Electric charge subsidy calculation method and device, equipment and storage medium

Abstract

The invention discloses an electric charge subsidy calculation method and device, equipment and a storage medium, and relates to the technical field of power plants. The method comprises the steps of obtaining image data of a power plant and operation data of power generation equipment in the power plant; determining predicted power consumption of a power consumption area corresponding to the power plant according to the image data of the power plant and the operation data of power generation equipment in the power plant; and determining a power consumption difference according to the actual power consumption and the predicted power consumption of the power consumption area corresponding to the power plant, and determining an electric charge subsidy corresponding to the power plant according to the power consumption difference. According to the technical scheme of the embodiment of the invention, the accuracy of electric charge subsidy calculation can be improved, so that the user satisfaction is improved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the technical field of power plants, and in particular to a method, device, equipment and storage medium for calculating electricity subsidy. Background Art

[0002] With the transformation of the global energy structure and the development of the power market, virtual power plants, as a new type of distributed energy aggregation and management model, have gradually become an important part of the power system. In the operation of virtual power plants, effectively motivating users to participate in demand response has become a key link. Demand response refers to users actively adjusting their electricity consumption behavior based on the signals of the power grid to achieve the goals of peak shaving, balancing power grid supply and demand, and promoting the consumption of renewable energy. In order to encourage users to actively participate in demand response, it is crucial to design a reasonable incentive mechanism. Economic incentives are one of the most common methods. By giving users electricity subsidies or other forms of economic compensation, users are motivated to adjust their electricity consumption behavior. Among them, the calculation of electricity subsidies is a core component of economic incentives.

[0003] The traditional method of calculating electricity subsidies is mainly based on the total installed capacity of the power plant (i.e. the sum of the rated active power of all generating units), and the subsidy amount is determined according to a fixed amount and distributed to eligible users. Although this method is simple and easy to operate, it ignores the actual electricity consumption, decouples the subsidy amount from the actual electricity consumption, and leads to a mismatch between subsidy allocation and actual output, resulting in waste or unfairness of resources, reduced user satisfaction, and reduced users' enthusiasm for truly reducing electricity consumption in demand response.

[0004] Therefore, it is urgent to propose a new method to solve the above problems. Summary of the invention

[0005] The present invention provides an electricity fee subsidy calculation method, device, equipment and storage medium, which can improve the accuracy of electricity fee subsidy calculation, thereby improving user satisfaction.

[0006] In a first aspect, an embodiment of the present invention provides a method for calculating electricity fee subsidies, including:

[0007] Acquiring image data of a power plant and operating data of power generation equipment in the power plant;

[0008] Determining the predicted power consumption of the power plant for the power application area according to the image data of the power plant and the operating data of the power generation equipment in the power plant;

[0009] The power consumption difference is determined according to the actual power consumption of the power plant in the power application area and the predicted power consumption, and the electricity fee subsidy corresponding to the power plant is determined according to the power consumption difference.

[0010] The technical solution of the present invention obtains the image data of the power plant and the operating data of the power generation equipment in the power plant; determines the predicted power consumption of the power plant for the power application area according to the image data of the power plant and the operating data of the power generation equipment in the power plant; determines the power consumption difference according to the actual power consumption and the predicted power consumption of the power plant in the power application area, and determines the corresponding electricity subsidy of the power plant according to the power consumption difference. The above technical solution first obtains the image data of the power plant and the operating data of the power generation equipment in the power plant, and then determines the predicted power consumption of the power plant for the power application area according to the image data of the power plant and the operating data of the power generation equipment in the power plant, which can more comprehensively evaluate the operating status of the power plant and improve the accuracy of the determined predicted power consumption. Afterwards, the power consumption difference is determined according to the actual power consumption and the predicted power consumption of the power plant in the power application area, and the corresponding electricity subsidy of the power plant is determined according to the power consumption difference, and then the electricity subsidy can be distributed to each user in the power application area of ​​the power plant, thereby encouraging users to plan electricity consumption more reasonably, cultivating users' energy-saving awareness, and reducing unnecessary electricity consumption. Compared with the prior art which usually determines the subsidy amount as a fixed amount based on the total installed capacity of the power plant (i.e. the sum of the rated active power of all generating units), the present invention determines the predicted power consumption of the power plant for the power application area based on the image data of the power plant and the operating data of the power generation equipment in the power plant, and determines the power consumption difference based on the actual power consumption and the predicted power consumption of the power application area, and then determines the corresponding electricity subsidy for the power plant based on the power consumption difference, thereby ensuring that the electricity subsidy is closely related to the actual power consumption, rather than simply determined according to a fixed amount, thereby improving the accuracy of determining the electricity subsidy, and then the electricity subsidy can be distributed to each user in the power application area of ​​the power plant to improve user satisfaction, thereby encouraging users to plan their electricity consumption more reasonably, cultivating users' energy-saving awareness, and reducing unnecessary electricity consumption.

