks (LSTM) and attention mechanisms, can capture long-term dependencies in time series data and provide accurate model support for load forecasting.

[0104] In addition, graph structure learning technology is also widely used in this scenario. By analyzing the network structure of the power system and optimizing the supply and demand forecasting model, the accuracy of the forecast is improved. The comprehensive application of these technologies makes the supply and demand forecast of the power market more accurate, helps the rational allocation of power resources, improves energy utilization efficiency, and enhances the emergency response capability of the power system.

[0105] At present, with the comprehensive coverage of intelligent measurement equipment and the rapid growth of user data, power system prediction technology is developing in a more intelligent direction. The vertical application of large language models (LLM) represented by generative pre-trained transformer models (GPT) in the field of energy and power presents urgent needs and broad application prospects. With its powerful data processing and pattern recognition capabilities, LLM can process massive amounts of unstructured data, identify complex time dependencies and spatial correlations, extract key information from multi-dimensional information, and provide a more comprehensive perspective for power system prediction.

[0106] LLM is designed based on the Transformer architecture. It is good at processing long sequence data and capturing long-term dependencies in downstream tasks. Based on this advantage, LLM can be applied to time series prediction, using its cross-task generalization, zero-shot / few-shot learning and reasoning capabilities to improve the accuracy and interpretability of the prediction model. There are two ways to use LLM to adapt to time series prediction tasks: embedding-visible LLM adaptation and text-visible LLM adaptation.

[0107] Embedding-visible LLM adjustment redesigns LLM using the traditional "pre-training and fine-tuning" paradigm, converting time series into vector sequences, redesigning the input embedding layer to align the time series with the LLM's dimensional space, and fine-tuning it for downstream time series tasks by identifying temporal patterns and integrating multimodal information. Under this paradigm, LLM is redesigned to perceive time series embedding rather than text input; text-visible LLM adjustment follows the three steps of "pre-training, prompting, and prediction", reconstructing the input-output of the time series task into text prompts, and using prompting technology to activate the LLM's capabilities, which has strong interpretability.

[0108] As the above Figure 3 The embodiment of the present application provides another method for simulating and deducing a power market. The method embodiment corresponds to the aforementioned system embodiment. For ease of reading, the present device embodiment will not repeat the details of the aforementioned system embodiment one by one, but it should be clear that the method in this embodiment can correspond to all the contents of the aforementioned system embodiment, such as Figure 5 As shown, the following specific steps are provided for this embodiment of the present application;

[0109] 201. Combined with extracting valuable information from historical data, providing input parameters and verification basis for market simulation, and integrating real-time electricity market data into the system.

[0110] 202. Construct at least one power market entity, and the power market entity corresponds to configuration attribute information.

[0111] 203. Based on the attribute information of the power market subject, at least one application scenario is configured for the power market subject, and a model that supports the application scenario and the corresponding application service is constructed.

[0112] 204. In the application service implemented in the application scenario, the collective behavior and interaction effects of market participants are simulated, and the market participants are from at least one electricity market entity.

[0113] This step includes: in simulating the collective behavior and interactive effects of market participants, constructing an agent to represent a market participant, so as to simulate the market transaction process through interaction between various agents, thereby simulating the collective behavior and interactive effects of market participants.

[0114] 205a. In simulating the collective behavior and interaction effects of market participants, the Monte Carlo method is used for random sampling of the obtained data information to evaluate the impact on the electricity market in terms of preset factor dimensions.

[0115] 205b. In simulating the collective behavior and interaction effects of market participants, the obtained data information is used to predict the data of the preset future period of the application service provided in the application scenario in the power market.

