Power resource processing method and system, computer equipment and storage medium

Abstract

The invention relates to a power resource processing method, device and system, computer equipment, a storage medium and a computer program product. The method comprises the following steps: according to a typical load curve, decomposing long coordination electric quantity to obtain long coordination decomposed electric quantity of the long coordination electric quantity in each time period; if the actual power demand information of the target time period is not matched with the long co-decomposition electric quantity of the target time period, obtaining spot electric quantity of the target time period; obtaining candidate power dispatching information of the target time period according to the long co-decomposition electric quantity and the spot electric quantity; performing scheduling optimization processing on the candidate power scheduling information to obtain target power scheduling information of a target time period; the target power dispatching information is used for indicating power generation information of a power generation enterprise and power transmission information of a power grid; and determining target resource transfer information of the target time period according to the target power dispatching information. By adopting the method, collaborative optimization of long-term coordination and spot electric quantity can be realized, and the electric power resource settlement processing efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of power technology, and in particular to a method, apparatus, system, computer equipment, storage medium, and computer program product for power resource processing. Background Technology

[0002] Driven by the global energy transition and the "dual carbon" goal, electricity market reform continues to deepen, and the construction of the spot market has become a key link in building a new power system. However, the settlement methods for medium- and long-term electricity resources and spot electricity resources are different, making coordination between them difficult.

[0003] Traditional technologies typically utilize big data modeling and dynamic threshold analysis to address the settlement issues of electricity resource transfers across different periods. However, when constructing a deep linkage between medium- and long-term contracts and the spot market using artificial intelligence models, the large scale of these models and the lengthy data processing time result in low efficiency in electricity resource settlement. Summary of the Invention

[0004] Therefore, it is necessary to provide a power resource processing method, apparatus, system, computer equipment, computer-readable storage medium, and computer program product that can improve the efficiency of power resource settlement and processing, in order to address the above-mentioned technical problems.

[0005] Firstly, this application provides a method for processing power resources. The method includes:

[0006] Based on the typical load curve, the long-term contract power is decomposed to obtain the decomposed power of the long-term contract in each time period; the typical load curve is obtained by processing historical power load data for historical time periods.

[0007] If the actual electricity demand information for the target time period does not match the long-term contracted electricity volume for the target time period, then the spot electricity volume for the target time period is obtained.

[0008] Based on the long-term contract power volume and the spot power volume, candidate power dispatch information for the target time period is obtained;

[0009] The candidate power dispatch information is processed by dispatch optimization to obtain the target power dispatch information for the target time period; the target power dispatch information is used to indicate the power generation information of power generation enterprises and the power transmission information of the power grid.

[0010] Based on the target power dispatch information, determine the target resource transfer information for the target time period.

[0011] In one embodiment, the candidate power dispatch information is subjected to dispatch optimization processing to obtain the target power dispatch information for the target time period, including:

[0012] Based on the power generation cost information of the power generation enterprises and the power transmission cost information of the power grid, the objective function is obtained;

[0013] Based on the objective function and power constraints, the candidate power dispatch information is optimized to obtain the target power dispatch information for the target time period; the power constraints are set based on the power generation and transmission power within the target time period.

[0014] In one embodiment, before performing scheduling optimization processing on the candidate power scheduling information based on the objective function and power constraints to obtain the target power scheduling information for the target time period, the method further includes:

[0015] Based on the maximum power generation of the power generation enterprise during the target time period, the power generation capacity constraint is obtained;

[0016] Based on the maximum transmission power of the power grid during the target time period, the power transmission capacity constraint is obtained.

[0017] Based on the actual power demand information for the target time period, the load demand constraints are obtained;

[0018] Based on the power generation capacity constraints, transmission capacity constraints, and load demand constraints, the power constraints are obtained.

[0019] In one embodiment, determining the target resource transfer information for the target time period based on the target power dispatch information includes:

[0020] Obtain the first power resource transfer information corresponding to the target long-term contract power volume in the target power dispatch information, and obtain the second power resource transfer information corresponding to the target spot power volume in the target power dispatch resource information;

[0021] Based on the first power resource transfer information and the target long-term contract power volume, as well as the second power resource transfer information and the target spot power volume, candidate resource transfer information for the target time period is obtained.

[0022] In one embodiment, the method further includes:

[0023] Based on the long-term contracted electricity volume for a preset time period and the third power resource transfer information corresponding to the long-term contracted electricity volume, candidate resource transfer information for the preset time period is obtained.

[0024] Based on the difference between the actual power generation of the power generation enterprise in the preset time period and the long-term contract power generation in the preset time period, the candidate resource transfer information is adjusted to obtain the target resource transfer information for the preset time period.

