Power load prediction method, device, product, medium and system

Abstract

The invention provides a power load prediction method, device, product, medium and system, and the method comprises the steps: obtaining parameter information through the calculation of the population variation of a holiday region, the per capita reference load, the climate change impact factor, the historical reference air temperature, the current meteorological data and the current population flow information; main factors influencing load change in festivals and holidays are quantitatively considered, a power load prediction value is determined based on formula calculation, and compared with an existing method, the method has considerable real-time performance and accuracy, so that the problems that the power load in the festivals and holidays is often poor in historical data fitting, is easily influenced by random factors, and is poor in reliability are solved. A traditional load prediction method has a problem of limitation in a load prediction scene of a related holiday.

Description

Technical Field

[0001] The present application relates to the technical field of power systems, and in particular to a method, device, product, medium and system for predicting power load. Background Art

[0002] For power grid operation, the uncertainty during holidays will affect the overall power grid, making the power supply in related areas unstable. Therefore, how to accurately forecast the load during relevant holidays is particularly important for providing high-quality services to electricity users during holidays.

[0003] At present, the existing method to consider the impact of holidays is to determine the relationship between the predicted value and the influencing factor through regression analysis. Regression analysis is carried out through the relationship between many factors such as weather in power load forecasting and the predicted value. However, for holidays with non-fixed cycles and uncertain weather factors, the existing methods have limitations and cannot make accurate predictions. Summary of the invention

[0004] The main purpose of the present application is to provide a method, device, product, medium and system for predicting power load, so as to at least solve the problem that the power load forecasting of the existing scheme has uncertainty for non-fixed cycles and weather factors on holidays.

[0005] In order to achieve the above object, according to one aspect of the present application, a method for predicting power load is provided, comprising:

[0006] Obtaining the population change in the holiday area, per capita reference load, climate change influencing factors, historical reference temperature, current meteorological data and current population flow information, wherein the population change in the holiday area represents the population change in the preset area during the historical preset holidays and before the holidays, the per capita reference load represents the per capita reference load of the changed population in the preset holiday area, the climate change influencing factors represent the relationship between the per capita load and the temperature, the historical reference temperature represents the average temperature of the preset area during each preset holiday in history, the current meteorological data includes the temperature of the current preset area, and the current population flow information represents the current population flow data in the preset area;

[0007] The power load forecast value is determined based on the population change in the holiday area, the per capita reference load, the climate change influencing factor, the historical reference temperature, the current meteorological data and the current population flow information.

[0008] Optionally, determining the power load forecast value according to the population change in the holiday area, the per capita reference load, the climate change impact factor, the historical reference temperature, the current meteorological data and the current population flow information includes:

[0009] According to L=L B +[δ+θ(TT B )]×F, determine the power load forecast value,

[0010] Among them, L is the predicted value of power load, θ is the climate change impact factor, δ is the population change in the holiday area, F is the current population flow information, L B is the per capita reference load, T B is the historical reference temperature, and T is the current meteorological data.

[0011] Optionally, obtain the change in regional population during holidays, including:

[0012] Get the population during the preset holidays and the population before the preset holidays;

[0013] The population change in the holiday area is determined as the difference between the population during the preset holiday period and the population before the preset holiday period.

[0014] Optionally, obtain per capita reference load, including:

[0015] Obtain the power load during the preset holidays, the power load before the preset holidays, the population during the preset holidays, and the population before the preset holidays;

[0016] The per capita reference load is determined as a ratio of a first difference and a second difference, wherein the first difference is a difference between the power load during the preset holiday and the power load before the preset holiday, and the second difference is a difference between the population during the preset holiday and the population before the preset holiday.

[0017] Optionally, obtain climate change impact factors, including:

[0018] Obtain the per capita load during the preset holidays, the per capita load before the preset holidays, the temperature during the preset holidays, and the temperature before the preset holidays;

[0019] The climate change impact factor is determined as the ratio of the third difference and the fourth difference, the third difference being the difference between the per capita load during the preset holiday and the per capita load before the preset holiday, and the fourth difference being the difference between the temperature during the preset holiday and the temperature before the preset holiday.