[0011] In a second aspect, an embodiment of the present invention further provides an electricity fee subsidy calculation device, the device comprising:

[0012] An acquisition module, used to acquire image data of a power plant and operation data of power generation equipment in the power plant;

[0013] A first determination module, configured to determine the predicted power consumption of the power plant for the power application area according to the image data of the power plant and the operation data of the power generation equipment in the power plant;

[0014] The second determination module is used to determine the power consumption difference according to the actual power consumption of the power plant in the power application area and the predicted power consumption, and determine the corresponding electricity fee subsidy for the power plant according to the power consumption difference.

[0015] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0016] at least one processor; and a memory communicatively coupled to the at least one processor;

[0017] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can implement any of the electricity subsidy calculation methods described in the first aspect.

[0018] In a fourth aspect, an embodiment of the present invention further provides a storage medium including computer executable instructions,

[0019] The computer executable instructions, when executed by a computer processor, implement any of the electricity fee subsidy calculation methods described in the first aspect.

[0020] It should be noted that the above-mentioned computer instructions may be stored in whole or in part on a computer-readable storage medium. The computer-readable storage medium may be packaged together with the processor of the electricity subsidy calculation device, or may be packaged separately from the processor of the electricity subsidy calculation device, and this application does not limit this.

[0021] The description of the second, third and fourth aspects in this application can refer to the detailed description of the first aspect; and the beneficial effects of the description of the second, third and fourth aspects can refer to the beneficial effect analysis of the first aspect, which will not be repeated here.

[0022] In this application, the name of the above-mentioned electricity subsidy calculation device does not limit the device or functional module itself. In actual implementation, these devices or functional modules may appear with other names. As long as the functions of each device or functional module are similar to those of this application, they belong to the scope of the claims of this application and their equivalent technologies.

[0023] These and other aspects of the present application will become more apparent from the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 A flow chart of a method for calculating electricity fee subsidies provided by an embodiment of the present invention;

[0026] Figure 2 A flowchart of another method for calculating electricity fee subsidies provided by an embodiment of the present invention;

[0027] Figure 3 A schematic diagram of the structure of an electricity fee subsidy calculation device provided by an embodiment of the present invention;

[0028] Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0030] The term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0031] The terms "first" and "second" and the like in the specification and drawings of this application are used to distinguish different objects, or to distinguish different processing of the same object, rather than to describe a specific order of objects.

[0032] In addition, the terms "including" and "having" and any variations thereof mentioned in the description of the present application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0033] It should be mentioned before discussing exemplary embodiments in more detail that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe various operations (or steps) as sequential processes, many operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of various operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to methods, functions, procedures, subroutines, subprograms, etc. In addition, the embodiments in the present invention and the features in the embodiments can be combined with each other without conflict.

[0034] It should be noted that, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0035] In the description of the present application, unless otherwise specified, “plurality” means two or more.

[0036] Figure 1 This is a flow chart of a method for calculating electricity subsidy provided by an embodiment of the present invention. This embodiment is applicable to the situation where it is necessary to calculate the electricity subsidy corresponding to the power plant. The method can be executed by an electricity subsidy calculation device, and specifically includes the following steps:

[0037] Step 110: Acquire image data of the power plant and operating data of power generation equipment in the power plant.

[0038] Among them, a power plant refers to a factory that produces electric energy. It converts primary energy into electric energy through different energy conversion methods. It is an important part of the power system and is responsible for providing a stable and reliable power supply to the power grid. The image data of a power plant refers to the image data of the power plant and its surrounding environment obtained through satellite remote sensing technology. For example, the image data of a power plant can be a photo of the appearance of the power plant equipment. Power generation equipment refers to mechanical equipment used in a power plant to convert various forms of energy into electric energy. For example, power generation equipment can be a boiler, steam turbine, generator, water turbine, wind turbine and / or solar panel, etc. The operating data of the power generation equipment in the power plant refers to the various parameters generated by the power generation equipment during the operation of the power plant. For example, the operating data of the power generation equipment in the power plant can be the operating temperature, power, current, voltage and other data of the equipment.

[0039] Specifically, the image data of the power plant captured by the satellite can be obtained through the satellite's ground receiving station, and the operating data of the power generation equipment can be obtained through various sensors installed on the power generation equipment (such as temperature sensors, pressure sensors, vibration sensors, current sensors, etc.).

[0040] In this embodiment, by acquiring the image data of the power plant and the operation data of the power generation equipment in the power plant, a data basis is provided for subsequently determining the predicted power consumption of the power plant for the power application area.

[0041] Step 120: Determine the predicted power consumption of the power plant for the power application area based on the image data of the power plant and the operating data of the power generation equipment in the power plant.