[0025] In one embodiment, after determining the target resource transfer information for the target time period based on the target power dispatch information, the method further includes:

[0026] Obtain a pre-built resource verification model;

[0027] The target resource transfer information is simulated and verified using the resource verification model to obtain the verification result of the target resource transfer information.

[0028] Secondly, this application also provides an electric resource processing device. The device includes:

[0029] The power decomposition module is used to decompose the long-term contract power according to the typical load curve to obtain the long-term contract power in each time period; the typical load curve is obtained by processing historical power load data for historical time periods.

[0030] The demand matching module is used to obtain the spot electricity for the target time period if the actual electricity demand information for the target time period does not match the long-term contracted electricity for the target time period.

[0031] The power dispatch module is used to obtain candidate power dispatch information for the target time period based on the long-term contract power and the spot power.

[0032] The scheduling optimization module is used to perform scheduling optimization processing on the candidate power scheduling information to obtain the target power scheduling information for the target time period; the target power scheduling information is used to indicate the power generation information of power generation enterprises and the power transmission information of the power grid.

[0033] The resource processing module is used to determine the target resource transfer information for the target time period based on the target power dispatch information.

[0034] Thirdly, this application also provides a power resource processing system. The system includes: a data acquisition module and a resource processing module;

[0035] The data acquisition module is used to acquire long-term contract power volume and actual power demand information for the target time period and send it to the resource processing module;

[0036] The resource processing module is used to decompose the long-term contracted electricity volume according to a typical load curve to obtain the decomposed long-term contracted electricity volume in each time period; the typical load curve is obtained based on historical power load data of historical time periods; if the actual power demand information of the target time period does not match the decomposed long-term contracted electricity volume of the target time period, candidate power dispatch information for the target time period is obtained according to the decomposed long-term contracted electricity volume and the spot electricity volume; the candidate power dispatch information is processed for dispatch optimization to obtain target power dispatch information for the target time period; the target power dispatch information is used to indicate the power generation information of power generation enterprises and the power transmission information of the power grid; and the target resource transfer information for the target time period is determined according to the target power dispatch information.

[0037] Fourthly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0038] Based on the typical load curve, the long-term contract power is decomposed to obtain the decomposed power of the long-term contract in each time period; the typical load curve is obtained by processing historical power load data for historical time periods.

[0039] If the actual electricity demand information for the target time period does not match the long-term contracted electricity volume for the target time period, then the spot electricity volume for the target time period is obtained.

[0040] Based on the long-term contract power volume and the spot power volume, candidate power dispatch information for the target time period is obtained;

[0041] The candidate power dispatch information is processed by dispatch optimization to obtain the target power dispatch information for the target time period; the target power dispatch information is used to indicate the power generation information of power generation enterprises and the power transmission information of the power grid.

[0042] Based on the target power dispatch information, determine the target resource transfer information for the target time period.

[0043] Fifthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0044] Based on the typical load curve, the long-term contract power is decomposed to obtain the decomposed power of the long-term contract in each time period; the typical load curve is obtained by processing historical power load data for historical time periods.

[0045] If the actual electricity demand information for the target time period does not match the long-term contracted electricity volume for the target time period, then the spot electricity volume for the target time period is obtained.

[0046] Based on the long-term contract power volume and the spot power volume, candidate power dispatch information for the target time period is obtained;

[0047] The candidate power dispatch information is processed by dispatch optimization to obtain the target power dispatch information for the target time period; the target power dispatch information is used to indicate the power generation information of power generation enterprises and the power transmission information of the power grid.

[0048] Based on the target power dispatch information, determine the target resource transfer information for the target time period.

[0049] Sixthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0050] Based on the typical load curve, the long-term contract power is decomposed to obtain the decomposed power of the long-term contract in each time period; the typical load curve is obtained by processing historical power load data for historical time periods.

[0051] If the actual electricity demand information for the target time period does not match the long-term contracted electricity volume for the target time period, then the spot electricity volume for the target time period is obtained.

[0052] Based on the long-term contract power volume and the spot power volume, candidate power dispatch information for the target time period is obtained;

[0053] The candidate power dispatch information is processed by dispatch optimization to obtain the target power dispatch information for the target time period; the target power dispatch information is used to indicate the power generation information of power generation enterprises and the power transmission information of the power grid.

[0054] Based on the target power dispatch information, determine the target resource transfer information for the target time period.

