Data processing method and device, equipment and storage medium

Abstract

This application provides a data processing method, apparatus, device, and storage medium applied to an energy management system. It acquires the operating data and base electricity price of a user-side photovoltaic energy storage grid-connected power station over a preset time period. Based on the power station's energy allocation strategy, it determines the mapping relationship between the operating data and the various paths involved in energy interaction within the power station. Based on the mapping relationship and the base electricity price, it determines the total revenue of the power station through a revenue calculation model. The revenue calculation model is constrained by the energy balance relationship, which is derived from the various paths involved in energy interaction within the power station. By determining the mapping relationship, the operating data is decoupled to the corresponding energy interaction paths, quantifying different energy storage scheduling strategies and ensuring that the total revenue clearly reflects the contribution of the energy interaction paths, facilitating revenue traceability. Furthermore, determining the mapping relationship based on the energy allocation strategy allows this application to flexibly adapt to the dynamic operation of the power station when calculating revenue, providing strong support for refined management and optimized scheduling of the power station.

Description

Technical Field

[0001] This application relates to the field of power management technology, and in particular to a data processing device, apparatus, equipment and storage medium. Background Technology

[0002] In distributed energy systems, energy flow paths are complex, including photovoltaic power generation, energy storage charging and discharging, and grid power purchase and sale. However, traditional revenue accounting methods are mostly based on the difference between purchased electricity and generated electricity, which has significant limitations.

[0003] For example, on the one hand, the estimation model is too simplified, often categorizing complex multi-path energy interactions into a single dimension such as self-consumption electricity and grid-connected electricity, thus failing to reflect the source path of revenue and leading to distorted revenue tracing; on the other hand, the static model of traditional methods is difficult to incorporate real-time factors such as time-of-use pricing and load fluctuations, and cannot quantitatively evaluate different energy storage dispatch strategies, thus lacking dynamic adaptability and failing to support the system's refined management and optimized dispatch.

[0004] It is evident that there is an urgent need for a new method of revenue calculation to overcome the aforementioned technical pain points of existing technologies. Summary of the Invention

[0005] This application provides a data processing method, apparatus, device, and storage medium to solve the technical problems of existing revenue calculation methods failing to reflect the revenue source path, resulting in distorted revenue tracing, and lacking dynamic adaptability, thus failing to support refined system management and optimized scheduling.

[0006] Firstly, this application provides a data processing method applied to an energy management system, the method comprising:

[0007] The system acquires the operating data and electricity price base of the user-side photovoltaic energy storage grid-connected power station during a preset time period. The operating data includes the total grid-connected electricity, total electricity consumption, and total purchased electricity.

[0008] Based on the power plant's energy allocation strategy, determine the mapping relationship between the operating data and the paths involved in energy interaction within the power plant;

[0009] Based on the mapping relationship and the electricity price base, the total revenue of the power station during the preset time period is determined by the revenue calculation model;

[0010] The application of the revenue calculation model is constrained by the energy balance relationship of the power station, which is obtained based on the law of conservation of energy and the various paths involved in energy interaction in the power station.

[0011] In one possible design, before determining the mapping relationship between the operating data and the paths involved in energy interaction within the power plant according to the power plant's energy allocation strategy, the method further includes:

[0012] Based on the energy flow direction of the power station, identify the paths involved in energy interaction within the power station;

[0013] The power volume on each path participating in energy interaction in the power station is characterized by the path power volume parameter.

[0014] Based on the energy conservation law, the energy balance relationship is obtained according to the electrical parameters of each path;

[0015] The energy interaction paths in the power station include: photovoltaic to battery charging path, photovoltaic to load power supply path, photovoltaic to grid power supply path, grid to battery charging path, battery to load power supply path, battery to grid power supply path, and grid to load power supply path.

[0016] In one possible design, before determining the total revenue of the power station during the preset time period using a revenue calculation model, the following steps are also included:

[0017] The revenue calculation model is generated based on the grid connection revenue component and the scheduling revenue component;

[0018] The grid-connected revenue component includes the sum of the electricity revenue generated by the photovoltaic-to-battery charging path, the photovoltaic-to-grid power transmission path, and the battery-to-grid power transmission path.

[0019] The scheduling revenue component includes the energy-saving revenue generated by the photovoltaic-to-load power supply path and the battery-to-load power supply path, and the difference between the charging cost generated by the grid-to-battery charging path.

[0020] In one possible design, before determining the mapping relationship between the operating data and the paths involved in energy interaction within the power plant according to the power plant's energy allocation strategy, the method further includes:

[0021] The energy allocation strategy is determined based on the operating environment and / or system constraints of the power plant.

[0022] The energy allocation strategy includes a photovoltaic power generation priority allocation strategy, and the allocation order of the photovoltaic power generation priority allocation strategy is as follows: priority is given to the photovoltaic to load power supply path, then to the photovoltaic to battery charging path, and finally to the photovoltaic to grid power transmission path.