[0042] Among them, the power plant's power application area refers to the geographical scope of the power supply provided by the power plant to the power consumption area through the power grid. The predicted power consumption of the power plant to the power application area refers to the total predicted power consumption of each user in the power application area by the power plant. Specifically, after obtaining the image data of the power plant and the operating data of the power generation equipment in the power plant, the collected image data can be pre-processed based on image recognition, feature extraction, etc. to obtain useful information from the image data and obtain image feature data. And the operating data of the power generation equipment is pre-processed based on cleaning, denoising, normalization, etc. to obtain operating feature data to ensure the accuracy and consistency of the operating data. After that, a suitable prediction method can be selected according to the actual situation and needs. For example, the prediction method can be time series analysis, regression analysis, machine learning algorithm, etc. Then, the selected prediction method is applied to process the image feature data and the operating feature data to obtain the predicted power consumption of the power plant to the power application area.

[0043] Exemplarily, if the selected prediction method is regression analysis, the dependent variable can be determined as the predicted power consumption of the power plant for the application area, and the independent variable can be the image data of the power plant and the operating data of the power generation equipment in the power plant, or it can be the image feature data and the operating feature data. Then select a suitable regression model according to the characteristics of the data and the prediction requirements, for example: the regression model can be linear regression, polynomial regression, ridge regression or Lasso regression, etc. Then use historical data (historical image data of the power plant, historical operating data of the power generation equipment in the power plant, and historical power consumption of the power plant for the application area) to train the selected regression model to learn the relationship between the independent variable and the dependent variable. Finally, the obtained image data of the power plant and the operating data of the power generation equipment in the power plant, or the image feature data and the operating feature data are input into the trained regression model, so that the regression model processes the image data of the power plant and the operating data of the power generation equipment in the power plant, or the image feature data and the operating feature data, and obtains the predicted power consumption of the power plant for the application area.

[0044] In this embodiment, the predicted power consumption of the power plant for the power application area is determined through the image data of the power plant and the operating data of the power generation equipment in the power plant, which can more comprehensively evaluate the operating status of the power plant and improve the accuracy of the determined predicted power consumption.

[0045] Step 130: determine the difference in electricity consumption according to the actual electricity consumption and the predicted electricity consumption of the power plant in the power application area, and determine the corresponding electricity fee subsidy for the power plant according to the electricity consumption difference.

[0046] The actual electricity consumption of the power plant in the power application area refers to the total actual electricity consumption of each user in the power application area. The power consumption difference refers to the difference between the actual power consumption and the predicted power consumption. The electricity fee subsidy refers to the financial subsidy provided by the government or power company to users in the power application area in order to encourage the power plant to actively participate in demand response (according to the signal of the power grid, actively adjust their own electricity consumption behavior to achieve the purpose of peak shaving, balancing the supply and demand of the power grid, and promoting the consumption of renewable energy).

[0047] Specifically, after obtaining the actual power consumption and predicted power consumption of the power plant in the power application area, the power consumption difference can be determined based on the actual power consumption and predicted power consumption of the power plant in the power application area. In practical applications, it can be determined that the power consumption difference = predicted power consumption - actual power consumption. Then, the corresponding electricity subsidy of the power plant can be determined based on the product of the power consumption difference and the subsidized electricity price. In practical applications, it can be determined that the corresponding electricity subsidy of the power plant = power consumption difference × subsidized electricity price.

[0048] In this embodiment, the electricity consumption difference is determined based on the actual electricity consumption and predicted electricity consumption in the power application area of ​​the power plant, and the corresponding electricity subsidy of the power plant is determined based on the electricity consumption difference. The electricity subsidy can then be distributed to each user in the power application area of ​​the power plant, thereby encouraging users to plan electricity consumption more reasonably, cultivating users' energy-saving awareness, and reducing unnecessary electricity consumption.

[0049] In the embodiment of the present invention, the image data of the power plant and the operating data of the power generation equipment in the power plant are first obtained, and then the predicted power consumption of the power plant for the power application area is determined based on the image data of the power plant and the operating data of the power generation equipment in the power plant, which can more comprehensively evaluate the operating status of the power plant and improve the accuracy of the determined predicted power consumption. After that, the power consumption difference is determined based on the actual power consumption and the predicted power consumption of the power plant for the power application area, and the corresponding electricity subsidy of the power plant is determined based on the power consumption difference. After that, the electricity subsidy can be distributed to each user in the power application area of ​​the power plant, thereby encouraging users to plan their electricity consumption more reasonably, cultivating users' energy-saving awareness, and reducing unnecessary power consumption. Compared with the prior art which usually determines the subsidy amount as a fixed amount based on the total installed capacity of the power plant (i.e. the sum of the rated active power of all generating units), the present invention determines the predicted power consumption of the power plant for the power application area based on the image data of the power plant and the operating data of the power generation equipment in the power plant, and determines the power consumption difference based on the actual power consumption and the predicted power consumption of the power application area, and then determines the corresponding electricity subsidy for the power plant based on the power consumption difference, thereby ensuring that the electricity subsidy is closely related to the actual power consumption, rather than simply determined according to a fixed amount, thereby improving the accuracy of determining the electricity subsidy, and then the electricity subsidy can be distributed to each user in the power application area of ​​the power plant to improve user satisfaction, thereby encouraging users to plan their electricity consumption more reasonably, cultivating users' energy-saving awareness, and reducing unnecessary electricity consumption.

