Power market transaction strategy optimization method and device and electronic equipment

Abstract

The invention discloses a power market transaction strategy optimization method and device and electronic equipment, and the method comprises the steps: obtaining the historical transaction data of a power market, and determining the transaction parameters of the power market based on the historical transaction data, the historical transaction data comprising the transaction data among a power generation end, a power distribution network and a power utilization end; constructing an electricity market transaction optimization model based on the determined transaction parameters; acquiring real-time transaction data and real-time equipment state data of the electricity market; and processing the real-time transaction data and the real-time equipment state data by using the electricity market transaction optimization model, and optimizing a transaction strategy of the electricity market based on a processing result. Through the method, multiple aspects can be comprehensively considered, a more comprehensive and reliable electricity market transaction optimization model is constructed, the strain capacity and stability of the electricity market are improved through real-time processing and feedback, and control over the electricity market is more accurate and reliable.

Description

Technical Field

[0001] The present application relates to the field of new energy power generation technology, and in particular to a method, device and electronic equipment for optimizing power market transaction strategies. Background Art

[0002] With the development of renewable energy technologies, new energy sources such as wind and solar power have become a crucial component of electricity production. While the use of new energy sources can reduce greenhouse gas emissions and alleviate energy crises, they also exhibit significant intermittent and volatile characteristics, impacting the stable operation of power systems. Currently, electricity market trading mechanisms still rely on traditional mechanisms, including matching supply and demand and leveraging market price signals, while also implementing a range of measures to address the volatility of new energy sources.

[0003] However, the volatility of renewable energy sources in these methods can cause dramatic fluctuations in electricity prices, and the power supply side is unable to adapt to the diverse demands of the demand side, resulting in poor power system stability. Furthermore, the accuracy of power supply output predictions is low, and the timeliness of data transmission between the power supply and demand side is low.

[0004] Currently, no effective solution has been proposed to address the above-mentioned problems of low power system stability and accuracy, as well as its inability to adapt to power market demand. Summary of the Invention

[0005] The purpose of the implementation method of this application is to provide a method, device and electronic equipment for optimizing electricity market trading strategies to solve the problems of low stability and accuracy of the power system and its inability to adapt to the needs of the electricity market.

[0006] To solve the above technical problems, the first aspect of this specification provides a method for optimizing power market transaction strategies, including:

[0007] Acquire historical transaction data of the power market, and determine transaction parameters of the power market based on the historical transaction data, wherein the historical transaction data includes transaction data between the power generation end, the distribution network, and the power consumption end;

[0008] Constructing an electricity market transaction optimization model based on determined transaction parameters;

[0009] Obtain real-time transaction data and equipment status data from the power market;

[0010] The real-time transaction data and the real-time device status data are processed using the power market transaction optimization model, and the transaction strategy of the power market is optimized based on the processing results.

[0011] In some embodiments of the present specification, the electricity market transaction optimization model includes an electricity market stability function, a resource utilization function, an economic benefit function, and market constraints.

[0012] In some embodiments of this specification, determining the transaction parameters of the electricity market based on the historical transaction data includes:

[0013] Performing clustering processing on the historical transaction data to obtain multiple data subsets;

[0014] Determine the association relationship between the multiple data subsets, and determine the transaction parameters corresponding to each data subset based on the data in each data subset and the association relationship between the multiple data subsets.

[0015] In some embodiments of this specification, constructing an electricity market transaction optimization model based on determined transaction parameters includes:

[0016] Determine the transaction scenario type corresponding to each transaction parameter, and classify the transaction parameters based on the transaction scenario type of each transaction parameter;

[0017] Based on the classification results, objective functions corresponding to various transaction scenario types are constructed. Transaction scenario types include market stability scenarios, resource utilization scenarios, and economic benefit scenarios.

[0018] determining a transaction object in the electricity market based on the historical transaction data;

[0019] Determine the operating constraints of each transaction object and the transaction constraints between transaction objects;

[0020] The power market transaction optimization model is constructed based on the objective function, operation constraints and transaction constraints corresponding to each transaction scenario.

[0021] In some embodiments of this specification, the power market transaction optimization model is expressed by the following formula:

[0022] E economic =∑(P market ×Q power -C generation -C storage );

[0023]

[0024] E stability =-Var(P market )+Balance(D demand -Q supply );

[0025] ∑Q supply =∑Ddemand ;

[0026] 0≤E storage (t)≤E max ;

[0027] P min ≤P generation ≤P max ;

[0028] Among them, E economic represents the economic benefits of the electricity market, P market represents the electricity price in the electricity market, Q power represents the electricity supply in the electricity market, C generation represents the power generation cost in the electricity market, C storage represents the energy storage cost in the electricity market; E efficiency represents the resource utilization efficiency of the electricity market; R available Indicates the amount of available resources in the electricity market; E stability Indicates the stability of the electricity market, Var(P market ) represents the variance of electricity prices in the electricity market, D demand and Q supply They represent the electricity demand and electricity supply in the electricity market respectively; E storage (t) represents the energy storage capacity of the electricity market at time t, E max Indicates the maximum output energy of energy storage equipment in the power market; P generation Indicates the power generation capacity of the power generation end in the power market, P min and P max They respectively represent the minimum and maximum power generation capacity of the power generation equipment at the power generation end.

