Electricity utilization planning scheme generation method and device, computer equipment and storage medium

Abstract

The invention discloses a power utilization planning scheme generation method and device, computer equipment and a storage medium. The method comprises the steps that a user power utilization data set is acquired; according to the user power consumption data set, identifying power consumption peak time periods and power consumption valley time periods of the user at different time scales; identifying a target energy-consuming electric appliance according to the power utilization peak period and the power utilization valley period at different time scales; a power utilization planning scheme is generated according to the power utilization peak time period, the power utilization valley time period and the target energy consumption electric appliance, and the power utilization peak time period and the power utilization valley time period of the user at different time scales are accurately identified through the user power utilization data set, so that the power utilization behavior of the user can be known; according to the method, the power consumption peak time period and the power consumption valley time period are identified, the target energy consumption electric appliances in the power consumption peak time period and the power consumption valley time period are identified, a personalized power consumption planning scheme is generated for the user based on the power consumption peak time period, the power consumption valley time period and the target energy consumption electric appliances, the user is helped to optimize the power consumption behavior, the electric charge is reduced, and the energy utilization efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power consumption data processing, and in particular to a method, device, computer equipment and storage medium for generating a power consumption planning scheme. Background Art

[0002] At present, with the development of economy, people's living standards are improving, various household appliances have entered thousands of households, high-power equipment is increasing, and electricity consumption is also increasing.

[0003] Although the electricity bills provided by current power supply companies include basic information such as electricity consumption, electricity fee amount, and billing cycle, it is still difficult for users to fully understand their electricity usage behavior through this information. For example, it is not clear which electrical equipment consumes more electricity, and it is impossible to accurately plan electricity consumption, resulting in high electricity costs. Summary of the invention

[0004] The present application proposes a method, device, computer equipment and storage medium for generating an electricity consumption planning scheme, which improves the accuracy of electricity consumption planning and thus helps to reduce electricity costs.

[0005] In a first aspect, a method for generating a power consumption planning scheme is provided, comprising:

[0006] Obtain user electricity consumption data set;

[0007] Identify the user's peak electricity consumption period and the user's low electricity consumption period at different time scales according to the user's electricity consumption data set;

[0008] Identify target energy-consuming appliances based on peak and valley periods of electricity consumption at different time scales;

[0009] A power consumption planning scheme is generated according to the power consumption peak period, the power consumption valley period and the target energy-consuming electrical appliances.

[0010] In a second aspect, a device for generating a power consumption planning scheme is provided, comprising:

[0011] An acquisition module is used to acquire a user's electricity consumption data set;

[0012] A first identification module is used to identify the user's peak electricity consumption period and the low electricity consumption period at different time scales according to the user's electricity consumption data set;

[0013] The second identification module is used to identify target energy-consuming electrical appliances according to peak power consumption periods and valley power consumption periods at different time scales;

[0014] A generation module is used to generate a power consumption planning plan according to the peak power consumption period, the low power consumption period and the target energy-consuming electrical appliances.

[0015] Optionally, in some embodiments of the present application, the first identification module includes:

[0016] The acquisition submodule is used to obtain the moving average period of different time scales;

[0017] A generating submodule, configured to generate power consumption curves of different time scales based on the user power consumption data set using the moving average period;

[0018] The submodule is used to obtain the peak power consumption period and the valley power consumption period of the user at different time scales according to the power consumption curves at different time scales.

[0019] Optionally, in some embodiments of the present application, the second identification module includes:

[0020] An analysis submodule, used for analyzing the correlation between the power consumption curve and the preset power information of the electrical equipment according to the peak power consumption periods and the valley power consumption periods of the different time scales;

[0021] An estimation submodule, used for estimating the proportion of power consumption of each electrical device based on the correlation;

[0022] The identification submodule is used to identify the target energy-consuming electrical appliance according to the power consumption ratio.