[0020] Optionally, obtain current population mobility information, including:

[0021] Get the current inflow population and the current outflow population;

[0022] The current population flow information is determined as the difference between the current inflow population number and the current outflow population number.

[0023] According to another aspect of the present application, there is provided a device for predicting power load, comprising:

[0024] an acquisition unit, for acquiring a population change in a holiday region, a per capita reference load, a climate change influencing factor, a historical reference temperature, current meteorological data, and current population flow information, wherein the population change in the holiday region represents a population change in a preset region during a historical preset holiday and before a holiday, the per capita reference load represents a per capita reference load of a preset holiday region change, the climate change influencing factor represents a relationship between per capita load and temperature, the historical reference temperature represents an average temperature of the preset region during each preset holiday in history, the current meteorological data includes the temperature of the current preset region, and the current population flow information represents the current population flow data in the preset region;

[0025] A determination unit is used to determine the power load forecast value according to the population change in the holiday area, the per capita reference load, the climate change influencing factor, the historical reference temperature, the current meteorological data and the current population flow information.

[0026] According to another aspect of the present application, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the steps of any one of the methods described are implemented.

[0027] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute any one of the methods described.

[0028] According to another aspect of the present application, a power load prediction system is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include methods for executing any one of the described methods.

[0029] By applying the technical solution of the present application, parameter information is obtained by calculating the data of the population change in the holiday area, the per capita reference load, the climate change influencing factor, the historical reference temperature, the current meteorological data and the current population flow information, thereby quantitatively considering the main factors affecting the load change during the holidays, and finally determining the power load forecast value based on the formula calculation. Compared with the existing methods, it has considerable real-time and accuracy, and thus solves the problem that the power load on holidays often has a poor fit with historical data and is easily affected by random factors, and the traditional load forecasting method has limitations in the load forecasting scenarios of relevant holidays. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The drawings constituting part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0031] Figure 1 A hardware structure block diagram of a mobile terminal for executing a method for predicting power load provided in an embodiment of the present application is shown;

[0032] Figure 2 A structural block diagram of a power load prediction device provided according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0033] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0034] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0035] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0036] As introduced in the background technology, the prior art uses regression analysis to determine the relationship between the predicted value and the influencing factor. Regression analysis is carried out by analyzing the relationship between many factors such as weather in power load forecasting and the predicted value. However, for non-fixed cycles and weather factors that cause uncertainty during holidays, existing methods have limitations and cannot perform accurate predictions. In order to solve the problem that the uncertainty during holidays will affect the overall power grid and cause unstable power supply in related areas for the operation of the power grid, the embodiments of the present application provide a method, device, product, medium and system for predicting power load.

[0037] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0038] In this embodiment, a method for predicting power load is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0039] Figure 1 FIG. 1 is a flow chart of a method for predicting power load according to an embodiment of the present application. Figure 1 As shown, the method comprises the following steps:

[0040] Step S101, obtaining the population change amount in the holiday area, the per capita reference load, the climate change influencing factor, the historical reference temperature, the current meteorological data and the current population flow information, wherein the population change amount in the holiday area represents the population change amount in the preset area during the historical preset holidays and before the holidays, the per capita reference load represents the per capita reference load of the changed population in the preset holiday area, the climate change influencing factor represents the relationship between the per capita load and the temperature, the historical reference temperature represents the average temperature of the preset area during the preset holidays, the current meteorological data includes the temperature of the current preset area, and the current population flow information represents the current population flow data in the preset area;

[0041] Specifically, since the electricity load during holidays often has poor fit with historical data, it is easy to be affected by random factors in the application scenario of load forecasting; therefore, the population change in the holiday area, per capita reference load, climate change influencing factors, historical reference temperature, current meteorological data and current population flow information are considered to reduce the impact of random factors on electricity load forecasting;

[0042] In one embodiment of the present application, obtaining the change in regional population during holidays includes:

[0043] Get the population during the preset holidays and the population before the preset holidays;

[0044] The population change in the above holiday area is determined as the difference between the population during the preset holiday period and the population before the preset holiday.