[0029] In some embodiments of this specification, processing the real-time transaction data and the real-time device status data using the power market transaction optimization model includes:

[0030] Preprocessing the real-time transaction data and real-time device status data, wherein the preprocessing includes data cleaning, outlier detection processing, and data format conversion;

[0031] The pre-processed data is input into the power market transaction optimization model, and the power market transaction optimization model is solved using an optimization algorithm to obtain a target transaction strategy.

[0032] In some embodiments of this specification, the transaction strategy of the electricity market includes a power supply strategy, an energy storage strategy, and operating parameters of power generation equipment.

[0033] A second aspect of the embodiments of this specification provides a device for optimizing power market transaction strategies, including:

[0034] a first data acquisition module, configured to acquire historical transaction data of the power market and determine transaction parameters of the power market based on the historical transaction data, wherein the historical transaction data includes transaction data between power generation terminals, distribution networks, and power consumption terminals;

[0035] A model building module, used to build an electricity market transaction optimization model based on determined transaction parameters;

[0036] The second data acquisition module is used to obtain real-time transaction data and real-time equipment status data of the power market;

[0037] A strategy optimization module is used to process the real-time transaction data and real-time device status data using the power market transaction optimization model, and optimize the transaction strategy of the power market based on the processing results.

[0038] The third aspect of this specification provides an electronic device, comprising: a memory and a processor, wherein the processor and the memory are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the steps of the method described in the first aspect.

[0039] A fourth aspect of this specification provides a computer storage medium, wherein the computer storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the steps of the method described in the first aspect are implemented.

[0040] A fifth aspect of this specification provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the method described in the first aspect.

[0041] The power market transaction strategy optimization method in the embodiment of this specification obtains historical transaction data of the power market and determines the transaction parameters of the power market based on the historical transaction data, wherein the historical transaction data includes transaction data between the power generation end, the distribution network and the power consumption end; constructs a power market transaction optimization model based on the determined transaction parameters; obtains real-time transaction data and real-time equipment status data of the power market; uses the power market transaction optimization model to process the real-time transaction data and real-time equipment status data, and optimizes the transaction strategy of the power market based on the processing results. The above method can comprehensively consider multiple aspects to construct a more comprehensive and reliable power market transaction optimization model, and improve the adaptability of the power market and the stability of the power market by real-time processing and feedback of market data, and make the control of the power market more accurate and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the implementation methods of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the implementation methods or the description of the prior art. Obviously, the drawings described below are only some implementation methods recorded in this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0043] Figure 1 Shown is a schematic diagram of a power market transaction strategy optimization method provided by an embodiment of this specification;

[0044] Figure 2 Shown is a schematic diagram of a method for constructing an electricity market transaction optimization model provided by an embodiment of this specification;

[0045] Figure 3 Shown is a schematic diagram of a power market transaction strategy optimization device provided by an embodiment of this specification;

[0046] Figure 4 Shown is a schematic diagram of an electronic device provided in an embodiment of this specification. DETAILED DESCRIPTION

[0047] In order to enable those skilled in the art to better understand the technical solutions in this application, the following will clearly and completely describe the technical solutions in the embodiments of this application in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0048] It should be noted that the user-related information and data involved in the embodiments of this specification are all information and data authorized by the user or fully authorized by relevant parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with relevant laws, regulations and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users or relevant parties to choose to authorize or refuse.

[0049] It should also be noted that in the embodiments of this specification, certain software, components, models and other existing solutions in the industry may be mentioned. They should be regarded as exemplary and their purpose is only to illustrate the feasibility of implementing the technical solution of this application, but it does not mean that the applicant has or will necessarily use the solution.

[0050] As mentioned above, market transactions for renewable energy primarily rely on traditional electricity market mechanisms, including the utilization of market price signals and the matching of power generation and demand. To address the volatility of renewable energy, some market designs have introduced energy storage systems as a means of balancing power supply and demand. Common implementation methods in the market include:

[0051] Price Mechanism: The electricity market guides electricity production and consumption through market prices. Market prices adjust in real time based on supply and demand, thereby encouraging or discouraging electricity production and consumption.

[0052] Energy storage systems: Energy storage systems are used to store electricity that isn't immediately consumed during periods of high demand or output, releasing it when demand increases or supply decreases. Energy storage technologies include battery energy storage systems (BESS) and pumped hydro.

[0053] Demand response: Through price signals or incentives, consumers are guided to reduce electricity consumption during peak electricity demand periods to achieve supply and demand balance.

[0054] Forecasting and scheduling: Use weather forecasts and historical data to predict wind and solar power generation, and perform power scheduling based on the forecast results.

[0055] The above methods address the challenges of new energy through market mechanisms and technical means, but the following problems still exist in practical applications:

[0056] Price volatility and market instability: Traditional electricity market pricing mechanisms can experience significant price fluctuations when faced with fluctuations in renewable energy sources, negatively impacting market participants and system stability. For example, uncertainty in solar and wind power generation can lead to significant price fluctuations.

[0057] Limitations of Energy Storage Systems: While energy storage systems can balance electricity supply and demand, their high cost, limited charging and discharging efficiency, and short lifespan hinder their large-scale adoption. Furthermore, the scheduling and management of energy storage systems are complex, requiring real-time adjustments to adapt strategies to market demand.

[0058] Difficulty in implementing demand response: Effective implementation of demand response programs requires consumers to be sensitive to electricity prices and have the ability to adjust their electricity consumption. In practice, consumers may not respond promptly or adequately, thus affecting the supply-demand balance.