[0023] Optionally, in some embodiments of the present application, the device further includes a comparison module, and the comparison module is used to:

[0024] Obtaining the current power consumption of the user;

[0025] Calculate the difference between the current power consumption and the standard power consumption, where the standard power consumption is the average power consumption of users of the same type and in the same area as the user;

[0026] Comparing the power consumption difference with a preset power consumption threshold;

[0027] When the power consumption difference is greater than the preset power consumption threshold, the power consumption planning scheme generated according to the power consumption peak period, the power consumption valley period and the target energy-consuming electrical appliance is executed.

[0028] Optionally, in some embodiments of the present application, the preset power consumption threshold is obtained according to the average power consumption.

[0029] Optionally, in some embodiments of the present application, the user electricity consumption data set includes user basic information and electricity consumption information, and the acquisition module includes an integration submodule, and the integration submodule is specifically used to:

[0030] Performing data cleaning on the electricity usage information;

[0031] Convert the cleaned electricity usage information into a new format;

[0032] The user's basic information and the electricity usage information after format conversion are associated and integrated to obtain the user's electricity usage data set.

[0033] Optionally, in some embodiments of the present application, the device further includes a display module, and the display module is specifically used to:

[0034] Generate visual charts corresponding to the user's current power consumption, the peak power consumption period, the low power consumption period, and the target energy-consuming electrical appliances respectively;

[0035] Each of the visual charts is displayed.

[0036] In a third aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for generating a power consumption planning scheme when executing the computer program.

[0037] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned method for generating a power consumption planning scheme are implemented.

[0038] The present application provides a method, device, computer equipment and storage medium for generating a power consumption planning scheme, by acquiring a user power consumption data set; identifying the user's power consumption peak hours and power consumption trough hours at different time scales based on the user power consumption data set; identifying target energy-consuming appliances based on the power consumption peak hours and power consumption trough hours at different time scales; and generating a power consumption planning scheme based on the power consumption peak hours, power consumption trough hours and target energy-consuming appliances. In the power consumption planning scheme generation scheme provided in the present application, the user's power consumption data set is used to accurately identify the user's power consumption peak hours and power consumption trough hours at different time scales, which helps to understand the user's power consumption behavior, and identify the target energy-consuming appliances during the power consumption peak hours and power consumption trough hours. Based on the power consumption peak hours, power consumption trough hours and target energy-consuming appliances, a personalized power consumption planning scheme is generated for the user, helping the user to optimize the power consumption behavior, thereby reducing electricity bills and improving energy efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying creative work.

[0040] Figure 1 An application environment diagram of the method for generating a power consumption planning scheme provided in an embodiment of the present application;

[0041] Figure 2 A flowchart of a method for generating a power consumption planning scheme provided in an embodiment of the present application;

[0042] Figure 3 A structural block diagram of a device for generating a power consumption planning scheme provided in an embodiment of the present application;

[0043] Figure 4 A structural block diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0046] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0047] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0048] The power consumption planning scheme generation method provided by the embodiment of the present invention can be applied in Figure 1In the application environment of . Among them, the computer device 110 communicates with the server 120 through the network 130. The computer device 110 can obtain the user's electricity consumption data set; identify the user's electricity consumption peak period and electricity consumption valley period at different time scales according to the user's electricity consumption data set; identify the target energy-consuming electrical appliances according to the electricity consumption peak period and electricity consumption valley period at different time scales; generate an electricity consumption planning scheme according to the electricity consumption peak period, the electricity consumption valley period and the target energy-consuming electrical appliances, and display it through the computer device 110. In the present invention, the user's electricity consumption data set accurately identifies the user's electricity consumption peak period and electricity consumption valley period at different time scales, which helps to understand the user's electricity consumption behavior, and identifies the target energy-consuming electrical appliances during the electricity consumption peak period and electricity consumption valley period. Based on the electricity consumption peak period, electricity consumption valley period and the target energy-consuming electrical appliances, a personalized electricity consumption planning scheme is generated for the user to help the user optimize the electricity consumption behavior, thereby reducing electricity bills and improving energy utilization efficiency. Among them, the computer device 110 can be, but is not limited to, various smart phones 110-1, tablet computers 110-2 and laptop computers 110-3. The present invention is described in detail below through specific embodiments.