[0023] In one possible design, the method further includes:

[0024] When the photovoltaic power generation is less than or equal to the load power consumption, the power revenue generated by the photovoltaic to battery charging path and the photovoltaic to grid power transmission path in the grid-connected revenue component is determined to be zero.

[0025] When the photovoltaic power generation is greater than the load power but less than the sum of the load power and the battery's maximum charging power, the electricity revenue generated by the photovoltaic power transmission path to the grid in the grid-connected revenue component is determined to be zero.

[0026] When the photovoltaic power generation is greater than or equal to the sum of the load power and the maximum charging power of the battery, the charging cost generated by the grid-to-battery charging path in the scheduling revenue component is determined to be zero.

[0027] In one possible design, when the scheduling benefit component is negative, the method further includes:

[0028] Generate scheduling loss alarm information;

[0029] Based on the scheduling loss alarm information and the loss paths involved in energy interaction in the power plant, loss paths are identified, and path scheduling and optimization are performed based on the loss paths.

[0030] Secondly, this application provides a data processing apparatus for use in an energy management system, the apparatus comprising:

[0031] The acquisition module is used to acquire the operating data and electricity price base of the user-side photovoltaic energy storage grid-connected power station during a preset time period. The operating data includes the total grid-connected power, total power consumption, and total purchased power.

[0032] The processing module is used to determine the mapping relationship between the operating data and the paths involved in energy interaction in the power station according to the power station's energy allocation strategy;

[0033] The calculation module is used to determine the total revenue of the power station during the preset time period based on the mapping relationship and the electricity price base, using the revenue calculation model.

[0034] The application of the revenue calculation model is constrained by the energy balance relationship of the power station, which is obtained based on the law of conservation of energy and the various paths involved in energy interaction in the power station.

[0035] In one possible design, the processing module is further configured to:

[0036] Based on the energy flow direction of the power station, identify the paths involved in energy interaction within the power station;

[0037] The power volume on each path participating in energy interaction in the power station is characterized by the path power volume parameter.

[0038] Based on the energy conservation law, the energy balance relationship is obtained according to the electrical parameters of each path;

[0039] The energy interaction paths in the power station include: photovoltaic to battery charging path, photovoltaic to load power supply path, photovoltaic to grid power supply path, grid to battery charging path, battery to load power supply path, battery to grid power supply path, and grid to load power supply path.

[0040] In one possible design, the processing module is further configured to:

[0041] The revenue calculation model is generated based on the grid connection revenue component and the scheduling revenue component;

[0042] The grid-connected revenue component includes the sum of the electricity revenue generated by the photovoltaic-to-battery charging path, the photovoltaic-to-grid power transmission path, and the battery-to-grid power transmission path.

[0043] The scheduling revenue component includes the energy-saving revenue generated by the photovoltaic-to-load power supply path and the battery-to-load power supply path, and the difference between the charging cost generated by the grid-to-battery charging path.

[0044] In one possible design, the processing module is further configured to:

[0045] The energy allocation strategy is determined based on the operating environment and / or system constraints of the power plant.

[0046] The energy allocation strategy includes a photovoltaic power generation priority allocation strategy, and the allocation order of the photovoltaic power generation priority allocation strategy is as follows: priority is given to the photovoltaic to load power supply path, then to the photovoltaic to battery charging path, and finally to the photovoltaic to grid power transmission path.

[0047] In one possible design, the computing module is further used for:

[0048] When the photovoltaic power generation is less than or equal to the load power consumption, the power revenue generated by the photovoltaic to battery charging path and the photovoltaic to grid power transmission path in the grid-connected revenue component is determined to be zero.

[0049] When the photovoltaic power generation is greater than the load power but less than the sum of the load power and the battery's maximum charging power, the electricity revenue generated by the photovoltaic power transmission path to the grid in the grid-connected revenue component is determined to be zero.

[0050] When the photovoltaic power generation is greater than or equal to the sum of the load power and the maximum charging power of the battery, the charging cost generated by the grid-to-battery charging path in the scheduling revenue component is determined to be zero.

[0051] In one possible design, the device further includes: an optimization module; the optimization module is used for:

[0052] Generate scheduling loss alarm information;

[0053] Based on the scheduling loss alarm information, the power plant identifies loss paths among the energy interaction paths and performs path scheduling and optimization based on these loss paths.

[0054] Thirdly, this application provides an electronic device, including: a memory and a processor;

[0055] The memory stores computer-executed instructions;

[0056] The processor executes computer execution instructions stored in the memory, causing the processor to perform any of the possible methods provided in the first aspect.

[0057] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, are used to implement any of the possible methods provided in the first aspect.

[0058] Fifthly, this application provides a computer program product including a computer program that, when executed by a processor, implements any of the possible methods provided in the first aspect.