[0059] Insufficient prediction accuracy: Although existing power generation prediction methods can provide approximate prediction data, the prediction error is still large when wind speed and light intensity change drastically, which affects the scheduling efficiency of the power system.

[0060] Single objective of the optimization model: Traditional optimization models often focus on a single objective, such as maximizing economic benefits or resource utilization efficiency, while ignoring other key factors such as market stability. As a result, they are unable to take into account multiple needs in practical applications.

[0061] In summary, although existing technologies provide certain solutions for renewable energy transactions in the electricity market, they still have significant deficiencies in dealing with renewable energy fluctuations, system stability, and comprehensive optimization.

[0062] In order to solve the above problems, the embodiments of this specification provide a method for optimizing power market transaction strategies, which obtains historical transaction data of the power market and determines the transaction parameters of the power market based on the historical transaction data, wherein the historical transaction data includes transaction data between the power generation end, the distribution network and the power consumption end; constructs a power market transaction optimization model based on the determined transaction parameters; obtains real-time transaction data and real-time equipment status data of the power market; processes the real-time transaction data and real-time equipment status data using the power market transaction optimization model, and optimizes the transaction strategy of the power market based on the processing results. The above method can comprehensively consider multiple aspects to construct a more comprehensive and reliable power market transaction optimization model, and improve the adaptability of the power market and the stability of the power market by real-time processing and feedback of market data, and make the control of the power market more accurate and reliable.

[0063] It is understood that the above methods provided in this application can be applied to electronic devices, which can refer to electronic devices with data computing, processing, and storage capabilities. The electronic device can be a terminal such as a PC (Personal Computer), a tablet computer, a smartphone, a wearable device, an intelligent robot, etc.; it can also be a server. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services.

[0064] The following describes the power market transaction strategy optimization method provided by the embodiment of the present application in conjunction with the accompanying drawings.

[0065] Figure 1Shown is a schematic diagram of the power market transaction strategy optimization method provided by the embodiment of this specification. Although this specification provides the method operation steps or device structure as shown in the following embodiments or drawings, the method or device may include more or fewer operation steps or module units after partial merger based on routine or no creative labor. In the steps or structures where there is no necessary causal relationship logically, the execution order of these steps or the module structure of the device is not limited to the execution order or module structure shown in the embodiments or drawings of this specification. When the method or module structure described is applied to actual devices, servers or terminal products, it can be executed sequentially or in parallel according to the method or module structure shown in the embodiments or drawings (for example, in a parallel processor or multi-threaded processing environment, or even in a distributed processing, server cluster implementation environment). As Figure 1 As shown, the method may include:

[0066] S101: Acquire historical transaction data of the power market, and determine transaction parameters of the power market based on the historical transaction data, wherein the historical transaction data includes transaction data between a power generation end, a distribution network, and a power consumption end.

[0067] It is understood that historical transaction data may include the amount of new energy used by the power generation equipment at the power generation end when generating electricity and the corresponding power generation, the input amount of the energy storage device, the output amount of the energy storage device, the amount of electricity received by the distribution network, the amount of electricity transported by the distribution network to the power consumption end, the amount of electricity received by the power consumption end, and the electricity price in the power market. In other embodiments, the historical transaction data may also include other transaction data, and the embodiments of this specification are not limited to this. In addition, while obtaining historical transaction data, the device status of each device in the power market can also be obtained, where the devices can be, for example, power generation equipment, energy storage equipment, etc.

[0068] In some embodiments of this specification, determining the transaction parameters of the electricity market based on the historical transaction data may include:

[0069] Performing clustering processing on the historical transaction data to obtain multiple data subsets;

[0070] Determine the association relationship between the multiple data subsets, and determine the transaction parameters corresponding to each data subset based on the data in each data subset and the association relationship between the multiple data subsets.

[0071] It can be understood that after obtaining the historical transaction data, the historical transaction data can be clustered to obtain multiple data subsets, each of which can correspond to a transaction parameter, and then the transaction parameters corresponding to each data subset can be determined by analyzing the correlation between the data in the data subsets and the data between the data subsets. Furthermore, the correlation obtained by analysis can also be used for the subsequent construction of an electricity market transaction optimization model. In the embodiments of this specification, through the above-mentioned clustering and analysis of the correlation between data, compared with directly determining the transaction parameters and the electricity market transaction optimization model based on the data source of the historical transaction data obtained, more accurate and reliable results can be obtained, and the constructed model can adapt to changes in the current electricity market transaction environment more quickly, and obtain an electricity market transaction optimization model that is more suitable for the current electricity market.

[0072] In some embodiments of this specification, clustering processing of historical transaction data may include K-means clustering algorithm, hierarchical clustering algorithm, neighbor propagation clustering algorithm, etc., which can be specifically selected based on the data characteristics of the historical transaction data, and this specification does not limit this.

[0073] In some embodiments of the present specification, determining the association relationship between multiple data subsets can be achieved by using methods such as the Apriori algorithm, the FP-growth algorithm, etc., or by simulating the mapping relationship between data of different data subsets to obtain the association relationship between data subsets. An artificial intelligence network model can also be used to analyze the data of multiple data subsets to determine the association relationship between each data subset, and then obtain the transaction parameters corresponding to each data subset.