[0050] Figure 2 A flowchart of another method for calculating electricity subsidy provided by an embodiment of the present invention. This embodiment is specific based on the above embodiment. In this embodiment, the method may also include:

[0051] Step 210: Acquire image data of the power plant and operation data of power generation equipment in the power plant.

[0052] Step 211: Determine various environmental information of the power plant according to the image data.

[0053] The environmental information refers to the information describing the environmental status of the power plant, for example, the environmental information may be weather information and personnel entry and exit information.

[0054] Specifically, after obtaining the image data, the image data can be preprocessed based on radiation correction, geometric correction and image cropping to eliminate atmospheric effects and ensure the accuracy of geographic coordinates, thereby obtaining an image portion containing the power plant and its surrounding environment. Then, the features of each environmental information can be extracted from the preprocessed image through a feature extraction algorithm to obtain the environmental information of the power plant. For example, the feature extraction algorithm can be a threshold segmentation algorithm, an edge detection algorithm, a maximum likelihood method, a support vector machine, a random forest or a target detection algorithm.

[0055] Exemplarily, if the environmental information is information about people entering and exiting, a target detection algorithm can be used to identify a human target in the image from the preprocessed image, and then the movement path of the person can be analyzed to determine the person's entry and exit information.

[0056] For example, if the environmental information is weather information, the pre-processed image can be classified and analyzed by remote sensing image processing software to identify key meteorological elements such as cloud system, water vapor, temperature, etc. Then, by analyzing these key meteorological elements, the type and intensity of the weather can be determined to obtain weather information.

[0057] In this embodiment, various environmental information of the power plant is determined based on the image data, which provides a data basis for subsequently determining the target environmental information of the power plant.

[0058] Step 212: Determine target environmental information of the power plant according to various environmental information of the power plant and weights of various environmental information.

[0059] The target environmental information refers to the key environmental parameters determined based on the environmental information of the power plant and the weights of each environmental information, which helps calculate the predicted power consumption of the power plant in the application area.

[0060] Specifically, since different environmental information has different dimensions and ranges, before determining the target environmental information of the power plant based on the environmental information of the power plant and the weight of each environmental information, all environmental information can be quantified and normalized according to the actual situation or needs to ensure that they are on the same scale. For each environmental information, a weight can be assigned to it in advance according to the actual situation or needs. Then, the target environmental information of the power plant is determined based on the environmental information of the power plant and the weight of each environmental information. In actual applications, the calculation formula of the target environmental information can be as follows:

[0061]

[0062] Among them, Q represents the target environment information, I represents the environment information, a represents the weight corresponding to the environment information, n represents the number of environment information, and i represents the i-th environment information.

[0063] Exemplarily, if the environmental information is weather information and personnel entry and exit information, the weather information takes a value of 1 when it is sunny, otherwise it takes a value of 0, the value of the personnel entry and exit information is the ratio of the number of employees entering and exiting the power plant to the total number of employees, the weight of the weather information is 0.6, and the weight of the personnel entry and exit information is 0.4. When the weather information is sunny and the personnel entry and exit information is that the number of employees entering and exiting the power plant is 30% of the total number of employees, it can be determined that the target environmental information is 1×0.6+0.3×0.4=0.72.

[0064] In this embodiment, the target environmental information of the power plant is determined by various environmental information of the power plant and the weight of each environmental information, which provides a data basis for subsequently constructing a power plant data matrix corresponding to the power plant.

[0065] Step 213: construct a power plant data matrix corresponding to the power plant according to the operating data of the power generation equipment in the power plant within a preset time period and the target environment information of the power plant.

[0066] The preset time period is a time period set in advance according to actual conditions or needs when collecting data, for example, the preset time period is 12 hours, 1 day or one week, etc. The power plant data matrix is ​​a two-dimensional data structure used to store and represent various operating data and target environmental information of the power plant within the preset time period.

[0067] Specifically, after obtaining the operating data of the power generation equipment in the power plant and the target environment information of the power plant within the preset time period, a power plant data matrix corresponding to the power plant can be constructed based on the preset construction rules according to the operating data of the power generation equipment in the power plant and the target environment information of the power plant within the preset time period. For example: the preset construction rule is that each row in the matrix represents the operating data of the power generation equipment in the power plant and the target environment information of the power plant at a specific time point, and each column in the matrix represents the operating data of the power generation equipment in the power plant at different time points and the target environment information of the power plant at different time points.