[0059] This application provides a data processing method, apparatus, device, and storage medium. The method is applied to an energy management system. First, it acquires the operating data and electricity price base of a user-side photovoltaic energy storage grid-connected power station within a preset time period. The operating data includes total grid-connected electricity, total electricity consumption, and total purchased electricity. Then, based on the power station's energy allocation strategy, it determines the mapping relationship between the operating data and each path involved in energy interaction within the power station. Next, based on the mapping relationship and the electricity price base, it determines the total revenue of the power station within the preset time period through a revenue calculation model. The revenue calculation model is constrained by the power station's energy balance relationship, which is derived from each path involved in energy interaction within the power station. By determining the mapping relationship between the operating data and the corresponding energy interaction paths, the final total revenue clearly reflects the contribution of each energy interaction path, facilitating revenue traceability. Furthermore, the mapping relationship decouples the operating data to the corresponding energy interaction paths, enabling quantitative evaluation of different energy storage scheduling strategies. Moreover, by determining this mapping relationship based on the energy allocation strategy, the data processing method provided in this application can flexibly adapt to the dynamic operation of the power station when calculating revenue, possessing strong dynamic adaptability and providing powerful support for the refined management and optimized scheduling of the power station. Attached Figure Description

[0060] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0061] Figure 1 This is a schematic diagram of the energy flow of a user-side photovoltaic energy storage grid-connected power station provided in this application;

[0062] Figure 2 Flowchart of the data processing method provided in this application Figure 1 ;

[0063] Figure 3 Flowchart of the data processing method provided in this application Figure 2 ;

[0064] Figure 4 A schematic diagram of the structure of a data processing device provided in this application;

[0065] Figure 5 A schematic diagram of another data processing apparatus provided in this application;

[0066] Figure 6 A schematic diagram of the structure of the electronic device provided in this application.

[0067] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0068] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0069] In some residential scenarios, such as villas or commercial and industrial energy storage scenarios, when a photovoltaic-energy storage-grid system is activated, the electricity revenue of the photovoltaic-energy storage-grid system is usually calculated to provide core data support for energy efficiency management, so as to manage the photovoltaic-energy storage-grid system in a transparent and accurate manner.

[0070] In some embodiments, the energy flow of a photovoltaic-storage-grid system is as follows: Figure 1 As shown, Figure 1This application provides a schematic diagram of the energy flow of a user-side photovoltaic energy storage grid-connected power station, such as... Figure 1 As shown, there are complex energy interaction paths between the photovoltaic system, the energy storage system, and the power grid. The photovoltaic system can generate electricity, which means converting solar energy into electrical energy through photovoltaic modules 11 to power the load 12, sell electricity to the grid 13, or charge the energy storage system, such as battery 14. The energy storage system refers to charging from the grid 13 or the photovoltaic system during off-peak electricity prices. Grid interaction refers to dynamically adjusting the electricity purchase or sale strategy based on real-time electricity prices and load demand.

[0071] However, in this scenario, with the increasing penetration rate of new energy sources, the complexity of factors such as electricity pricing mechanisms (e.g., time-of-use pricing, peak-valley pricing), load volatility (e.g., changes in industrial and commercial electricity demand), and energy storage dispatch strategies (e.g., peak shaving and valley filling) increases significantly. This leads to significant limitations in traditional revenue calculation methods that rely heavily on the difference between purchased and generated electricity. For example, on the one hand, the estimation models are overly simplified, often lumping complex multi-path energy interactions into a single dimension such as self-consumption and grid-connected electricity, thus failing to reflect the source path of revenue and causing distortion in revenue tracing. On the other hand, the static models of traditional methods struggle to incorporate real-time factors such as time-of-use pricing and load volatility, and cannot quantitatively evaluate different energy storage dispatch strategies, thus lacking dynamic adaptability and failing to support refined system management and optimized dispatch.

[0072] To address the aforementioned problems in the existing technology, this application provides a data processing method, apparatus, device, and storage medium. The data processing method provided in this application is applied to an energy management system to provide a novel revenue calculation method. The inventive concept is as follows: based on modeling each path involved in energy interaction within a power plant, and according to the power plant's energy allocation strategy, the mapping relationship between the power plant's operating data over a preset time period and each path involved in energy interaction within the power plant is determined. Then, based on the mapping relationship and the electricity price base, the total revenue of the power plant over the preset time period is determined through a revenue calculation model.

[0073] By establishing a mapping relationship between operational data and corresponding energy interaction paths, the final total revenue clearly reflects the contribution of each energy interaction path, facilitating revenue tracing. Furthermore, this mapping relationship decouples operational data from corresponding energy interaction paths, enabling quantitative evaluation of different energy storage scheduling strategies. Moreover, determining this mapping relationship based on energy allocation strategies allows the data processing method provided in this application to flexibly adapt to the dynamic operation of the power plant when calculating revenue, exhibiting strong dynamic adaptability and providing powerful support for the refined management and optimized scheduling of the power plant. In addition, the application of the revenue calculation model is constrained by the energy balance relationship obtained from the law of energy conservation, ensuring the accuracy and reliability of the revenue calculation model output and greatly improving the engineering practicality and economic efficiency of the data processing method for revenue calculation provided in this application.