[0055] The aforementioned power resource processing methods, devices, systems, computer equipment, storage media, and computer program products decompose long-term contracted electricity volume according to typical load curves to obtain the decomposed long-term contracted electricity volume for each time period. Typical load curves are obtained based on historical power load data for historical time periods. If the actual power demand information for the target time period does not match the decomposed long-term contracted electricity volume for that time period, spot electricity volume for that time period is obtained. Based on the decomposed long-term contracted electricity volume and spot electricity volume, candidate power dispatch information for the target time period is obtained. This candidate power dispatch information is then optimized to obtain the target power dispatch information for the target time period. The target power dispatch information is used to indicate the power generation information of power generation enterprises and the power transmission information of the power grid. Based on the target power dispatch information, the target resource transfer information for the target time period is determined. Using this method, power dispatch can be optimized based on the decomposed long-term contracted electricity volume and spot electricity volume for each time period, thereby accurately determining the target resource transfer information for the target time period. This achieves coordinated optimization of long-term contracted and spot electricity volumes, enhances the responsiveness to changes in actual power usage, and improves the efficiency of power resource settlement processing. Attached Figure Description

[0056] Figure 1 This is an application environment diagram of a power resource processing method in one embodiment;

[0057] Figure 2 This is a flowchart illustrating a power resource processing method in one embodiment;

[0058] Figure 3 This is a flowchart illustrating the steps of optimizing candidate power dispatch information in one embodiment.

[0059] Figure 4 This is a flowchart illustrating the power resource processing method in another embodiment;

[0060] Figure 5 This is a schematic diagram of the structure of a power resource processing system in one embodiment;

[0061] Figure 6 This is a schematic diagram of the data flow of a power resource processing system in one embodiment;

[0062] Figure 7 This is a structural block diagram of a power resource processing device in one embodiment;

[0063] Figure 8 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0064] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0065] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0066] The power resource processing method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, the power system 101 communicates with the enterprise end 102 of the power generation company and the grid end 103 of the power grid via a network. The data storage system can store the data that the processor end 101 needs to process. The data storage system can be integrated on a server, or it can be located on the cloud or other network servers. The processor end 101 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart vehicle devices, etc. Portable wearable devices can include smartwatches, smart bracelets, head-mounted devices, etc. The server 102 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0067] In one embodiment, such as Figure 2 As shown, a power resource processing method is provided, which is applied to... Figure 1 Taking the power system in China as an example, the following steps are included:

[0068] Step S201: Based on the typical load curve, the long-term contract power is decomposed to obtain the decomposed power of the long-term contract in each time period; the typical load curve is obtained by processing historical power load data for historical time periods.

[0069] Specifically, the typical load curve is derived from the analysis and summarization of a large amount of historical power load data, reflecting the patterns and characteristics of power demand in different time periods. A matching model for the electricity volume and time period of long-term contracts and spot transactions is established. Long-term contracts, as the stable cornerstone of power trading, stipulate the electricity supply within a specific time period. To translate the agreed-upon long-term contract electricity volume into precise scheduling in actual operation, it is necessary to decompose the agreed-upon electricity volume in the long-term contract into smaller time periods based on the typical load curve, thus obtaining the decomposed long-term contract electricity volume in each time period. The time period can be daily or hourly. Through this decomposition method, the long-term contract electricity volume becomes the basic electricity supply, providing a reliable guarantee for the stable operation of the power system.

[0070] Step S202: If the actual electricity demand information for the target time period does not match the long-term contracted electricity volume for the target time period, then obtain the spot electricity volume for the target time period.

[0071] Specifically, in the spot market, electricity supply and demand are constantly changing and highly uncertain. A real-time monitoring mechanism is needed to dynamically track the electricity supply and demand situation. When there is a discrepancy between the actual electricity demand for a target time period and the long-term contracted electricity volume for that period, the electricity volume is supplemented or adjusted through spot market supply. For example, during peak summer electricity consumption periods, due to rising temperatures, residential air conditioning usage increases significantly, and industrial production is also at its peak, leading to a sharp rise in actual electricity demand in a certain region, exceeding the long-term contracted volume. At this time, the power system automatically activates the spot market supply mechanism, transferring spot electricity resources with power generation companies to obtain additional electricity to meet load demand and ensure the stability and reliability of electricity supply. This resource transfer and matching mechanism between long-term contracts and the spot market not only ensures the stable execution of long-term contracts but also flexibly responds to real-time changes in the electricity market, improving the efficiency of electricity resource allocation.

[0072] Step S203: Based on the long-term contract power and spot power, obtain candidate power dispatch information for the target time period.

[0073] Specifically, the power system can preliminarily determine the power generation of power generation enterprises for long-term contract allocation and spot market allocation under the target time period, as well as the transmission power of the power grid, based on the long-term contract allocation and spot market allocation, and thus obtain candidate power dispatch information for the target time period.

[0074] Step S204: Perform scheduling optimization processing on the candidate power dispatch information to obtain the target power dispatch information for the target time period; the target power dispatch information is used to indicate the power generation information of power generation enterprises and the power transmission information of the power grid.