[0068] In this embodiment, a power plant data matrix corresponding to the power plant is constructed based on the operating data of the power generation equipment in the power plant within a preset time period and the target environmental information of the power plant, providing a data basis for subsequently determining the predicted power consumption of the power plant for the power application area.

[0069] Step 214: input the power plant data matrix into a pre-trained power forecasting model to obtain the power plant's predicted power consumption for the power application area.

[0070] The pre-trained electricity prediction model is a model obtained after training based on historical image data of the power plant, historical operation data of power generation equipment in the power plant, and historical electricity consumption of the power plant in the power application area.

[0071] Specifically, after constructing the power plant data matrix corresponding to the power plant, the constructed power plant data matrix can be input into the pre-trained power prediction model. Since the power prediction model is a model obtained after training based on the historical image data of the power plant, the historical operation data of the power generation equipment in the power plant and the historical power consumption of the power plant in the power application area, and the power plant data matrix is ​​obtained based on the image data of the power plant and the operation data of the power generation equipment in the power plant, the power prediction model can obtain the predicted power consumption of the power plant in the power application area based on the power plant data matrix.

[0072] In this embodiment, the predicted power consumption of the power plant for the power application area is determined according to a pre-trained power prediction model, which can improve the prediction accuracy.

[0073] Furthermore, the training process of the power prediction model includes: obtaining historical image data of the power plant, historical operation data of the power generation equipment in the power plant, and historical power consumption of the power plant in the power application area; using the historical image data of the power plant, historical operation data of the power generation equipment in the power plant, and historical power consumption of the power plant in the power application area as training data to train the deep learning model, and calculate the loss function; optimizing the model based on the back propagation algorithm until the loss function converges to obtain the power prediction model.

[0074] Specifically, the historical image data of the power plant, the historical operation data of the power generation equipment in the power plant, and the historical power consumption of the power plant in the application area are first obtained. These data are cleaned and preprocessed to ensure that they meet the input requirements of the model. Then the acquired historical image data of the power plant, the historical operation data of the power generation equipment in the power plant, and the historical power consumption of the power plant in the application area are used as training data to train the deep learning model. This process usually includes two steps: forward propagation and back propagation. Forward propagation is to obtain the prediction result through the model of the input data, and then calculate the loss between the prediction result and the true target. Back propagation is to update the parameters of the model according to the loss function to reduce the gap between the prediction result and the true target. The deep learning model can be CornerNet, FCOS, RetinaNet, YolV7, etc., and the embodiment of the present invention is not limited to this. Finally, the model can be optimized based on the back propagation algorithm until the loss function converges, thereby obtaining a power prediction model. For example: the gradient descent method or Adam can be selected to determine hyperparameters such as the learning rate in order to optimize the model.

[0075] In this embodiment, the power prediction model is trained by using the historical image data of the power plant, the historical operation data of the power generation equipment in the power plant, and the historical power consumption of the power plant for the power application area, so that the power prediction model can be used to determine the predicted power consumption of the power plant for the power application area based on the power plant data matrix corresponding to the power plant.

[0076] Step 215: Determine the power consumption difference according to the actual power consumption and predicted power consumption of the power plant in the power application area.

[0077] Specifically, after obtaining the actual power consumption and predicted power consumption of the power plant for the power application area, the power consumption difference can be determined based on the actual power consumption and predicted power consumption of the power plant for the power application area. In actual applications, it can be determined that the power consumption difference = predicted power consumption - actual power consumption. For example: if the predicted power consumption of the power plant for the power application area is 1 million kWh, and the actual power consumption of the power plant for the power application area is 900,000 kWh, then the power consumption difference is 100,000 kWh.

[0078] Step 216: Calculate the product of the power consumption difference and the subsidized electricity price to obtain the electricity fee subsidy for the power plant to the users in the power consumption area.

[0079] Among them, subsidized electricity prices refer to electricity prices set by the government or relevant agencies in order to encourage users to use electricity rationally, actively cultivate energy-saving awareness, and reduce unnecessary electricity consumption.

[0080] Specifically, after obtaining the electricity consumption difference, the electricity subsidy for the power plant to users in the power application area can be determined based on the product of the electricity consumption difference and the subsidized electricity price. In actual applications, the electricity subsidy for the power plant to users in the power application area = electricity consumption difference × subsidized electricity price. After obtaining the electricity subsidy for the power plant to users in the power application area, it can be allocated to each user in the power plant's power application area. In actual applications, the electricity subsidy for each user = the electricity subsidy for the power plant to users in the power application area ÷ the total number of users. It should be noted that if the calculated electricity subsidy for the power plant to users in the power application area is less than or equal to zero, the power plant will not subsidize users in the power application area.