[0074] In one possible design, the energy management system may include one of the following: a user-side photovoltaic energy storage grid-connected system (EMS), an energy dispatch optimization system, or a virtual power plant (VPP) platform system.

[0075] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0076] Figure 2 Flowchart of the data processing method provided in this application Figure 1 This method can be applied to energy management systems. For example... Figure 2 As shown, the method includes:

[0077] S101. Obtain the operating data and electricity price base of the user-side photovoltaic energy storage grid-connected power station during a preset time period.

[0078] The operational data includes total grid-connected power, total power consumption, and total purchased power.

[0079] The application collects the total grid-connected electricity, total electricity consumption, and total purchased electricity of the user-side photovoltaic energy storage grid-connected power station within a preset time period, such as a revenue calculation cycle, as well as the external electricity price base. This data can be collected through electricity meters, and the application does not limit the means of obtaining the operational data.

[0080] Among these, total grid-connected electricity is, for example, the total kilowatt-hours supplied to the grid by the power station as measured by the electricity meter; total electricity consumption is, for example, the total kilowatt-hours consumed by the load as measured by the electricity meter; and total purchased electricity is, for example, the total kilowatt-hours purchased from the grid as measured by the electricity meter. Optionally, under the time-of-use pricing mechanism, the grid purchase price and grid-connected electricity price may also include rates for different time periods.

[0081] S102. Based on the power plant's energy allocation strategy, determine the mapping relationship between the operating data and the various paths involved in energy interaction within the power plant.

[0082] Based on the power plant's energy allocation strategy, a correspondence is established between operational data and the paths involved in energy interaction within the power plant. This allows for the identification of which paths primarily contribute to the measured total grid-connected electricity and which paths the total purchased electricity flows to, under the energy allocation strategy. This ensures that the operational data and the paths involved in energy interaction within the power plant are clearly correlated. Figure 1 The energy flow paths correspond to this. By dynamically analyzing the intrinsic composition of macroscopic operational data through energy allocation strategies, the path sources corresponding to revenue can be clearly identified.

[0083] In some embodiments, prior to step S102, the data processing method provided in this application further includes, as follows: Figure 3 The steps are shown. Figure 3 Flowchart of the data processing method provided in this application Figure 2 ,like Figure 3 As shown, the method includes:

[0084] S201. Identify the pathways involved in energy interaction within the power plant.

[0085] For example, based on the energy flow direction of the user-side photovoltaic energy storage grid-connected power station, the various paths involved in energy interaction in the power station can be identified.

[0086] In some embodiments, the identified paths involved in energy interaction in the power plant may include: a photovoltaic to battery charging path, a photovoltaic to load power supply path, a photovoltaic to grid power supply path, a grid to battery charging path, a battery to load power supply path, a battery to grid power supply path, and a grid to load power supply path.

[0087] S202. Characterize the electricity on each path participating in energy interaction in the power plant through path electricity parameters.

[0088] The electricity on each path participating in energy interaction is characterized by path electricity parameters. In other words, the electricity on each path participating in energy interaction in the power plant is defined by path electricity parameters, thereby defining the electricity on each path participating in energy interaction in the power plant as a corresponding independent variable.

[0089] For example, the amount of electricity on the photovoltaic-to-battery charging path is represented by path electricity parameter x1, the amount of electricity on the photovoltaic-to-load power supply path is represented by path electricity parameter x2, the amount of electricity on the photovoltaic-to-grid power supply path is represented by path electricity parameter x3, the amount of electricity on the grid-to-battery charging path is represented by path electricity parameter x4, the amount of electricity on the battery-to-load power supply path is represented by path electricity parameter x5, the amount of electricity on the battery-to-grid power supply path is represented by path electricity parameter x6, and the amount of electricity on each of the grid-to-load power supply paths is represented by path electricity parameter x7.

[0090] S203. Based on the law of conservation of energy, obtain the energy balance relationship according to the electrical parameters of each path.

[0091] According to the law of conservation of energy, the electrical charges in each path involved in energy interaction have the following energy balance relationships (1) to (6):

[0092]

[0093] The above (1) to (6) are the energy balance relationships obtained based on the electrical parameters of each path. Among them, the expression of the law of conservation of energy is A+C+E=B+D+F.

[0094] By identifying the various paths of energy interaction and obtaining the energy balance relationship based on the law of conservation of energy through the data processing method provided in this application, the complex energy flow can be decomposed into quantifiable and traceable independent variables, and a strict physical constraint framework can be established for them based on the law of conservation of energy, providing a reliable model foundation and data traceability capability for subsequent accurate and dynamic calculation of benefits.