[0074] In some embodiments of this specification, before clustering historical transaction data, the historical transaction data may be pre-processed such as data cleaning, outlier detection, and data format conversion to provide a basis for the accuracy of subsequent data clustering and analysis of correlation relationships between data.

[0075] S102: Constructing an electricity market transaction optimization model based on the determined transaction parameters.

[0076] It can be understood that when constructing an electricity market transaction model based on transaction parameters, the model can also be constructed in combination with the correlation between the various transaction parameters determined in the aforementioned steps. For example, the objective function in the model and its corresponding key parameters can be pre-defined, and then based on the correlation between the various transaction parameters and the key parameters, and combined with the mathematical model of the key parameters, a power market transaction optimization model that integrates the mathematical model and the actual transaction scenario is constructed, so that the constructed model can quickly and accurately reflect the changes in the power market transaction scenario. Furthermore, when constructing the power market transaction optimization model, it can also be constructed in combination with the historical operating data of each terminal device in the power market.

[0077] In some embodiments of the present specification, the electricity market transaction optimization model may include an electricity market stability function, a resource utilization function, an economic benefit function, and market constraints.

[0078] For example, the electricity market stability function, resource utilization function, and economic benefit function can be constructed with the purpose of maximizing electricity market stability, maximizing resource utilization, and maximizing economic benefits, respectively. Market constraints can be constructed based on the balance of electricity supply and demand, operating constraints of various equipment in the market (for example, generators, energy storage equipment, etc.), and electricity demand curves.

[0079] Please refer to Figure 2 In some embodiments of this specification, building a power market transaction optimization model based on the determined transaction parameters in step S102 may specifically include:

[0080] S1021: Determine the transaction scenario type corresponding to each transaction parameter, and classify the transaction parameters based on the transaction scenario type of each transaction parameter.

[0081] It can be understood that in order to quickly construct each objective function, the transaction scenario type corresponding to each objective function can be pre-defined. Then, when constructing the electricity market optimization model based on the transaction parameters, the transaction scenario type corresponding to the transaction parameters can be determined first to classify the transaction parameters, and then the subsequent objective function can be constructed based on the classification results.

[0082] S1022: Constructing an objective function corresponding to each transaction scenario type based on the classification results. The transaction scenario types include market stability scenarios, resource utilization scenarios, and economic benefit scenarios.

[0083] It can be understood that the above-mentioned transaction scenario type is an example in the embodiments of this specification. In other embodiments, the transaction scenario type may also include more types, such as environmentally friendly scenarios, social welfare scenarios, etc., and this specification does not limit this.

[0084] S1023: Determine the transaction object of the electricity market based on the historical transaction data.

[0085] It can be understood that the transaction objects may include the transaction objects at the power generation end, distribution network and power consumption end in the power market, such as generators, energy storage equipment, power equipment in the distribution network, users at the power consumption end, etc., and then constraints can be constructed based on the transaction objects.

[0086] S1024: Determine the operation constraints of each transaction object and the transaction constraints between transaction objects.

[0087] It can be understood that the operating constraints are used to characterize the operating restrictions corresponding to a single transaction, and the transaction constraints are used to characterize the transaction constraints between at least two transaction objects. The operating constraints and transaction constraints can be used as market constraints. For example, the operating constraints can be, for example, the operating constraints of the generator set, the operating constraints of the energy storage device, etc., and the transaction constraints can be, for example, power supply and demand constraints, etc. The operating constraints of the generator set can be defined based on the operating parameters of the generator set, for example, the constraints can be defined based on the power generation of the generator set, the power generation rate of the generator set, and other related parameters. The operating constraints of the energy storage device can be defined based on the operating parameters of the energy storage device, for example, the charging rate, discharge rate, and charging amount of the energy storage device. Of course, the operating constraints and transaction constraints can also include constraints related to other transaction objects, and this specification does not limit this.

[0088] S1025: Constructing the electricity market transaction optimization model based on the objective function, operation constraints and transaction constraints corresponding to each transaction scenario.

[0089] For example, after obtaining multiple objective functions, operating constraints, and transaction constraints, a power market transaction optimization model can be constructed by linear programming or sub-linear programming, which is not limited in this specification.

[0090] In some embodiments of this specification, the power market transaction optimization model can be expressed by the following formula:

[0091] E economic =∑(P market ×Q power -C generation -C storage );

[0092]

[0093] E stability =-Var(P market )+Balance(Ddemand -Q supply );

[0094] ∑Q supply =∑D demand ;

[0095] 0≤E storage (t)≤E max ;

[0096] P min ≤P generation ≤P max ;

[0097] Among them, E economic represents the economic benefits of the electricity market, P market represents the electricity price in the electricity market, Q power represents the electricity supply in the electricity market, C generation represents the power generation cost in the electricity market, C storage represents the energy storage cost in the electricity market; E efficiency represents the resource utilization efficiency of the electricity market; R available Indicates the amount of available resources in the electricity market; E stability Indicates the stability of the electricity market, Var(P market ) represents the variance of electricity prices in the electricity market, D demand and Q supply They represent the electricity demand and electricity supply in the electricity market respectively; E storage (t) represents the energy storage capacity of the electricity market at time t, E max Indicates the maximum output energy of energy storage equipment in the power market; P generation Indicates the power generation capacity of the power generation end in the power market, P min and P max They respectively represent the minimum and maximum power generation capacity of the power generation equipment at the power generation end.