[0081] In this embodiment, by calculating the product of the electricity consumption difference and the subsidized electricity price, the electricity subsidy for users within the power application area of ​​the power plant is obtained, and the subsidy is distributed to users within the power application area of ​​the power plant. This can encourage users to plan their electricity consumption more reasonably, cultivate users' energy-saving awareness, and reduce unnecessary electricity consumption.

[0082] Furthermore, after step 216, the method further includes: adjusting the subsidized electricity price according to the electricity subsidy corresponding to the power plant.

[0083] Specifically, a subsidy threshold can be set according to actual conditions or needs. If the electricity subsidy corresponding to the power plant is greater than the subsidy threshold, the subsidized electricity price will be reduced to avoid financial pressure caused by excessive subsidies. If the electricity subsidy corresponding to the power plant is less than the subsidy threshold, the subsidized electricity price will be increased to encourage users to plan electricity use more reasonably and reduce unnecessary electricity consumption. If the electricity subsidy corresponding to the power plant is equal to the subsidy threshold, the subsidized electricity price will not be adjusted.

[0084] Furthermore, after step 216, the method further includes: generating a subsidy report according to the actual power consumption of the power plant in the power application area, the predicted power consumption of the power plant in the power application area, and the corresponding electricity subsidy of the power plant.

[0085] Among them, the subsidy report includes but is not limited to the name of the power plant, the geographical scope of the power plant's power application area, the actual electricity consumption data of the power plant's power application area during the reporting period, the predicted electricity consumption data, the power plant's corresponding electricity subsidy, the subsidy allocation principles and the subsidy amount received by each user.

[0086] Specifically, after obtaining the electricity subsidy corresponding to the power plant, a subsidy report can be generated based on the actual power consumption of the power plant in the power application area, the predicted power consumption of the power plant in the power application area, and the electricity subsidy corresponding to the power plant. The subsidy report can then be sent to the terminal held by the staff through the server. The terminal can be a tablet, a mobile phone, or a computer, and the embodiment of the present invention is not limited to this. The subsidy report can also be displayed in the terminal held by the staff based on a preset method. For example: the subsidy report can be displayed in the form of a chart, an image, or text. The staff can refer to the subsidy report to adjust the subsidy standard, subsidy scope, subsidy method, etc.

[0087] In this embodiment, by generating a subsidy report, it helps the staff to better understand the current electricity consumption situation and the implementation effect of the subsidy policy, and adjust the subsidy standards, subsidy scope and subsidy method according to the subsidy report, thereby encouraging users to use electricity reasonably and reduce unnecessary electricity consumption.

[0088] Therefore, the technical solution of the present invention first obtains the image data of the power plant and the operating data of the power generation equipment in the power plant, then determines the various environmental information of the power plant based on the image data, and determines the target environmental information of the power plant based on the various environmental information of the power plant and the weight of each environmental information, and then constructs the power plant data matrix corresponding to the power plant according to the operating data of the power generation equipment in the power plant and the target environmental information of the power plant within a preset time period, and then inputs the power plant data matrix into the pre-trained power prediction model to obtain the predicted power consumption of the power plant for the power application area, thereby improving the prediction accuracy. Afterwards, the power consumption difference is determined based on the actual power consumption and predicted power consumption of the power plant for the power application area, and the product of the power consumption difference and the subsidized electricity price is calculated to obtain the electricity fee subsidy for the power plant for users in the power application area, and the subsidy is distributed to the power plant for users in the power application area, which can encourage users to plan their power consumption more reasonably, cultivate users' energy-saving awareness, and reduce unnecessary power consumption. Compared with the prior art which usually determines the subsidy amount as a fixed amount based on the total installed capacity of the power plant (i.e. the sum of the rated active power of all generating units), the present invention determines the predicted electricity consumption of the power plant for the power application area based on the image data of the power plant and the operating data of the power generation equipment in the power plant, and determines the electricity consumption difference based on the actual electricity consumption and the predicted electricity consumption of the power plant for the power application area, and then determines the electricity fee subsidy for the users in the power application area from the power plant based on the electricity consumption difference, thereby ensuring that the electricity fee subsidy is closely related to the actual electricity consumption, rather than simply being determined according to a fixed amount, thereby improving the accuracy of determining the electricity fee subsidy, and then the electricity fee subsidy can be distributed to each user in the power application area of ​​the power plant to improve user satisfaction, thereby encouraging users to plan their electricity consumption more reasonably, cultivating users' energy-saving awareness, and reducing unnecessary electricity consumption.

[0089] Moreover, by training the power prediction model, the power prediction model can be used to determine the predicted power consumption of the power plant for the power application area according to the power plant data matrix corresponding to the power plant.