[0045] Specifically, by determining the above-mentioned holiday area population change as the difference between the population during the preset holiday period and the population before the preset holiday period, the holiday area population change can represent the population change of the preset area during the historical preset holiday period and before the holiday period, thereby reducing the impact of random factors on the power load forecast;

[0046] In one embodiment of the present application, obtaining a per capita reference load includes:

[0047] Obtain the power load during the preset holidays, the power load before the preset holidays, the population during the preset holidays, and the population before the preset holidays;

[0048] The per capita reference load is determined as the ratio of a first difference to a second difference, wherein the first difference is the difference between the power load during the preset holidays and the power load before the preset holidays, and the second difference is the difference between the population during the preset holidays and the population before the preset holidays.

[0049] Specifically, by determining the per capita reference load as the ratio of the difference between the power load during the preset holiday and the power load before the preset holiday and the difference between the population during the preset holiday and the population before the preset holiday, the per capita reference load can represent the per capita reference load of the population change in the preset holiday area, thereby more accurately predicting the power load during the holiday and reducing the impact of random factors on the power load prediction;

[0050] In one embodiment of the present application, obtaining a climate change impact factor includes:

[0051] Obtain the per capita load during the preset holidays, the per capita load before the preset holidays, the temperature during the preset holidays, and the temperature before the preset holidays;

[0052] The above-mentioned climate change impact factor is determined as the ratio of the third difference and the fourth difference, the above-mentioned third difference is the difference between the per capita load during the above-mentioned preset holidays and the per capita load before the above-mentioned preset holidays, and the above-mentioned fourth difference is the difference between the temperature during the above-mentioned preset holidays and the temperature before the above-mentioned preset holidays.

[0053] Specifically, temperature changes may lead to drastic fluctuations in electricity demand. By determining the climate change impact factor as the ratio of the difference between the per capita load during the preset holiday and the per capita load before the preset holiday and the difference between the temperature during the preset holiday and the temperature before the preset holiday, the climate change impact factor can characterize the relationship between the per capita load and the temperature, thereby quantifying the impact of climate on power load forecasting and reducing the impact of random factors on power load forecasting;

[0054] In one embodiment of the present application, obtaining current population flow information includes:

[0055] Get the current inflow population and the current outflow population;

[0056] The current population flow information is determined as the difference between the current inflow population and the current outflow population.

[0057] Specifically, by determining the current population flow information as the difference between the current inflow population and the current outflow population, the current population flow information can represent the current population flow data in the preset area. For example, if the current inflow population is 2 and the current outflow population is 1, the difference is 1. Then, according to the current population flow information, the population flow data in the preset area is 1. Monitor population flow, so as to adjust power supply in time and reduce the impact of random factors on power load forecasting;

[0058] Step S102, determining the power load forecast value according to the above-mentioned holiday regional population change, the above-mentioned per capita reference load, the above-mentioned climate change impact factor, the above-mentioned historical reference temperature, the above-mentioned current meteorological data and the above-mentioned current population flow information.

[0059] Specifically, parameter information is calculated based on the above-mentioned regional population change during holidays, the above-mentioned per capita reference load, the above-mentioned climate change impact factor, the above-mentioned historical reference temperature, the above-mentioned current meteorological data and the above-mentioned current population flow information data, and substituted into the power load forecast value calculation formula to determine the power load forecast value, and the main factors affecting the load change during holidays are quantitatively considered;

[0060] In one embodiment of the present application, the power load forecast value is determined according to the population change in the holiday area, the per capita reference load, the climate change impact factor, the historical reference temperature, the current meteorological data and the current population flow information, including:

[0061] According to L=L B +[δ+θ(TT B )]×F, determine the above power load forecast value,

[0062] Among them, L is the above-mentioned power load forecast value, θ is the above-mentioned climate change impact factor, δ is the above-mentioned holiday regional population change, F is the above-mentioned current population flow information, L B is the above per capita reference load, T B is the above historical reference temperature, and T is the above current meteorological data.