[0095] As can be seen from the above energy balance relationships, according to linear algebra, the rank of the augmented matrix is ​​5. The non-homogeneous linear equation system consisting of the above 6 energy conservation relationships and 7 unknowns has no unique solution and has two free variables. Therefore, further constraints need to be provided based on the power plant's energy allocation strategy to ensure a unique solution to the equation system, thereby clarifying the specific path source of the operational data in conjunction with the energy conservation relationships.

[0096] In one possible design, prior to step S102, the method further includes: determining an energy allocation strategy based on the power plant's operating environment and / or system constraints.

[0097] For example, the power plant's operating environment may include one or more of the following: time-of-use pricing signals, grid dispatch instructions, and power generation forecast information. System constraints may be system operating states, such as physical constraints like battery state of charge (SOC), equipment temperature, and load priority. Energy allocation strategies are set based on the power plant's operating environment and / or system operating states.

[0098] In some embodiments, the energy allocation strategy may include a photovoltaic (PV) power generation priority allocation strategy. The allocation order of the PV power generation priority allocation strategy may be: priority allocation to the PV-to-load power supply path, second allocation to the PV-to-battery charging path, and finally allocation to the PV-to-grid power transmission path. In this case, the total grid-connected power D is very likely to be mainly mapped to the PV-to-grid power transmission path, and not primarily to the battery-to-grid power transmission path. At the same time, the total purchased power E is likely to be mapped to 0, because there is a surplus of PV power and no need to purchase power from the grid.

[0099] Based on a photovoltaic (PV) power generation priority allocation strategy, for example, when PV power generation is less than or equal to the load power consumption, the power on both the PV-to-battery charging path and the PV-to-grid power transmission path can be constrained to zero, i.e., x1 and x3 are both zero. In the operational data, the total grid-connected power D comes entirely from the battery-to-grid power transmission path, the total power consumption F comes from three paths: PV-to-load power supply, battery-to-load power supply, and grid-to-load power supply. The total purchased power E is contributed by the grid-to-battery charging path and the grid-to-load power supply path. In this scenario, PV power generation is insufficient to meet the load demand; therefore, all PV power is used for load charging, with no PV charging or grid connection. The battery may discharge to supply the load or connect to the grid, and the grid purchases power for charging and supplying the load.

[0100] When the photovoltaic power generation is greater than the load power but less than the sum of the load power and the battery's maximum charging power, the amount of electricity on the photovoltaic-to-grid power transmission path is zero, and the amount of electricity on the grid-to-load power supply path is zero. Neither the total grid-connected electricity D nor the total purchased electricity E has any path contribution. The total electricity consumption F is mapped to the photovoltaic-to-load power supply path and the battery-to-load power supply path. However, in this scenario, photovoltaic power is prioritized for the load, and the battery usually does not discharge. Therefore, the total electricity consumption F is usually entirely contributed by the photovoltaic-to-load power supply path. In this scenario, after the photovoltaic power generation meets the load, the remaining part is used entirely for battery charging, and there is no photovoltaic grid connection or grid-supply load.

[0101] When the photovoltaic power generation is greater than or equal to the sum of the load power and the battery's maximum charging power, the amount of electricity on the grid-to-battery charging path and the grid-to-load power supply path is zero. The total grid-connected electricity D is contributed by the photovoltaic-to-grid power supply path and the battery-to-grid power supply path. The total purchased electricity E has no path contribution. The total consumed electricity F is contributed by the photovoltaic-to-load power supply path and the battery-to-load power supply path. In this scenario, after the photovoltaic power generation meets the load and battery charging needs, there is still surplus for grid connection, and the grid no longer participates in charging or power supply.

[0102] It is evident that establishing a mapping relationship can ensure the physical correctness and mathematical consistency of revenue calculation using operational data, enabling the revenue calculation model to dynamically adapt to different scenarios and accurately reflect the economic contribution of each path, thereby supporting refined management and optimized scheduling.

[0103] In some embodiments, in residential scenarios, user-side photovoltaic energy storage grid-connected power stations typically experience a situation where the generated power is less than the load power, meaning the photovoltaic power generation is less than or equal to the load's electricity consumption. In industrial and commercial scenarios, all three scenarios in the aforementioned photovoltaic power generation priority allocation strategy may occur.

[0104] After determining the mapping relationship between the operating data and the paths involved in energy interaction in the power plant based on the power plant's energy allocation strategy, the total revenue is determined through a revenue calculation model based on the specific composition of the operating data.

[0105] It should be noted that energy allocation strategies can also be other energy allocation principles set according to actual operating conditions. The photovoltaic power generation priority allocation strategies listed above are only illustrative descriptions and are not a limitation on energy allocation strategies.

[0106] S103. Based on the mapping relationship and the electricity price base, determine the total revenue of the power station in the preset time period through the revenue calculation model.