[0090] In addition, adjusting the subsidized electricity price according to the corresponding electricity subsidy of the power plant can not only avoid the financial pressure caused by excessive subsidies, but also encourage users to plan their electricity use more reasonably and reduce unnecessary electricity consumption.

[0091] On the other hand, generating a subsidy report based on the actual electricity consumption of the power plant in the power application area, the power plant's predicted electricity consumption in the power application area and the power plant's corresponding electricity fee subsidy will help staff better understand the current electricity consumption situation and the implementation effect of the subsidy policy, and adjust the subsidy standards, subsidy scope and subsidy methods based on the subsidy report, thereby encouraging users to use electricity reasonably and reduce unnecessary electricity consumption.

[0092] Figure 3 A schematic diagram of the structure of an electricity subsidy calculation device provided in an embodiment of the present invention. The device and the electricity subsidy calculation methods of the above-mentioned embodiments belong to the same inventive concept. For details not fully described in the embodiments of the electricity subsidy calculation device, reference can be made to the embodiments of the above-mentioned electricity subsidy calculation methods.

[0093] like Figure 3 As shown, the device comprises:

[0094] An acquisition module 310 is used to acquire image data of a power plant and operation data of power generation equipment in the power plant;

[0095] A first determination module 320, configured to determine the predicted power consumption of the power plant for the power application area according to the image data of the power plant and the operation data of the power generation equipment in the power plant;

[0096] The second determination module 330 is used to determine the power consumption difference according to the actual power consumption of the power plant in the power application area and the predicted power consumption, and determine the electricity fee subsidy corresponding to the power plant according to the power consumption difference.

[0097] Based on the above embodiment, the device further includes:

[0098] The third determination module is used to determine various environmental information of the power plant according to the image data after acquiring the image data of the power plant; and determine the target environmental information of the power plant according to the various environmental information of the power plant and the weight of each environmental information.

[0099] Based on the above embodiment, the second determining module 330 is specifically used for:

[0100] Constructing a power plant data matrix corresponding to the power plant according to the operating data of the power generation equipment in the power plant within a preset time period and the target environment information of the power plant;

[0101] The power plant data matrix is ​​input into a pre-trained power consumption prediction model to obtain the predicted power consumption of the power plant for the power application area.

[0102] Based on the above embodiment, the training process of the power prediction model includes:

[0103] Acquire historical image data of the power plant, historical operation data of the power generation equipment in the power plant, and historical power consumption of the power plant in the power application area;

[0104] Using historical image data of the power plant, historical operation data of power generation equipment in the power plant, and historical power consumption of the power plant in the power application area as training data to train the deep learning model, and calculate the loss function;

[0105] The model is optimized based on the back propagation algorithm until the loss function converges to obtain the power prediction model.

[0106] On the basis of the above embodiment, determining the electricity subsidy corresponding to the power plant according to the electricity consumption difference includes:

[0107] The product of the electricity consumption difference and the subsidized electricity price is calculated to obtain the electricity fee subsidy for the power plant to the users in the power application area.

[0108] Based on the above embodiment, the device further includes:

[0109] An adjustment module is used to adjust the subsidized electricity price according to the electricity subsidy corresponding to the power plant after determining the electricity subsidy corresponding to the power plant according to the electricity consumption difference.

[0110] Based on the above embodiment, the device further includes:

[0111] The reporting module is used to generate a subsidy report based on the actual electricity consumption of the power plant in the power application area, the predicted electricity consumption of the power plant in the power application area and the electricity subsidy corresponding to the power plant after determining the electricity subsidy corresponding to the power plant according to the electricity consumption difference.

[0112] The electricity subsidy calculation device provided in the embodiment of the present invention can execute the electricity subsidy calculation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0113] It is worth noting that in the embodiment of the above-mentioned electricity subsidy calculation device, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0114] Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Figure 4 A block diagram of an exemplary electronic device 4 suitable for implementing embodiments of the present invention is shown. Figure 4 The electronic device 4 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0115] like Figure 4 As shown, the electronic device 4 is in the form of a general purpose computing electronic device. The components of the electronic device 4 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 connecting different system components (including the system memory 28 and the processing unit 16).

[0116] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0117] The electronic device 4 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 4, including volatile and non-volatile media, removable and non-removable media.