[0063] Specifically, based on the parameter information calculated in step S201, as well as the real-time operator big data and meteorological real-time data before the holiday, the load change amount of the region during the holiday is calculated according to the above formula;

[0064] In the above steps, parameter information is calculated based on the data of the population change in the above-mentioned holiday area, the above-mentioned per capita reference load, the above-mentioned climate change influencing factors, the above-mentioned historical reference temperature, the above-mentioned current meteorological data and the above-mentioned current population flow information, so as to quantify the main factors affecting the load change during the above-mentioned holidays, and finally determine the power load forecast value based on the formula calculation. Compared with the existing methods, it has considerable real-time and accuracy, and thus solves the problem that the power load on holidays often has a poor fit with historical data and is easily affected by random factors, and the traditional load forecasting method has limitations in the load forecasting scenarios of relevant holidays.

[0065] Through the above embodiments, the uncertainty problem of existing power load forecasting schemes caused by non-fixed cycles and weather factors during holidays can be effectively solved, the prediction accuracy and reliability can be improved, and it is helpful to ensure the stability and security of power supply.

[0066] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0067] The embodiment of the present application also provides a prediction device for power load. It should be noted that the prediction device for power load of the embodiment of the present application can be used to execute the prediction method for power load provided by the embodiment of the present application. The device is used to implement the above-mentioned embodiments and preferred embodiments, and the descriptions have been omitted. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0068] The following is an introduction to the power load prediction device provided in the embodiments of the present application.

[0069] Figure 2 is a structural block diagram of a power load prediction device provided according to an embodiment of the present application. Figure 2 As shown, the device comprises:

[0070] The acquisition unit 21 is used to acquire the population change amount in the holiday area, the per capita reference load, the climate change impact factor, the historical reference temperature, the current meteorological data and the current population flow information, wherein the population change amount in the holiday area represents the population change amount in the preset area during the historical preset holidays and before the holidays, the per capita reference load represents the per capita reference load of the changed population in the preset holiday area, the climate change impact factor represents the relationship between the per capita load and the temperature, the historical reference temperature represents the average temperature of the preset area during the preset holidays, the current meteorological data includes the temperature of the current preset area, and the current population flow information represents the current population flow data in the preset area;

[0071] The determination unit 22 is used to determine the power load forecast value according to the above-mentioned holiday regional population change, the above-mentioned per capita reference load, the above-mentioned climate change impact factor, the above-mentioned historical reference temperature, the above-mentioned current meteorological data and the above-mentioned current population flow information.

[0072] In the above-mentioned device, parameter information is obtained by calculating the data of the population change in the above-mentioned holiday area, the above-mentioned per capita reference load, the above-mentioned climate change influencing factor, the above-mentioned historical reference temperature, the above-mentioned current meteorological data and the above-mentioned current population flow information, thereby quantitatively considering the main factors affecting the load change on the above-mentioned holidays, and finally determining the power load forecast value based on the formula calculation. Compared with the existing methods, it has considerable real-time and accuracy, and thus solves the problem that the power load on holidays often has a poor fit with historical data and is easily affected by random factors, and the traditional load forecasting method has limitations in the load forecasting scenarios of relevant holidays.

[0073] In one embodiment of the present application, the determining unit includes a first determining module,

[0074] The first determination module is used to determine the B +[δ+θ(TT B )]×F, determine the above power load forecast value,

[0075] Among them, L is the above-mentioned power load forecast value, θ is the above-mentioned climate change impact factor, δ is the above-mentioned holiday regional population change, F is the above-mentioned current population flow information, L B is the above per capita reference load, T B is the above historical reference temperature, and T is the above current meteorological data.

[0076] In one embodiment of the present application, the acquisition unit includes a first acquisition module and a second determination module.

[0077] The first acquisition module is used to obtain the population during the preset holidays and the population before the preset holidays;

[0078] The second determination module is used to determine the population change in the holiday area as the difference between the population during the preset holiday and the population before the preset holiday.