[0107] Based on the mapping relationship, operational data and electricity price base are substituted into the revenue calculation model, which determines the total revenue of the power plant within a preset time period. For example, based on the mapping relationship, the total grid-connected electricity, total electricity consumption, total purchased electricity, and electricity price base are substituted into the revenue calculation model. The mapping relationship allows us to know the electricity volume along the corresponding energy interaction paths that constitute the total grid-connected electricity, total electricity consumption, and total purchased electricity, thus determining the values ​​of each independent variable in the revenue calculation model and achieving accurate revenue calculation.

[0108] In one possible design, a revenue calculation model is constructed before determining the total revenue of the power plant over a preset time period through a revenue calculation model.

[0109] For example, a revenue calculation model is generated based on the grid connection revenue component and the scheduling revenue component, as shown in equation (7) below:

[0110]

[0111] The grid connection revenue component includes the sum of the electricity revenue generated by the photovoltaic to battery charging path, the photovoltaic to grid power transmission path, and the battery to grid power transmission path, as shown in the following formula (8):

[0112]

[0113] Among them, the electricity price benchmark for electricity revenue is the grid-connected electricity price, represented as p_feed.

[0114] The dispatch revenue component includes the energy-saving revenue generated by the photovoltaic-to-load power supply path and the battery-to-load power supply path, and the difference between the charging cost generated by the grid-to-battery charging path, as shown in, for example, equation (9):

[0115]

[0116] The electricity price benchmark for both the energy-saving benefits and the charging costs is the grid purchase price, represented as p_buy.

[0117] Combining formulas (7) to (9) above, we can obtain the following (10) representing the profit calculation model:

[0118]

[0119] In one possible design, based on the photovoltaic power generation priority allocation strategy described above, in equation (10), when the photovoltaic power generation is less than or equal to the load power consumption, it can be determined that the power revenue generated by the photovoltaic to battery charging path and the photovoltaic to grid power transmission path in the grid connection revenue component is zero, where x1 and x3 are both zero.

[0120] When the photovoltaic power generation is greater than the load power but less than the sum of the load power and the battery's maximum charging power, it can be determined that the electricity revenue generated by the photovoltaic power transmission path to the grid in the grid-connected revenue component is zero, where x3 and x7 are both zero.

[0121] When the photovoltaic power generation is greater than or equal to the sum of the load power and the battery's maximum charging power, it can be determined that the charging cost generated by the grid-to-battery charging path in the dispatch revenue component is zero, where x4 and x7 are both zero.

[0122] Based on the mapping relationship and the electricity price base, the operating data is substituted into the revenue calculation model to obtain the total revenue of the power plant within a preset time period. The source of the total revenue path, i.e., the revenue originates from the energy interaction path, can also be identified. The application of the revenue calculation model is constrained by the energy balance relationship of the power plant, ensuring that the path energy parameters representing the energy interaction paths strictly adhere to the law of conservation of energy. This fundamentally eliminates calculation results that violate the law, such as the creation or disappearance of energy out of thin air. This ensures that the total revenue output by the revenue calculation model is physically reliable and accurate, providing a reliable data foundation for subsequent decision-making such as regulation and optimization.

[0123] The data processing method provided in this application is applied to an energy management system. First, it acquires the operating data and electricity price base of the user-side photovoltaic energy storage grid-connected power station within a preset time period. The operating data includes total grid-connected electricity, total electricity consumption, and total purchased electricity. Then, based on the power station's energy allocation strategy, it determines the mapping relationship between the operating data and the paths involved in energy interaction within the power station. Next, based on the mapping relationship and the electricity price base, it determines the total revenue of the power station within the preset time period through a revenue calculation model. The revenue calculation model is constrained by the power station's energy balance relationship, which is derived from each path involved in energy interaction within the power station. By determining the mapping relationship between the operating data and the corresponding energy interaction paths, the final total revenue clearly reflects the contribution of each energy interaction path, facilitating revenue tracing. Furthermore, the mapping relationship decouples the operating data to the corresponding energy interaction paths, enabling quantitative evaluation of different energy storage dispatch strategies. Moreover, by determining this mapping relationship based on the energy allocation strategy, the data processing method provided in this application can flexibly adapt to the dynamic operation of the power station when calculating revenue, possessing strong dynamic adaptability and providing powerful support for the refined management and optimized dispatch of the power station.

[0124] In one possible design, after calculating the total revenue of the power station over a preset time period using a revenue calculation model, the data processing method provided in this application may further include steps for identifying and optimizing scheduling losses. For example, when the scheduling revenue component is negative, i.e., when the total electricity consumption is less than the total purchased electricity, it may also include:

[0125] Generate scheduling loss alarm information, identify loss paths based on scheduling loss alarm information and each path involved in energy interaction in the power plant, and perform path scheduling and optimization based on loss paths.

[0126] When the dispatch revenue component is negative, meaning the total electricity consumption is less than the total purchased electricity (F < E), it indicates that the purchased electricity at the power plant has not been effectively absorbed by the load. In this case, the dispatch revenue is negative, resulting in a dispatch loss, and thus a dispatch loss alarm message is generated. For example, the dispatch loss alarm message can be sent to maintenance personnel or stored in a database as an event record. Furthermore, based on the dispatch loss alarm message and the various paths involved in energy interaction within the power plant, the electricity consumption and costs or revenues of each path are analyzed to pinpoint the main sources of the loss, identify the loss-making paths, and perform corresponding path scheduling and optimization based on these loss-making paths.