[0075] Specifically, the power system can also optimize the scheduling of candidate power dispatch information by comprehensively considering long-term contract power resource transfer information, day-ahead spot resource transfer information, real-time spot resource transfer information, and ancillary service resource transfer information through a scheduling optimization algorithm, thereby obtaining the target power dispatch information for the target time period. During the optimization scheduling process, not only economic factors such as generation and transmission costs must be considered, but also the safe and stable operation of the power system must be fully taken into account to ensure that users' electricity needs can be met under various circumstances.

[0076] Step S205: Determine the target resource transfer information for the target time period based on the target power dispatch information.

[0077] Specifically, through a multi-cycle linked resource processing model, the power resource transfer information for each target time period is processed to obtain the total target resource transfer information for each target time period. It can also calculate the power resource transfer information for each preset time period to obtain the target resource transfer information for each preset time period.

[0078] In the aforementioned power resource processing method, long-term contracted electricity is decomposed based on typical load curves to obtain the decomposed electricity for each time period. Typical load curves are obtained from historical power load data for historical time periods. If the actual power demand information for the target time period does not match the decomposed electricity for that period, spot electricity for that period is acquired. Based on the decomposed and spot electricity, candidate power dispatch information for the target time period is obtained. This candidate power dispatch information is then optimized to obtain the target power dispatch information for the target time period. The target power dispatch information is used to indicate the power generation information of power generation enterprises and the power transmission information of the power grid. Based on the target power dispatch information, the target resource transfer information for the target time period is determined. This method optimizes power dispatch based on the decomposed electricity and spot electricity for each time period, accurately determining the target resource transfer information for the target time period. It achieves coordinated optimization of long-term and spot electricity, enhancing the ability to respond to changes in actual power usage.

[0079] In one embodiment, such as Figure 3 As shown, step S204 above performs scheduling optimization processing on the candidate power dispatch information to obtain the target power dispatch information for the target time period, specifically including the following:

[0080] Step S301: Based on the power generation cost information of the power generation enterprise and the power transmission cost information of the power grid, the objective function is obtained.

[0081] Step S302: Based on the objective function and power constraints, the candidate power dispatch information is processed for dispatch optimization to obtain the target power dispatch information for the target time period; the power constraints are set based on the power generation and transmission power within the target time period.

[0082] Specifically, the objective function is first derived by integrating the power generation cost information of power generation enterprises and the transmission cost information of the power grid. The objective function is to minimize the operating cost of the power system, that is, to comprehensively minimize the power generation cost information of power generation enterprises and the transmission cost information of the power grid. At the same time, various power constraints need to be considered to optimize the candidate power dispatch information based on both the objective function and the power constraints, and finally output the target power dispatch information for the target time period.

[0083] Furthermore, when making dispatch optimization decisions, the power system prioritizes the execution of long-term contracted power volumes. Long-term contracted power resource transfers, as a crucial component of the electricity market, are characterized by stability and long-term nature. Ensuring the execution of long-term contracted power volumes helps maintain market stability and protect the interests of power generation companies. Based on this, the power system rationally allocates power generation resources according to spot market price signals. Spot market resource transfer information reflects the real-time supply and demand relationship in the electricity market. By analyzing changes in the magnitude of resource transfer information, the dispatch optimization model can determine the value of electricity at different time periods, thereby rationally arranging the power generation plans of power generation companies. For example, on a given operating day, the dispatch optimization model will pre-arrange the generation of some units based on the day-ahead spot market resource transfer forecast information and the resource transfer estimate information of power generation companies. If a large electricity demand is predicted for a certain time period the following day, and the resource transfer forecast or estimate information is high, the dispatch optimization model will pre-start the generation of some high-efficiency units to meet part of the load demand the following day. Simultaneously, to cope with sudden load changes, the dispatch optimization model will reserve a certain amount of generation capacity for real-time spot market adjustments. In this way, when a sudden situation causes a sharp increase in electricity demand, electricity can be obtained promptly through the real-time spot market, ensuring the stability of the power supply.

[0084] In this embodiment, candidate power dispatch information is optimized by minimizing the objective function and restricting power constraints, so that the output target dispatch information can not only better complete the power generation and power transmission tasks, but also reduce operating costs and ensure the safety and reliability of power system operation.

[0085] In one embodiment, before performing scheduling optimization processing on the candidate power dispatch information based on the objective function and power constraints in step S302 to obtain the target power dispatch information for the target time period, the method further includes: obtaining power generation capacity constraints based on the maximum power generation that the power generation enterprise can provide within the target time period; obtaining transmission capacity constraints based on the maximum transmission power that the power grid can withstand when transmitting power within the target time period; obtaining load demand constraints based on the actual power demand information for the target time period; and obtaining power constraints based on the power generation capacity constraints, transmission capacity constraints, and load demand constraints.

[0086] Among them, the maximum power generation of a power generation company within the target time period refers to the maximum power generation that a power generation company can provide within the target time period.