[0079] In one embodiment of the present application, the acquisition unit includes a second acquisition module and a third determination module.

[0080] The second acquisition module is used to acquire the power load during the preset holidays, the power load before the preset holidays, the population during the preset holidays, and the population before the preset holidays;

[0081] The third determination module is used to determine the above-mentioned per capita reference load as the ratio of the first difference and the second difference, the above-mentioned first difference is the difference between the power load during the above-mentioned preset holidays and the power load before the above-mentioned preset holidays, and the above-mentioned second difference is the difference between the population during the above-mentioned preset holidays and the population before the above-mentioned preset holidays.

[0082] In one embodiment of the present application, the acquisition unit includes a third acquisition module and a fourth determination module.

[0083] The third acquisition module is used to obtain the per capita load during the preset holidays, the per capita load before the preset holidays, the temperature during the preset holidays, and the temperature before the preset holidays;

[0084] The fourth determination module is used to determine the above-mentioned climate change impact factor as the ratio of the third difference and the fourth difference, the above-mentioned third difference is the difference between the per capita load during the above-mentioned preset holidays and the per capita load before the above-mentioned preset holidays, and the above-mentioned fourth difference is the difference between the temperature during the above-mentioned preset holidays and the temperature before the above-mentioned preset holidays.

[0085] In one embodiment of the present application, the acquisition unit includes a fourth acquisition module and a fifth determination module.

[0086] The fourth acquisition module is used to obtain the current inflow population and the current outflow population;

[0087] The fifth determination module is used to determine the current population flow information as the difference between the current inflow population number and the current outflow population number.

[0088] The above-mentioned power load prediction device includes a processor and a memory. The above-mentioned acquisition unit and determination unit are stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize the corresponding functions. The above-mentioned modules are all located in the same processor; or, the above-mentioned modules are located in different processors in any combination.

[0089] The processor contains a kernel, which calls the corresponding program unit from the memory. One or more kernels can be set. By adjusting the kernel parameters, the limitations of traditional load forecasting methods in holiday load forecasting scenarios can be solved. Accurately forecast the load during relevant holidays, and be fully prepared to provide high-quality services to electricity users during holidays.

[0090] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0091] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that is initialized with at least the following method steps: obtaining a population change in a holiday area, a per capita reference load, a climate change influencing factor, a historical reference temperature, current meteorological data, and current population flow information, wherein the population change in the holiday area represents the population change in the preset area during the historical preset holidays and before the holidays, the per capita reference load represents the per capita reference load of the changed population in the preset holiday area, the climate change influencing factor represents the relationship between the per capita load and the temperature, the historical reference temperature represents the average temperature of the preset area during each preset holiday in history, the current meteorological data includes the temperature of the current preset area, and the current population flow information represents the current population flow data in the preset area; and determining the power load forecast value based on the population change in the holiday area, the per capita reference load, the climate change influencing factor, the historical reference temperature, the current meteorological data, and the current population flow information.

[0092] An embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the power load prediction method.

[0093] The present application also provides a power load prediction system, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include means for executing any one of the above methods.

[0094] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, 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.

[0095] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0096] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0097] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0098] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0099] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0100] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0101] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0102] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0103] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0104] 1) The power load prediction method of the present application calculates parameter information based on the data of the above-mentioned holiday regional population change, the above-mentioned per capita reference load, the above-mentioned climate change influencing factors, the above-mentioned historical reference temperature, the above-mentioned current meteorological data and the above-mentioned current population flow information, thereby quantitatively considering the main factors affecting the load change during the above-mentioned holidays, and finally determining the power load prediction value based on the formula calculation. Compared with the existing methods, it has considerable real-time and accuracy, and thus solves the problem that the holiday power load often has a poor fit with historical data and is easily affected by random factors, and the traditional load forecasting method has limitations in the load forecasting scenarios of relevant holidays.