[0098] In some embodiments of this specification, the economic benefit function can be constructed based on electricity market prices and cost data, and the cost data may include the operating costs of the transaction objects at each end; the resource utilization efficiency function may include the effective utilization degree of power generation resources and energy storage resources, which can be obtained by implementing a resource monitoring system for data monitoring; the market stability function may include the degree of market price fluctuation, the balance between supply and demand, etc. In order to ensure the accurate calculation of market price volatility and consider the impact of real-time differences between demand and supply on market stability, market analysis tools and data collection platforms are required to provide a data basis.

[0099] In some embodiments of this specification, after determining constraints such as operational constraints and transaction constraints, the constraints can be integrated into a multi-objective function to ensure that the optimization result is within a practical range. An optimization algorithm can be used to process the constraints, and the algorithm will ensure that all constraints are satisfied by solving linear or nonlinear programming problems. In this process, the accuracy of the constraints and the effectiveness of the optimization algorithm can be guaranteed by using data acquisition and processing tools (such as real-time data monitoring systems), mathematical modeling software (such as MATLAB or the SciPy library in Python), and optimization solver tools (such as Gurobi or CPLEX).

[0100] S103: Acquire real-time transaction data and real-time equipment status data of the power market.

[0101] It is understood that real-time transaction data may include real-time monitoring data related to transactions between power generation, distribution networks, and power users. For example, the real-time amount of new energy used by power generation equipment at the power generation end and the corresponding real-time power generation, the real-time input and output of energy storage devices, the real-time amount of electricity received by the distribution network, the real-time amount of electricity transported from the distribution network to the power user, the real-time amount of electricity received by the power user, and the real-time electricity price in the power market.

[0102] S104: Processing the real-time transaction data and the real-time device status data using the power market transaction optimization model, and optimizing the power market transaction strategy based on the processing results.

[0103] In some embodiments of this specification, processing the real-time transaction data and the real-time device status data using the power market transaction optimization model may include:

[0104] Preprocessing the real-time transaction data and real-time device status data, wherein the preprocessing includes data cleaning, outlier detection processing, and data format conversion;

[0105] The pre-processed data is input into the power market transaction optimization model, and the power market transaction optimization model is solved using an optimization algorithm to obtain a target transaction strategy.

[0106] In some embodiments of this specification, the optimization algorithm may include a genetic algorithm, a particle swarm optimization algorithm, a simulated annealing algorithm, or a multi-objective approximation algorithm, etc., through which multiple objective functions can be optimized while satisfying constraints. Then, the objective functions and constraints are input into an optimization solution tool, such as MATLAB's Optimization Toolbox, the SciPy library in Python, or the Gurobi solver, which can handle complex mathematical models and solution processes. Finally, the validity of the model and the solution result are verified, and it can be checked whether the optimization result satisfies all constraints. Based on the inspection results, the optimization scheme is adjusted and optimized. The accuracy of the model and the validity of the solution can be ensured by using data processing tools, mathematical modeling software, and optimization solution tools.

[0107] Furthermore, when selecting an optimization algorithm, you can choose a suitable algorithm based on the specific problem, then set the algorithm parameters and implement the optimization process. The following introduces the optimization process of the optimization algorithm using the genetic algorithm, particle swarm optimization algorithm, and simulated annealing algorithm as examples.

[0108] In some embodiments of the present specification, a genetic algorithm can be used to optimize the electricity market transaction optimization model, and the optimization steps may include: initializing the population, and an initial population of a set of solutions can be generated in a random manner; defining a fitness function to evaluate the pros and cons of each solution, such as using the objective function value to evaluate; generating a new generation of population by applying selection, crossover and mutation operations, wherein the selection operation is used to select individuals with high fitness, the crossover operation is used to generate new individuals, and the mutation operation is used to increase the diversity of the population; iteratively performing the above operations until the termination conditions are met, such as reaching the maximum number of generations or convergence requirements; and finally selecting the optimal solution from the population.

[0109] In some embodiments of the present specification, a particle swarm algorithm can be used to optimize the power market transaction optimization model, and the optimization steps may include: initializing a particle swarm, where each particle represents a solution; defining an objective function as a fitness evaluation criterion; updating the speed and position of the particle, and updating the speed based on the current particle optimal solution and the global optimal solution; iteratively executing the position and speed updates until the termination condition is met; and selecting the optimal solution from the particle swarm.

[0110] In some embodiments of the present specification, a simulated annealing algorithm can be used to optimize the power market transaction optimization model, and the optimization steps may include: initializing the current solution and the initial temperature; defining an objective function as an evaluation criterion; generating a neighborhood solution and calculating its objective function value; deciding whether to accept the neighborhood solution based on an acceptance criterion, such as using the Metropolis criterion; gradually lowering the temperature to reduce the probability of accepting a bad solution; iterating until the temperature drops to a predetermined value; and finally obtaining the optimal solution as a result.

[0111] In some embodiments of the present specification, in the process of optimization using any of the above-mentioned optimization algorithms, appropriate optimization tools and programming environments, such as MATLAB's Optimization Toolbox, Python's SciPy library, or specialized optimization solvers, can be used to handle complex calculations and optimization problems, and provide algorithm implementation and debugging functions. The effective coordination of data processing, mathematical modeling, and optimization tools ensures the efficiency of the algorithm implementation and optimization process.