[0087] The maximum transmission power of the power grid during the target time period refers to the maximum transmission power that the power grid can withstand during the target time period.

[0088] Specifically, generation capacity constraints are constraints set for power generation companies; they refer to the maximum amount of electricity a power generation company can provide within a specific time period, which depends on factors such as the performance of power generation equipment and fuel supply. Transmission capacity constraints, on the other hand, are constraints set for the power grid; they refer to the maximum power the grid can handle during power transmission, limited by factors such as grid line capacity and transformer capacity. Load demand constraints refer to the electricity demand of users at different times, which is an important basis for dispatching decisions. All three constraints—generation capacity constraints, transmission capacity constraints, and load demand constraints—are designated as power constraints.

[0089] In this embodiment, by setting various power constraints, the safe and stable operation of the power system is fully considered, ensuring that the user's electricity demand can be met under various circumstances, and also ensuring the safety and reliability of power operation.

[0090] In one embodiment, step S205, which determines the target resource transfer information for the target time period based on the target power dispatch information, specifically includes the following: obtaining the first power resource transfer information corresponding to the target long-term contracted electricity volume in the target power dispatch information, and obtaining the second power resource transfer information corresponding to the target spot electricity volume in the target power dispatch resource information; and obtaining the candidate resource transfer information for the target time period based on the first power resource transfer information and the target long-term contracted electricity volume, as well as the second power resource transfer information and the target spot electricity volume.

[0091] Specifically, a multi-cycle linkage resource processing model is constructed under the "daily clearing and monthly settlement" model. In each target time period (e.g., daily), resource transfer information in the spot market is cleared in real time, including the collection and calculation of data such as the electricity output of power generation companies, the electricity consumption of users, and spot market prices. The target resource transfer information for the day is calculated, and funds are pre-allocated.

[0092] In this embodiment, candidate resource transfer information for the target time period is calculated by using the first power resource transfer information and the target long-term contract decomposed electricity volume, as well as the second power resource transfer information and the target spot electricity volume, which effectively improves the calculation efficiency of power resource transfer.

[0093] In one embodiment, the above-mentioned power resource processing method further includes: obtaining candidate resource transfer information for a preset time period based on the long-term contracted power volume and the third power resource transfer information corresponding to the long-term contracted power volume; and adjusting the candidate resource transfer information based on the power volume difference between the actual power generation of the power generation enterprise in the preset time period and the long-term contracted power volume in the preset time period to obtain target resource transfer information for the preset time period.

[0094] Specifically, when settling accounts for each preset time period (monthly), the transaction data for all days of the month is aggregated, and the final settlement is made in conjunction with the execution status of long-term contracts. For example, for power generation companies, the target resource transfer information for monthly settlement = long-term contract electricity volume × long-term contract resource transfer information + Σ (daily spot market resource transfer electricity volume × daily spot market resource transfer information). Meanwhile, considering the handling of deviation electricity volume, the difference between the actual power generation of the power generation company within the preset time period and the long-term contract electricity volume within the preset time period can be adjusted using penalty factors or compensation factors to obtain the target resource transfer information for the preset time period.

[0095] Furthermore, a dynamic resource transfer information pool can be established. Based on factors such as the market entity's credit rating and historical resource transfer data, a certain amount of resource transfer information is allocated to each market entity. During daily resource transfer settlement, the flow of resource transfer information among market entities is monitored in real time. When a market entity's resource transfer information pool balance falls below a certain threshold, the system automatically issues a warning and takes corresponding measures, such as limiting its subsequent transaction scale or requiring it to replenish funds. In addition, by establishing a cross-cycle fund adjustment mechanism, daily settlement fund fluctuations are included in the monthly settlement adjustment scope to ensure monthly fund balance. For example, if a power sales company experiences significant resource transfer information expenditures due to fluctuations in spot market resource transfer information on certain days, resulting in insufficient resource transfer information pool balance, the system will comprehensively calculate its resource transfer information usage for the month during monthly settlement and appropriately adjust the settlement resource transfer information to maintain its resource transfer information balance.

[0096] In this embodiment, the candidate resource transfer information is adjusted based on the difference between the actual power generation of the power generation enterprise in the preset time period and the long-term contract power generation in the preset time period to obtain the target resource transfer information in the preset time period, which effectively improves the calculation accuracy of power resource transfer.

[0097] In one embodiment, after determining the target resource transfer information for the target time period based on the target power dispatch information in step S205, the method further includes: acquiring a pre-built resource verification model; and performing simulation verification processing on the target resource transfer information through the resource verification model to obtain the verification result of the target resource transfer information.

[0098] Specifically, the verification domain constructs a full-scale sandbox testing environment, namely the resource verification model, which supports comprehensive verification before settlement rule changes.