[0118] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 4 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 4 not shown, usually called a "hard drive"). Although Figure 4Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0119] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0120] The electronic device 4 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), one or more devices that enable a user to interact with the electronic device 4, and / or any device that enables the electronic device 4 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via an input / output (I / O) interface 22. Furthermore, the electronic device 4 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 20. Figure 4 As shown, the network adapter 20 communicates with other modules of the electronic device 4 via the bus 18. It should be understood that although Figure 4 Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 4, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0121] The processing unit 16 executes various functional applications and page displays by running the program stored in the system memory 28, for example, implementing the electricity subsidy calculation method provided in the embodiment of the present invention, which includes:

[0122] Acquiring image data of a power plant and operating data of power generation equipment in the power plant;

[0123] Determining the predicted power consumption of the power plant for the power application area according to the image data of the power plant and the operating data of the power generation equipment in the power plant;

[0124] The power consumption difference is determined according to the actual power consumption of the power plant in the power application area and the predicted power consumption, and the electricity fee subsidy corresponding to the power plant is determined according to the power consumption difference.

[0125] Of course, those skilled in the art can understand that the processor can also implement the technical solution of the electricity subsidy calculation method provided in any embodiment of the present invention.

[0126] An embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method for calculating electricity subsidy provided by an embodiment of the present invention is implemented. The method includes:

[0127] Acquiring image data of a power plant and operating data of power generation equipment in the power plant;

[0128] Determining the predicted power consumption of the power plant for the power application area according to the image data of the power plant and the operating data of the power generation equipment in the power plant;

[0129] The power consumption difference is determined according to the actual power consumption of the power plant in the power application area and the predicted power consumption, and the electricity fee subsidy corresponding to the power plant is determined according to the power consumption difference.

[0130] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0131] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0132] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0133] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0134] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, optionally, they can be implemented by a program code executable by a computer device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0135] In addition, the acquisition, storage, use, and processing of data in the technical solution of the present invention are in compliance with the relevant provisions of national laws and regulations.

[0136] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for calculating electricity fee subsidy, characterized in that: The method comprises: Acquiring image data of a power plant and operating data of power generation equipment in the power plant; Determining the predicted power consumption of the power plant for the power application area according to the image data of the power plant and the operating data of the power generation equipment in the power plant; The power consumption difference is determined according to the actual power consumption of the power plant in the power application area and the predicted power consumption, and the electricity fee subsidy corresponding to the power plant is determined according to the power consumption difference.

2. The method for calculating electricity fee subsidy according to claim 1, characterized in that: After acquiring the image data of the power plant, it also includes: Determine various environmental information of the power plant according to the image data; The target environmental information of the power plant is determined according to each piece of environmental information of the power plant and a weight of each piece of environmental information.

3. The method for calculating electricity subsidy according to claim 2, characterized in that: Determining the predicted power consumption of the power plant for the power application area according to the image data of the power plant and the operating data of the power generation equipment in the power plant includes: Constructing a power plant data matrix corresponding to the power plant according to the operating data of the power generation equipment in the power plant within a preset time period and the target environment information of the power plant; The power plant data matrix is ​​input into a pre-trained power consumption prediction model to obtain the predicted power consumption of the power plant for the power application area.

4. The method for calculating electricity fee subsidy according to claim 3, characterized in that: The training process of the power prediction model includes: Acquire historical image data of the power plant, historical operation data of the power generation equipment in the power plant, and historical power consumption of the power plant in the power application area; Using historical image data of the power plant, historical operation data of power generation equipment in the power plant, and historical power consumption of the power plant in the power application area as training data to train the deep learning model, and calculate the loss function; The model is optimized based on the back propagation algorithm until the loss function converges to obtain the power prediction model.

5. The method for calculating electricity fee subsidy according to claim 1, characterized in that: Determining the electricity fee subsidy corresponding to the power plant according to the electricity consumption difference includes: The product of the electricity consumption difference and the subsidized electricity price is calculated to obtain the electricity fee subsidy for the power plant to the users in the power application area.

6. The method for calculating electricity fee subsidy according to claim 5, characterized in that: After determining the electricity subsidy corresponding to the power plant according to the electricity consumption difference, the method further includes: The subsidized electricity price is adjusted according to the electricity subsidy corresponding to the power plant.

7. The method for calculating electricity subsidy according to claim 1, characterized in that: After determining the electricity subsidy corresponding to the power plant according to the electricity consumption difference, the method further includes: A subsidy report is generated according to the actual power consumption of the power plant in the power application area, the predicted power consumption of the power plant in the power application area and the electricity subsidy corresponding to the power plant.

8. An electricity fee subsidy calculation device, characterized in that: The device comprises: An acquisition module, used to acquire image data of a power plant and operation data of power generation equipment in the power plant; A first determination module, configured to determine the predicted power consumption of the power plant for the power application area according to the image data of the power plant and the operation data of the power generation equipment in the power plant; The second determination module is used to determine the power consumption difference according to the actual power consumption of the power plant in the power application area and the predicted power consumption, and determine the corresponding electricity fee subsidy for the power plant according to the power consumption difference.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the electricity subsidy calculation method described in any one of claims 1-7.

10. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions, when executed by a computer processor, implement the electricity fee subsidy calculation method described in any one of claims 1 to 7.

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