[0112] In some embodiments of this specification, the transaction strategy of the electricity market may include a power supply strategy, an energy storage strategy, and operating parameters of power generation equipment.

[0113] It can be understood that after using the electricity market transaction optimization model to process the real-time transaction data and real-time equipment status data, at least one of the power supply strategy, energy storage strategy, and operating parameters of the power generation equipment can be adjusted based on the processing results to adapt to the current electricity market transaction scenario.

[0114] In some embodiments of the present specification, a data acquisition and processing system can also be established to obtain real-time transaction data of the power market and perform feedback adjustments. The data collected by the system can include real-time power market prices, power generation and energy storage data, demand forecasts, and other information. The above-mentioned data processing process can specifically include: establishing a data acquisition and processing system, using an API interface to obtain real-time data from market data providers, and the real-time data can be, for example, power market prices and demand forecasts, power generation and energy storage status, etc.; pre-processing the collected data, including data cleaning, outlier detection, and data format conversion to ensure data quality; updating the database in real time and storing the processed data in the database, such as using a relational database MySQL or a NoSQL database MongoDB; passing the real-time data to the optimization model according to the requirements of the optimization algorithm, updating the model input through the data interface, and ensuring that the optimization calculation is based on the latest market information; implementing a feedback mechanism to adjust the market strategy according to the optimization results, adjust the power supply and energy storage strategy in real time, and send the adjustment instructions to the actual operating system, such as the power generation control system or the energy storage management system, through the control system; monitoring the performance of the data acquisition and processing system to ensure the timeliness and accuracy of data processing and feedback adjustments, and performing system maintenance and upgrades to adapt to market changes. Among them, when configuring the system, the data acquisition and processing system can be equipped with a stable network connection and API interface, and the system can be associated with data analysis software (such as Python's Pandas library or MATLAB) and database management systems (such as MySQL or MongoDB) to process real-time data based on the collaborative work of multiple systems or tools. Furthermore, after determining the optimized trading strategy, the feedback adjustment of the power market can rely on the interface between the control system and the actual power equipment to ensure that the optimization results can be effectively applied to market operations.

[0115] In the embodiments of this specification, the following beneficial effects can be achieved by optimizing the new energy storage power market transaction algorithm with multiple objectives:

[0116] First, it can simultaneously focus on maximizing economic benefits, maximizing resource utilization efficiency, and maximizing market stability, overcoming the limitations of traditional single-objective optimization models; by comprehensively considering multiple objectives, it can balance economic benefits, resource utilization, and market stability while optimizing electricity market trading strategies, thereby achieving a globally optimal solution.

[0117] Secondly, by introducing the objective function of maximizing market stability, the sharp fluctuations in electricity market prices can be effectively reduced, the overall stability of the market can be improved, which helps to reduce the uncertainty caused by price fluctuations, protect the interests of market participants, and enhance the reliability and attractiveness of the market.

[0118] Third, by setting the objective function of maximizing resource utilization efficiency, new energy and energy storage resources can be efficiently configured and used to avoid resource waste; resource scheduling and utilization can be optimized, the overall operating efficiency of the system can be improved, and the effective utilization of new energy resources can be enhanced.

[0119] Fourthly, the introduction of the data processing module enables real-time acquisition of market data, and feedback adjustments based on the latest information. This allows for dynamic optimization of strategies based on actual market conditions and changes in demand, improving the system's response speed and adaptability, and ensuring that optimization plans are always based on the latest market information.

[0120] Fifth, by optimizing the objective function of maximizing economic benefits, the overall economic benefits of the electricity market can be effectively improved, and scientific trading strategies can be used to reduce cost expenditures and increase profits, thereby improving the economic benefits of market participants.

[0121] Sixth, by optimizing existing electricity market trading strategies, the overall implementation cost of the power system can be continuously reduced, resource allocation can be optimized, market stability and economic benefits can be improved, and additional costs and risks caused by market fluctuations can be reduced.

[0122] Seventh, through the use of the power market transaction optimization model, it is not only applicable to the current power market, but also has strong adaptability and can be extended to different types of power markets and new energy configuration scenarios. It has high flexibility and versatility, and can thus respond to changes under different market conditions and provide feasible solutions.

[0123] Based on the above-mentioned method for optimizing electricity market transaction strategies, one or more embodiments of this specification also provide an apparatus for optimizing electricity market transaction strategies. The apparatus may include an apparatus (including a distributed system), software (application), module, plug-in, server, client, etc. that uses the method described in the embodiments of this specification and is combined with the necessary implementation hardware. Based on the same innovative concept, the apparatus in one or more embodiments provided in the embodiments of this specification is as described in the following embodiments. Since the implementation scheme and method for solving the problem of the apparatus are similar, the implementation of the specific apparatus in the embodiments of this specification can refer to the implementation of the aforementioned method, and the repetitions will not be repeated. As used below, the term "unit" or "module" can be a combination of software and / or hardware that implements predetermined functions. Although the apparatus described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived. Figure 3 The figure shows a schematic diagram of the power market transaction strategy optimization device provided by the embodiment of this specification. Figure 3 As shown, the power market transaction strategy optimization device 300 may include:

[0124] The first data acquisition module 301 is used to acquire historical transaction data of the power market and determine transaction parameters of the power market based on the historical transaction data. The historical transaction data includes transaction data between the power generation end, the distribution network and the power consumption end.

[0125] The model building module 302 is used to build an electricity market transaction optimization model based on the determined transaction parameters.