[0099] The system processing flow can be formally represented as: F(x) = Σ[W_t·S_t + W_s·S_s + W_b·S_b]

[0100] Each parameter has a clear business meaning: W_t represents the time dimension weight factor, reflecting the degree of influence of different time periods on the settlement results; S_t is the time adjustment factor, which is dynamically adjusted according to the characteristics of the settlement period; W_s represents the spatial dimension weight, reflecting the influence of the power grid topology; S_s is the spatial adjustment factor, taking into account the changes in the power grid operating status; W_b represents the business dimension weight, reflecting the relative importance of different business rules; S_b is the business adjustment factor, which supports the dynamic adjustment of business rules.

[0101] In this embodiment, a resource verification model is used to simulate and verify the target resource transfer information, obtaining the verification results. The sandbox simulation system can identify more than 90% of rule defects in advance. During the simulation, unreasonable aspects of the rules can be identified based on the system's automatic calculations, enabling the operations team to monitor the health of resource transfer information settlement in real time, effectively enhancing risk control capabilities.

[0102] In one embodiment, such as Figure 4 As shown, another method for processing power resources is provided, which can be applied to... Figure 1 Taking the power system in China as an example, the following steps are included:

[0103] Step S401: Based on the typical load curve, the long-term contract power is decomposed to obtain the decomposed power of the long-term contract in each time period; the typical load curve is obtained by processing historical power load data for historical time periods.

[0104] Step S402: If the actual power demand information for the target time period does not match the long-term contracted power volume for the target time period, then obtain the spot power volume for the target time period.

[0105] Step S403: Based on the long-term contract power and spot power, obtain candidate power dispatch information for the target time period.

[0106] Step S404: Based on the power generation cost information of the power generation enterprise and the power transmission cost information of the power grid, the objective function is obtained.

[0107] Step S405: Based on the objective function and power constraints, the candidate power dispatch information is processed for dispatch optimization to obtain the target power dispatch information for the target time period; the power constraints are set based on the power generation and transmission power within the target time period.

[0108] Step S406: Determine the target resource transfer information for the target time period based on the target power dispatch information.

[0109] The above-mentioned power resource processing method can achieve the following beneficial effects: Long-term contracted power is decomposed based on typical load curves to obtain the decomposed power for each time period; typical load curves are obtained based on historical power load data for historical time periods; if the actual power demand information for the target time period does not match the decomposed power for the target time period, the spot power for the target time period is obtained; candidate power dispatch information for the target time period is obtained based on the decomposed power and spot power; the candidate power dispatch information is optimized to obtain the target power dispatch information for the target time period; the target power dispatch information is used to indicate the power generation information of power generation enterprises and the power transmission information of the power grid; and the target resource transfer information for the target time period is determined based on the target power dispatch information.

[0110] To more clearly illustrate the power resource processing method provided in this disclosure, a specific embodiment is used below to specifically describe the above-described power resource processing method. Another power resource processing method is provided, which can be applied to... Figure 1 The power system in China specifically includes the following:

[0111] After the long-term contract is signed, the system breaks down the contracted electricity volume into daily and hourly amounts according to a typical load curve and stores it in the database.

[0112] Before each day's operation, market participants submit spot market transaction declaration information, including the power generation capacity and quotations of power generation companies, and the electricity demand of users.

[0113] Based on the application information and system operation status, the transaction matching and scheduling module uses optimized scheduling algorithms to determine the power generation plans and power allocation schemes of power generation enterprises, giving priority to the execution of long-term contract power, while also arranging the power for spot market transactions.

[0114] In this embodiment, firstly, transaction coordination efficiency is improved: through the matching mechanism of long-term contracts and spot transactions and optimized scheduling algorithms, the organic coordination of multi-cycle transactions in the electricity market is realized, improving the efficiency of power resource allocation, reducing generation and consumption costs, and enhancing the ability of market participants to respond to market changes. Secondly, settlement management is optimized: the multi-cycle linkage settlement model and capital balance management mechanism effectively solve the problem that traditional settlement methods are difficult to adapt to the multi-cycle linkage capital balance requirements, improving the accuracy and timeliness of settlement, reducing the capital risk of market participants, and ensuring the stable operation of the electricity market.

[0115] In one embodiment, such as Figure 5 and Figure 6 As shown, a power resource processing system is provided. In this embodiment, the system includes the following steps: a data acquisition module and a resource processing module.

[0116] The data acquisition module is used to acquire long-term contracted electricity volume and actual power demand information for the target time period and send it to the resource processing module. The resource processing module is used to decompose the long-term contracted electricity volume according to the typical load curve to obtain the decomposed long-term contracted electricity volume for each time period. The typical load curve is obtained by processing historical power load data for historical time periods. If the actual power demand information for the target time period does not match the decomposed long-term contracted electricity volume for the target time period, candidate power dispatch information for the target time period is obtained based on the decomposed long-term contracted electricity volume and the spot electricity volume. The candidate power dispatch information is then optimized to obtain the target power dispatch information for the target time period. The target power dispatch information is used to indicate the power generation information of power generation enterprises and the power transmission information of the power grid. Based on the target power dispatch information, the target resource transfer information for the target time period is determined.