[0127] For example, in the case of a grid-to-battery charging path, electricity is purchased and charged during peak electricity price periods. However, the revenue from subsequent battery-to-load or battery-to-grid power supply paths fails to cover their costs, resulting in a loss-making path. Subsequent path scheduling and optimization could include avoiding charging from the grid or checking battery efficiency during peak electricity price periods in the future, or implementing automatic control at power plants to constrain or prevent the operation of the grid-to-battery charging path.

[0128] The data processing method provided in this application, after obtaining the total revenue, also performs scheduling loss identification and optimization, realizes loss source identification and provides scheduling optimization direction, enabling this application to have the ability of loss diagnosis, root cause analysis and optimization guidance, and can provide direct and powerful data and technical support for the refined and intelligent operation of power plants.

[0129] Figure 4 This is a schematic diagram of a data processing device provided in this application, which is applied to an energy management system. Figure 4 As shown, the data processing apparatus 400 provided in this application includes:

[0130] The acquisition module 401 is used to acquire the operating data and electricity price base of the user-side photovoltaic energy storage grid-connected power station during a preset time period. The operating data includes the total grid-connected power, total power consumption and total purchased power.

[0131] The processing module 402 is used to determine the mapping relationship between the operating data and the paths in the power plant that participate in energy interaction, based on the power plant's energy allocation strategy.

[0132] Calculation module 403 is used to determine the total revenue of the power plant in a preset time period based on the mapping relationship and the electricity price base through a revenue calculation model;

[0133] The application of the revenue calculation model is constrained by the energy balance relationship of the power plant, which is obtained based on the law of conservation of energy and the various paths involved in energy interaction in the power plant.

[0134] In one possible design, processing module 402 is also used for:

[0135] Identify the paths involved in energy interaction in the power plant, and characterize the electricity on each path involved in energy interaction in the power plant through path electricity parameters;

[0136] Based on the law of conservation of energy, the energy balance relationship is obtained according to the electrical parameters of each path.

[0137] In one possible design, processing module 402 is also used for:

[0138] Identify the various paths involved in energy interaction within the power plant based on the energy flow direction of the power plant;

[0139] The various paths involved in energy interaction in the power plant include: photovoltaic to battery charging path, photovoltaic to load power supply path, photovoltaic to grid power supply path, grid to battery charging path, battery to load power supply path, battery to grid power supply path, and grid to load power supply path.

[0140] In one possible design, processing module 402 is also used for:

[0141] The revenue calculation model generated based on the grid connection revenue component and the scheduling revenue component includes:

[0142] The grid connection revenue component includes the sum of the electricity revenue generated by the photovoltaic to battery charging path, the photovoltaic to grid power transmission path, and the battery to grid power transmission path.

[0143] The dispatch revenue component includes the energy-saving revenue generated by the photovoltaic-to-load power supply path and the battery-to-load power supply path, and the difference between the charging cost generated by the grid-to-battery charging path.

[0144] In one possible design, processing module 402 is also used for:

[0145] Based on the operating environment and / or system constraints of the power plant, determine the energy allocation strategy;

[0146] Among them, the energy allocation strategy includes the photovoltaic power generation priority allocation strategy; the allocation order of the photovoltaic power generation priority allocation strategy is: priority allocation to the photovoltaic to load power supply path, second allocation to the photovoltaic to battery charging path, and finally allocation to the photovoltaic to grid power transmission path.

[0147] In one possible design, the computing module 403 is also used for:

[0148] When the photovoltaic power generation is less than or equal to the load power consumption, the power revenue generated by the photovoltaic to battery charging path and the photovoltaic to grid power transmission path in the grid connection revenue component is determined to be zero.

[0149] When the photovoltaic power generation is greater than the load power but less than the sum of the load power and the battery's maximum charging power, the electricity revenue generated by the photovoltaic power transmission path to the grid in the grid-connected revenue component is determined to be zero.

[0150] When the photovoltaic power generation is greater than or equal to the sum of the load power and the battery's maximum charging power, the charging cost generated by the grid-to-battery charging path in the dispatch revenue component is determined to be zero.

[0151] In one possible design, the electricity price benchmark for electricity revenue is the grid connection price, while the electricity price benchmark for both electricity saving revenue and charging cost is the grid purchase price.

[0152] exist Figure 4 On this basis, Figure 5 A schematic diagram of another data processing apparatus provided in this application is shown below. Figure 5 As shown, the data processing device 400 further includes an optimization module 404, which is used for:

[0153] Generate scheduling loss alarm information;

[0154] Based on the scheduling loss alarm information and the various paths involved in energy interaction in the power plant, loss paths are identified, and path scheduling and optimization are performed based on these loss paths.