[0116] In the embodiments of the present application, the application of the electricity market simulation system will bring significant advantages and benefits to market regulators and participants. The simulation system provides an in-depth understanding of the market operation mechanism and the behavior of participants, enhancing the insight of market regulators; by simulating different market scenarios and evaluating market risks, it helps regulators and participants to formulate effective risk management strategies; the simulation platform allows users to test different market strategies, optimize operational decisions, and improve market competitiveness; the simulation system serves as a training tool to help new market participants quickly understand market rules and improve their ability to respond to market changes, and provides policymakers with an experimental platform to evaluate the potential impact of different policy measures on the market; through the analysis and visualization of simulation results, the transparency and trust of market participants in market operations are improved, and the application of simulation technology promotes the innovation of market operation models and trading mechanisms, and promotes the sustainable development of the electricity market.

[0117] In summary, the electricity market simulation system includes a processor and a memory. The above-mentioned market entity simulation construction module, market service model construction module and swarm intelligence module are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize corresponding functions.

[0118] The processor contains a kernel, which calls the corresponding program unit from the memory. One or more kernels can be set. By adjusting the kernel parameters, the subjects, application scenarios, application services and group intelligence in the actual power market can be close to each other, so as to efficiently simulate and deduce the operation of the power market, provide insights for market regulators and participants, and provide solutions for effectively realizing power market simulation and deduction.

[0119] An embodiment of the present application provides a storage medium on which a program is stored, and when the program is executed by a processor, the power market simulation method is implemented.

[0120] An embodiment of the present application provides a processor, which is used to run a program, wherein the power market simulation method is executed when the program is running.

[0121] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program for initializing the steps of the power market simulation deduction method.

[0122] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0123] In a typical configuration, the device includes one or more processors (CPU), memory and bus. The device may also include input / output interface, network interface and the like.

[0124] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip. The memory is an example of a computer-readable medium.

[0125] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0126] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0127] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0128] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A power market simulation system, characterized in that: The system at least includes: a market subject simulation construction module, a market service model construction module and a group intelligence module; The market subject simulation construction module is used to construct at least one power market subject, and the power market subject corresponds to configuration attribute information; The market service model construction module is used to configure at least one application scenario for the power market subject according to the attribute information of the power market subject, and to construct a model that supports the application service corresponding to the application scenario; The swarm intelligence module is used to simulate the collective behavior and interactive effects of market participants in the application service implemented in the application scenario, and the market participants are from at least one of the electricity market entities.

2. The system according to claim 1, characterized in that The system further comprises: The evaluation module is used to randomly sample the data results output by the swarm intelligence module using the Monte Carlo method to evaluate the impact on the power market based on the preset factor dimension.

3. The system according to claim 1, characterized in that A plurality of agent submodules are also constructed in the swarm intelligence module, each agent submodule represents one of the market participants, so as to simulate the market transaction process through interaction between the agent submodules, thereby simulating the collective behavior and interaction effect of the market participants.

4. The system according to claim 1, characterized in that The system further comprises: a data integration module, which is used to integrate real-time electricity market data into the system.

5. The system according to any one of claims 1 to 4, characterized in that The system further comprises a market prediction module for predicting the data of a preset future period of the application service provided in the application scenario in the power market according to the data information output by the swarm intelligence module.

6. A method for simulating and deducing an electricity market, characterized in that: The method is implemented on the system as described in any one of claims 1 to 5 above, and the method comprises: Constructing at least one power market subject, the power market subject corresponding to configuration attribute information; According to the attribute information of the power market subject, at least one application scenario is configured for the power market subject, and a model supporting the application service corresponding to the application scenario is constructed; In the application service implemented in the application scenario, the collective behavior and interactive effects of market participants are simulated, and the market participants are from at least one of the electricity market entities.

7. The method according to claim 6, characterized in that The method further comprises: In the collective behavior and interactive effects of the simulated market participants, the Monte Carlo method is used for random sampling of the obtained data information to evaluate the impact on the electricity market in terms of preset factor dimensions.

8. The method according to claim 6, characterized in that In the simulation of the collective behavior and interactive effects of market participants, an agent is constructed to represent one of the market participants, so as to simulate the market transaction process through interaction between the agents, thereby simulating the collective behavior and interactive effects of the market participants.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for simulating and deducing an electricity market as described in any one of claims 6 to 8 is implemented.

10. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the power market simulation method as described in any one of claims 6 to 8.

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