[0117] like Figure 5 As shown, in practical applications, the power resource processing system adopts an innovative "four-layer, three-domain" hybrid architecture design, realizing a complete closed loop from business requirements to technical implementation in power transaction settlement. This architecture fully considers the complexity of power transaction settlement operations, real-time requirements, and future business expansion needs.

[0118] At the technical architecture level, the system is divided into four layers from top to bottom:

[0119] 1. The interaction layer provides a variety of user interfaces, including a visual configuration portal and a natural language interaction interface, which allows business personnel to configure settlement rules by dragging and dropping or to directly describe business needs using natural language.

[0120] 2. The service layer is the core processing engine of the system, which includes two core components: a dynamic rule engine and an intelligent code generator. It is responsible for transforming business requirements into executable settlement logic.

[0121] 3. The data layer constructs a dedicated spatiotemporal data cube, employing a multidimensional data model to store and manage various types of settlement-related data, supporting efficient multidimensional data analysis and querying.

[0122] 4. The infrastructure layer is built on a cloud-native technology stack, using Kubernetes container orchestration and Docker containerized deployment to ensure the system has elastic scalability and high availability.

[0123] At the business function level, power resource processing is divided into three core functional domains:

[0124] 1. The configuration domain provides a complete rule management workbench, supporting the flexible definition and adjustment of settlement rules.

[0125] 2. The execution domain contains a high-performance distributed settlement engine, ensuring the efficient execution of large-scale settlement tasks.

[0126] 3. The verification domain constructs a full-scale sandbox testing environment, supporting comprehensive verification before settlement rule changes.

[0127] like Figure 6 As shown, the power resource processing system mainly includes the demand side (market participants, etc.), the supply side, the power trading platform, the medium- and long-term and spot market coordinated allocation module, and the final settlement module.

[0128] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0129] Based on the same inventive concept, this application also provides a power resource processing apparatus for implementing the power resource processing method described above. The solution provided by this apparatus is similar to the solution described in the above method; therefore, the specific limitations in one or more power resource processing apparatus embodiments provided below can be found in the limitations of the power resource processing method described above, and will not be repeated here.

[0130] In one embodiment, such as Figure 7 As shown, a power resource processing device 700 is provided, including: a power decomposition module 701, a demand matching module 702, a power dispatching module 703, a dispatching optimization module 704, and a resource processing module 705, wherein:

[0131] The power decomposition module 701 is used to decompose the long-term contract power according to the typical load curve to obtain the long-term contract power decomposed in each time period; the typical load curve is obtained by processing historical power load data of historical time periods.

[0132] The demand matching module 702 is used to obtain the spot electricity for the target time period if the actual electricity demand information for the target time period does not match the long-term contracted electricity volume for the target time period.

[0133] The power dispatch module 703 is used to obtain candidate power dispatch information for the target time period based on the long-term contract power and spot power.

[0134] The scheduling optimization module 704 is used to perform scheduling optimization processing on the candidate power scheduling information to obtain the target power scheduling information for the target time period; the target power scheduling information is used to indicate the power generation information of power generation enterprises and the power transmission information of the power grid.

[0135] The resource processing module 705 is used to determine the target resource transfer information for the target time period based on the target power dispatch information.

[0136] In one embodiment, the scheduling optimization module 704 is further configured to obtain an objective function based on the power generation cost information of the power generation enterprise and the power transmission cost information of the power grid; and to perform scheduling optimization processing on the candidate power scheduling information based on the objective function and power constraints to obtain the target power scheduling information for the target time period; the power constraints are set based on the power generation and transmission power within the target time period.

[0137] In one embodiment, the power resource processing device 700 further includes a constraint acquisition module, used to obtain power generation capacity constraints based on the maximum power generation of the power generation enterprise within the target time period; obtain transmission capacity constraints based on the maximum transmission power of the power grid during power transmission within the target time period; obtain load demand constraints based on the actual power demand information of the target time period; and obtain power constraints based on the power generation capacity constraints, transmission capacity constraints, and load demand constraints.

[0138] In one embodiment, the resource processing module 705 is further configured to obtain first power resource transfer information corresponding to the target long-term contracted electricity volume in the target power dispatch information, and second power resource transfer information corresponding to the target spot electricity volume in the target power dispatch resource information; and obtain candidate resource transfer information for the target time period based on the first power resource transfer information and the target long-term contracted electricity volume, and the second power resource transfer information and the target spot electricity volume.