[0126] The second data acquisition module 303 is used to acquire real-time transaction data and real-time device status data of the power market.

[0127] The strategy optimization module 304 is configured to process the real-time transaction data and the real-time device status data using the power market transaction optimization model, and optimize the power market transaction strategy based on the processing results.

[0128] In some embodiments of the present specification, the electricity market transaction optimization model may include an electricity market stability function, a resource utilization function, an economic benefit function, and market constraints.

[0129] In some embodiments of the present specification, when determining the transaction parameters of the electricity market based on the historical transaction data, the first data acquisition module 301 can be specifically used to: cluster the historical transaction data to obtain multiple data subsets; determine the association relationship between the multiple data subsets, and determine the transaction parameters corresponding to each data subset based on the data in each data subset and the association relationship between the multiple data subsets.

[0130] In some embodiments of the present specification, the model construction module 302 can be specifically used to: determine the transaction scenario type corresponding to each transaction parameter, and classify the transaction parameters based on the transaction scenario type of each transaction parameter; construct the objective function corresponding to each transaction scenario type based on the classification result, and the transaction scenario types include market stability scenarios, resource utilization scenarios and economic benefit scenarios; determine the transaction objects of the power market based on the historical transaction data; determine the operating constraints of each transaction object and the transaction constraints between transaction objects; and construct the power market transaction optimization model based on the objective function, operating constraints and transaction constraints corresponding to each transaction scenario.

[0131] In some embodiments of this specification, the power market transaction optimization model can be expressed by the following formula:

[0132] E economic =Σ(P market ×Q power -C generation -C storage );

[0133]

[0134] E stability =-Var(P market )+Balance(D demand -Q supply );

[0135] ΣQ supply =∑D demand ;

[0136] 0≤E storage (t)≤E max ;

[0137] P min ≤P generation ≤P max ;

[0138] Among them, E economic represents the economic benefits of the electricity market, P market represents the electricity price in the electricity market, Q power represents the electricity supply in the electricity market, C generation represents the power generation cost in the electricity market, C storage represents the energy storage cost in the electricity market; E efficiency represents the resource utilization efficiency of the electricity market; R available Indicates the amount of available resources in the electricity market; E stability Indicates the stability of the electricity market, Var(P market ) represents the variance of electricity prices in the electricity market, D demand and Q supply They represent the electricity demand and electricity supply in the electricity market respectively; E storage (t) represents the energy storage capacity of the electricity market at time t, E max Indicates the maximum output energy of energy storage equipment in the power market; P generation Indicates the power generation capacity of the power generation end in the power market, P min and P max They respectively represent the minimum and maximum power generation capacity of the power generation equipment at the power generation end.

[0139] In some embodiments of the present specification, when the strategy optimization module 304 uses the electricity market transaction optimization model to process the real-time transaction data and real-time equipment status data, it can be specifically used to: preprocess the real-time transaction data and real-time equipment status data, and the preprocessing includes data cleaning, outlier detection processing and data format conversion; input the preprocessed data into the electricity market transaction optimization model, and use the optimization algorithm to solve the electricity market transaction optimization model to obtain the target transaction strategy.

[0140] In some embodiments of this specification, the transaction strategy of the electricity market may include a power supply strategy, an energy storage strategy, and operating parameters of power generation equipment.

[0141] The description and functions of the above modules can be understood by referring to the content of the power market trading strategy optimization method part, which will not be repeated here.

[0142] The present application also provides an electronic device, such as Figure 4 As shown, the electronic device may include a processor 401 and a memory 402, wherein the processor 401 and the memory 402 may be connected via a bus or other means. Figure 4 The bus connection is taken as an example.

[0143] The processor 401 may be a central processing unit (CPU). The processor 401 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0144] Memory 402, as a non-transient computer-readable storage medium, can be used to store non-transient software programs, non-transient computer executable programs, and modules, such as the program instructions / modules corresponding to the power market transaction strategy optimization method in the embodiment of the present invention (first data acquisition module 301, model building module 302, second data acquisition module 303, and strategy optimization module 304). Processor 401 executes the various functional applications and data processing of the processor by running the non-transient software programs, instructions, and modules stored in memory 402, thereby implementing the power market transaction strategy optimization method in the above method embodiment.

[0145] The memory 402 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and applications required for at least one function; the data storage area may store data created by the processor 401, etc. In addition, the memory 402 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 402 may optionally include a memory remotely located relative to the processor 401, and these remote memories may be connected to the processor 401 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0146] The one or more modules are stored in the memory 402 and, when executed by the processor 401, perform the following power market transaction strategy optimization method:

[0147] Acquire historical transaction data of the power market, and determine the transaction parameters of the power market based on the historical transaction data, wherein the historical transaction data includes transaction data between the power generation end, the distribution network and the power consumption end; construct a power market transaction optimization model based on the determined transaction parameters; acquire real-time transaction data and real-time equipment status data of the power market; use the power market transaction optimization model to process the real-time transaction data and real-time equipment status data, and optimize the transaction strategy of the power market based on the processing results.

[0148] The specific details of the above electronic device can be understood by referring to the corresponding descriptions and effects in the above method embodiments, and will not be repeated here.

[0149] This specification also provides a computer storage medium, which stores computer program instructions. When the computer program instructions are executed, the steps of the above-mentioned power market transaction strategy optimization method are implemented.