[0105] 2) The power load prediction device of the present application calculates parameter information based on the data of the above-mentioned holiday regional population change, the above-mentioned per capita reference load, the above-mentioned climate change influencing factor, the above-mentioned historical reference temperature, the above-mentioned current meteorological data and the above-mentioned current population flow information, thereby quantitatively considering the main factors affecting the load change during the above-mentioned holidays, and finally determining the power load prediction value based on the formula calculation. Compared with the existing methods, it has considerable real-time and accuracy, and thus solves the problem that the holiday power load often has a poor fit with historical data and is easily affected by random factors, and the traditional load prediction method has limitations in the load prediction scenarios of relevant holidays.

[0106] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for predicting power load, characterized in that: include: Obtaining the population change in the holiday area, per capita reference load, climate change influencing factors, historical reference temperature, current meteorological data and current population flow information, wherein the population change in the holiday area represents the population change in the preset area during the historical preset holidays and before the holidays, the per capita reference load represents the per capita reference load of the changed population in the preset holiday area, the climate change influencing factors represent the relationship between the per capita load and the temperature, the historical reference temperature represents the average temperature of the preset area during each preset holiday in history, the current meteorological data includes the temperature of the current preset area, and the current population flow information represents the current population flow data in the preset area; The power load forecast value is determined based on the population change in the holiday area, the per capita reference load, the climate change influencing factor, the historical reference temperature, the current meteorological data and the current population flow information.

2. The method according to claim 1, characterized in that Determining a power load forecast value according to the population change in the holiday area, the per capita reference load, the climate change impact factor, the historical reference temperature, the current meteorological data and the current population flow information includes: According to L=L B +[δ+θ(TT B )]×F, determine the power load forecast value, Among them, L is the predicted value of power load, θ is the climate change impact factor, δ is the population change in the holiday area, F is the current population flow information, L B is the per capita reference load, T B is the historical reference temperature, and T is the current meteorological data.

3. The method according to claim 1, characterized in that Get the population change in the holiday area, including: Get the population during the preset holidays and the population before the preset holidays; The population change in the holiday area is determined as the difference between the population during the preset holiday period and the population before the preset holiday period.

4. The method according to claim 1, characterized in that: Obtain per capita reference load, including: Obtain the power load during the preset holidays, the power load before the preset holidays, the population during the preset holidays, and the population before the preset holidays; The per capita reference load is determined as a ratio of a first difference and a second difference, wherein the first difference is a difference between the power load during the preset holiday and the power load before the preset holiday, and the second difference is a difference between the population during the preset holiday and the population before the preset holiday.

5. The method according to claim 1, characterized in that Obtain climate change impact factors, including: Obtain the per capita load during the preset holidays, the per capita load before the preset holidays, the temperature during the preset holidays, and the temperature before the preset holidays; The climate change impact factor is determined as the ratio of the third difference and the fourth difference, the third difference being the difference between the per capita load during the preset holiday and the per capita load before the preset holiday, and the fourth difference being the difference between the temperature during the preset holiday and the temperature before the preset holiday.

6. The method according to claim 1, characterized in that Get current population mobility information, including: Get the current inflow population and the current outflow population; The current population flow information is determined as the difference between the current inflow population number and the current outflow population number.

7. A power load prediction device, characterized in that: include: An acquisition unit is used to acquire a population change in a holiday area, a per capita reference load, a climate change influencing factor, a historical reference temperature, current meteorological data, and current population flow information, wherein the population change in the holiday area represents a population change in a preset area during a historical preset holiday and before a holiday, the per capita reference load represents a per capita reference load of a preset holiday area change, the climate change influencing factor represents a relationship between per capita load and temperature, the historical reference temperature represents an average temperature of the preset area during each preset holiday in history, the current meteorological data includes the temperature of the current preset area, and the current population flow information represents the current population flow data in the preset area; A determination unit is used to determine the power load forecast value according to the population change in the holiday area, the per capita reference load, the climate change influencing factor, the historical reference temperature, the current meteorological data and the current population flow information.

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

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 6.

10. A power load prediction system, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include methods for executing any one of claims 1 to 6.

Images