[0139] In one embodiment, the power resource processing device 700 further includes an information adjustment module, which is used to obtain candidate resource transfer information for a preset time period based on the long-term contracted power volume and the third power resource transfer information corresponding to the long-term contracted power volume; and to adjust the candidate resource transfer information based on the power volume difference between the actual power generation of the power generation enterprise in the preset time period and the long-term contracted power volume in the preset time period to obtain target resource transfer information for the preset time period.

[0140] In one embodiment, the power resource processing device 700 further includes a model verification module for acquiring a pre-built resource verification model; and using the resource verification model, performing simulation verification processing on the target resource transfer information to obtain the verification result of the target resource transfer information.

[0141] Each module in the aforementioned power resource processing device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0142] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 8As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores data such as long-term contract electricity volume and spot electricity volume. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a power resource processing method.

[0143] Those skilled in the art will understand that Figure 8 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0144] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0145] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0146] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0147] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0148] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0149] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for processing power resources, characterized in that, The method includes: Based on the typical load curve, the long-term contract power is decomposed to obtain the decomposed power of the long-term contract in each time period; the typical load curve is obtained by processing historical power load data for historical time periods. If the actual electricity demand information for the target time period does not match the long-term contracted electricity volume for the target time period, then the spot electricity volume for the target time period is obtained. Based on the long-term contract power volume and the spot power volume, candidate power dispatch information for the target time period is obtained; The candidate power dispatch information is subjected to dispatch optimization processing to obtain the target power dispatch information for the target time period; the target power dispatch information is used to indicate the power generation information of power generation enterprises and the power transmission information of the power grid. Based on the target power dispatch information, determine the target resource transfer information for the target time period.

2. The method according to claim 1, characterized in that, The step of performing scheduling optimization processing on the candidate power dispatch information to obtain the target power dispatch information for the target time period includes: Based on the power generation cost information of the power generation enterprises and the power transmission cost information of the power grid, the objective function is obtained; Based on the objective function and power constraints, the candidate power dispatch information is optimized to obtain the target power dispatch information for the target time period; the power constraints are set based on the power generation and transmission power within the target time period.

3. The method according to claim 2, characterized in that, Before performing scheduling optimization processing on the candidate power scheduling information based on the objective function and power constraints to obtain the target power scheduling information for the target time period, the process further includes: Based on the maximum power generation of the power generation enterprise during the target time period, the power generation capacity constraint is obtained; Based on the maximum transmission power of the power grid during the target time period, the power transmission capacity constraint is obtained. Based on the actual power demand information for the target time period, the load demand constraints are obtained; Based on the power generation capacity constraints, transmission capacity constraints, and load demand constraints, the power constraints are obtained.

4. The method according to claim 1, characterized in that, The step of determining the target resource transfer information for the target time period based on the target power dispatch information includes: Obtain the first power resource transfer information corresponding to the target long-term contract power volume in the target power dispatch information, and obtain the second power resource transfer information corresponding to the target spot power volume in the target power dispatch resource information; Based on the first power resource transfer information and the target long-term contract power volume, as well as the second power resource transfer information and the target spot power volume, candidate resource transfer information for the target time period is obtained.

5. The method according to claim 1, characterized in that, The method further includes: Based on the long-term contracted electricity volume for a preset time period and the third power resource transfer information corresponding to the long-term contracted electricity volume, candidate resource transfer information for the preset time period is obtained. Based on the difference between the actual power generation of the power generation enterprise in the preset time period and the long-term contract power generation in the preset time period, the candidate resource transfer information is adjusted to obtain the target resource transfer information for the preset time period.

6. The method according to claim 1, characterized in that, After determining the target resource transfer information for the target time period based on the target power dispatch information, the method further includes: Obtain a pre-built resource verification model; The target resource transfer information is simulated and verified using the resource verification model to obtain the verification result of the target resource transfer information.

7. A power resource processing system, characterized in that, The system includes: a data acquisition module and a resource processing module; The data acquisition module is used to acquire long-term contract power volume and actual power demand information for the target time period and send it to the resource processing module; The resource processing module is used to decompose the long-term contracted electricity volume according to a typical load curve to obtain the decomposed long-term contracted electricity volume in each time period; the typical load curve is obtained based on historical power load data of historical time periods; if the actual power demand information of the target time period does not match the decomposed long-term contracted electricity volume of the target time period, candidate power dispatch information for the target time period is obtained according to the decomposed long-term contracted electricity volume and the spot electricity volume; the candidate power dispatch information is processed for dispatch optimization to obtain target power dispatch information for the target time period; the target power dispatch information is used to indicate the power generation information of power generation enterprises and the power transmission information of the power grid; and the target resource transfer information for the target time period is determined according to the target power dispatch information.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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