[0150] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD), or a solid-state drive (SSD). The storage medium can also include a combination of the above-mentioned types of memory.

[0151] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0152] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions.

[0153] For the convenience of description, the above devices are described as being divided into various units according to their functions. Of course, when implementing this application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0154] Through the description of the above embodiments, it can be seen that those skilled in the art can clearly understand that the present application can be implemented by means of software plus the necessary general hardware platform. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute certain parts of the methods of each embodiment of the present application.

[0155] The present application can be used in a wide variety of general-purpose or specialized computer system environments or configurations, such as personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments that include any of the above.

[0156] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communications network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0157] Although the present application has been described through embodiments, those skilled in the art will appreciate that there are many modifications and variations to the present application without departing from the spirit of the present application. It is intended that the appended claims include these modifications and variations without departing from the spirit of the present application.

Claims

1. A method for optimizing power market transaction strategy, characterized in that: include: Acquire historical transaction data of the power market, and determine the transaction parameters of the power market based on the historical transaction data, wherein the historical transaction data includes transaction data between the power generation end, the distribution network and the power consumption end; Constructing an electricity market transaction optimization model based on determined transaction parameters; Obtain real-time transaction data and real-time equipment status data from the power market; The real-time transaction data and the real-time device status data are processed using the power market transaction optimization model, and the transaction strategy of the power market is optimized based on the processing results.

2. The power market transaction strategy optimization method according to claim 1 is characterized in that: The power market transaction optimization model includes a power market stability function, a resource utilization function, an economic benefit function, and market constraints.

3. The power market transaction strategy optimization method according to claim 1 is characterized in that: Determining the transaction parameters of the power market based on the historical transaction data includes: Performing clustering processing on the historical transaction data to obtain multiple data subsets; Determine the association relationship between the multiple data subsets, and determine the transaction parameters corresponding to each data subset based on the data in each data subset and the association relationship between the multiple data subsets.

4. The method for optimizing power market transaction strategy according to claim 1, characterized in that: Construct an electricity market transaction optimization model based on the determined transaction parameters, including: Determine the transaction scenario type corresponding to each transaction parameter, and classify the transaction parameters based on the transaction scenario type of each transaction parameter; Based on the classification results, objective functions corresponding to various transaction scenario types are constructed. Transaction scenario types include market stability scenarios, resource utilization scenarios, and economic benefit scenarios. Determining a transaction object in the power market based on the historical transaction data; Determine the operating constraints of each transaction object and the transaction constraints between transaction objects; The power market transaction optimization model is constructed based on the objective function, operation constraints and transaction constraints corresponding to each transaction scenario.

5. The method for optimizing power market transaction strategy according to any one of claims 1 to 4, characterized in that: The power market transaction optimization model is expressed by the following formula: AND economic =Σ(P market ×Q power -C generation -C storage ): AND stability =-Var(P market )+Balance(D demand -Q supply ); ΣQ supply =∑D demand ; 0≤E storage (t)≤E max ; P min ≤P generation ≤P max ; Among them, E economic represents the economic benefits of the electricity market, P market represents the electricity price in the electricity market, Q power represents the electricity supply in the electricity market, C generation represents the generation cost in the electricity market, C storage represents the energy storage cost in the electricity market; E efficiency Represents the resource utilization efficiency of the electricity market; R available Indicates the available resources in the electricity market; E stability Indicates the stability of the electricity market, Var(P market ) represents the variance of electricity prices in the electricity market, D demand and Q supply They represent the electricity demand and electricity supply in the electricity market respectively; E storage (t) represents the energy storage capacity of the power market at time t, E max Indicates the maximum output energy of energy storage equipment in the power market; P generation represents the power generation capacity of the power generation end of the power market, P min and P max They respectively represent the minimum and maximum power generation of the power generation equipment at the power generation end.

6. The method for optimizing power market transaction strategy according to claim 1, characterized in that: The real-time transaction data and the real-time device status data are processed using the power market transaction optimization model, including: Preprocessing the real-time transaction data and real-time device status data, wherein the preprocessing includes data cleaning, outlier detection processing, and data format conversion; The preprocessed data is input into the power market transaction optimization model, and the power market transaction optimization model is solved using an optimization algorithm to obtain a target transaction strategy.

7. The method for optimizing power market transaction strategy according to claim 6, characterized in that: The trading strategies of the electricity market include power supply strategies, energy storage strategies, and operating parameters of power generation equipment.

8. A device for optimizing power market transaction strategy, characterized in that: include: A first data acquisition module, used to acquire historical transaction data of the power market and determine transaction parameters of the power market based on the historical transaction data, wherein the historical transaction data includes transaction data between the power generation end, the distribution network and the power consumption end; A model building module, used to build an electricity market transaction optimization model based on determined transaction parameters; The second data acquisition module is used to acquire real-time transaction data and real-time equipment status data of the power market; The strategy optimization module is used to process the real-time transaction data and real-time device status data using the power market transaction optimization model, and optimize the transaction strategy of the power market based on the processing results.

9. An electronic device, characterized in that: include: A memory and a processor, wherein the processor and the memory are communicatively connected to each other, the memory stores computer instructions, and the processor implements the steps of the method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer storage medium, characterized in that: The computer storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

11. A computer program product, characterized in that The invention comprises a computer program, which implements the steps of the method according to any one of claims 1 to 7 when being executed by a processor.

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