[0155] In one possible design, the energy management system includes one of the following: a user-side photovoltaic energy storage grid-connected system, an energy dispatch optimization system, or a virtual power plant platform system.

[0156] The data processing apparatus provided in this application can execute the methods provided in the above-described method embodiments. Its implementation principle and technical effects are similar, and will not be described in detail here.

[0157] Figure 6 A schematic diagram of the structure of the electronic device provided in this application, such as... Figure 6 As shown, the electronic device 50 provided in this embodiment includes at least one processor 501 and a memory 502. Optionally, the device 50 further includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus.

[0158] In a specific implementation, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to perform the above-described method.

[0159] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0160] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0161] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0162] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0163] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0164] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0165] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0166] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0167] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another power station, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0168] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0169] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0170] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0171] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0172] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A data processing method, characterized in that, The method, applied to an energy management system, includes: The system acquires the operating data and electricity price base of the user-side photovoltaic energy storage grid-connected power station during a preset time period. The operating data includes the total grid-connected electricity, total electricity consumption, and total purchased electricity. Based on the power plant's energy allocation strategy, determine the mapping relationship between the operating data and the paths involved in energy interaction within the power plant; Based on the mapping relationship and the electricity price base, the total revenue of the power station during the preset time period is determined by the revenue calculation model. The application of the revenue calculation model is constrained by the energy balance relationship of the power station, which is obtained based on the law of conservation of energy and the various paths involved in energy interaction in the power station.

2. The method according to claim 1, characterized in that, Before determining the mapping relationship between the operating data and the paths involved in energy interaction within the power plant based on the power plant's energy allocation strategy, the method further includes: Based on the energy flow direction of the power station, identify the paths involved in energy interaction within the power station; The power volume on each path participating in energy interaction in the power station is characterized by the path power volume parameter. Based on the energy conservation law, the energy balance relationship is obtained according to the electrical parameters of each path; The energy interaction paths in the power station include: photovoltaic to battery charging path, photovoltaic to load power supply path, photovoltaic to grid power supply path, grid to battery charging path, battery to load power supply path, battery to grid power supply path, and grid to load power supply path.

3. The method according to claim 2, characterized in that, Before determining the total revenue of the power plant during the preset time period using the revenue calculation model, the method further includes: The revenue calculation model is generated based on the grid connection revenue component and the scheduling revenue component; The grid-connected revenue component includes the sum of the electricity revenue generated by the photovoltaic-to-battery charging path, the photovoltaic-to-grid power transmission path, and the battery-to-grid power transmission path. The scheduling revenue component includes the energy-saving revenue generated by the photovoltaic-to-load power supply path and the battery-to-load power supply path, and the difference between the charging cost generated by the grid-to-battery charging path.

4. The method according to claim 3, characterized in that, Before determining the mapping relationship between the operating data and the paths involved in energy interaction in the power plant according to the power plant's energy allocation strategy, the method further includes: determining the energy allocation strategy based on the power plant's operating environment and / or system constraints. The energy allocation strategy includes a photovoltaic power generation priority allocation strategy, and the allocation order of the photovoltaic power generation priority allocation strategy is as follows: priority is given to the photovoltaic to load power supply path, then to the photovoltaic to battery charging path, and finally to the photovoltaic to grid power transmission path.

5. The method according to claim 4, characterized in that, include: When the photovoltaic power generation is less than or equal to the load power consumption, the power revenue generated by the photovoltaic to battery charging path and the photovoltaic to grid power transmission path is determined to be zero. When the photovoltaic power generation is greater than the load power but less than the sum of the load power and the battery's maximum charging power, the electricity revenue generated by the photovoltaic-to-grid power transmission path is determined to be zero. When the photovoltaic power generation is greater than or equal to the sum of the load power and the maximum charging power of the battery, the charging cost generated by the power grid to charge the battery is determined to be zero.

6. The method according to claim 3, characterized in that, When the scheduling benefit component is negative, the method further includes: Generate scheduling loss alarm information; Based on the scheduling loss alarm information and the loss paths involved in energy interaction in the power plant, loss paths are identified, and path scheduling and optimization are performed based on the loss paths.

7. A data processing apparatus, characterized in that, The device, used in an energy management system, includes: The acquisition module is used to acquire the operating data and electricity price base of the user-side photovoltaic energy storage grid-connected power station during a preset time period. The operating data includes the total grid-connected power, total power consumption, and total purchased power. The processing module is used to determine the mapping relationship between the operating data and the paths involved in energy interaction in the power station according to the power station's energy allocation strategy; The calculation module is used to determine the total revenue of the power station during the preset time period based on the mapping relationship and the electricity price base, using the revenue calculation model. The application of the revenue calculation model is constrained by the energy balance relationship of the power station, which is obtained based on the law of conservation of energy and the various paths involved in energy interaction in the power station.

8. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-6.

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