[0049] See also Figure 2 As shown, Figure 2 A flowchart of a method for generating a power consumption planning scheme provided by an embodiment of the present invention is provided. The method can be applied to both a terminal and a server. This embodiment is illustrated by applying it to a server. The method for generating a power consumption planning scheme includes the following steps:

[0050] S101: Acquire a user electricity consumption dataset.

[0051] The user electricity consumption data set may be a data set including the user's electricity consumption information within a preset time period. The preset time period may be in units of hours, days, weeks, months, years, etc. The user electricity consumption data set may include the user's electricity consumption accurate to each time period, electricity price pricing method (such as peak and valley electricity prices, tiered electricity prices, etc.), user basic information (address, user type, etc.) and payment records, etc.

[0052] The original data of the user's electricity bill can be obtained from the power supply enterprise system to obtain the user's electricity consumption data set; or the user can manually input the corresponding original data of the electricity bill to obtain the user's electricity consumption data set; or the user's electricity bill and other image data can be uploaded and the user's electricity consumption data set can be obtained through OCR text recognition; or the user's electricity consumption data set can be obtained by uploading an Excel file and searching and extracting the content of the Excel file.

[0053] Optionally, the user's account information may be logged in, and the user's electricity consumption data set may be obtained at a predetermined time interval (eg, uploading the data of the previous day at noon every day).

[0054] Furthermore, a preliminary integrity check can be performed on the collected user electricity consumption data to ensure that the data is not missing or damaged, and the data is cached for subsequent processing. For example, check whether the electricity consumption data for certain time periods is not recorded; confirm whether each record in the data set contains all necessary fields, such as date, time, electricity consumption, etc.; check whether the values ​​in the user electricity consumption data set are within a reasonable range, such as electricity consumption should not be negative. This is conducive to providing a complete data basis for subsequent accurate analysis and avoiding deviations in analysis results due to missing data.

[0055] S102: Identify the user's peak power consumption period and the user's low power consumption period at different time scales according to the user power consumption data set.

[0056] Herein, different time scales refer to different time periods within a preset time period.

[0057] The peak power consumption period refers to the period of time when the power grid load is higher than the preset value during the different time periods. For example, users use electricity during the daytime working hours; and industrial, commercial and household users use electricity at night.

[0058] The off-peak period refers to the period of time when the grid load is lower than or equal to the preset value during different time periods, for example, late at night or early in the morning when most users are resting and industrial and commercial activities are reduced.

[0059] It should be noted that peak electricity consumption periods may vary due to seasonal changes. For example, in the summer, peak electricity consumption periods may be longer or occur at different times due to increased air conditioning use. Trough electricity consumption periods may also vary due to seasonal changes. For example, in the winter, trough electricity consumption periods may be longer or occur at different times due to reduced heating demand.

[0060] The pre-trained time period prediction model can be loaded from local storage or cloud servers, and the user's electricity consumption characteristics can be extracted from the user's electricity consumption data set. The user's electricity consumption characteristics are used as the input of the time period prediction model, so that the time period preset model can analyze and predict the user's electricity consumption characteristics, and obtain the user's peak electricity consumption period and electricity trough period at different time scales in the future preset time period.

[0061] For example, the electricity consumption data of a residential user shows that a large amount of electricity is used between 6 pm and 8 pm in 7 days, which is the peak period of electricity consumption, such as turning on air conditioning, lighting and cooking. Based on the time characteristics and electricity consumption characteristics in 7 days, the pre-trained model predicts that in the next week, 6 pm to 8 pm will still be the peak period of electricity consumption, while the late night period (such as 1 am to 5 am) will be the low period of electricity consumption.

[0062] By analyzing the changing patterns of the user's electricity consumption at different time scales (such as day, week, month, season, etc.), the peak electricity consumption period and the valley electricity consumption period can be determined to analyze the differences in the user's electricity consumption characteristics in different seasons, such as the peak electricity consumption of air conditioners in summer and the changes in electricity consumption of heating equipment in winter. That is, in one embodiment, the identification of the user's electricity consumption peak period and valley electricity consumption period at different time scales according to the user's electricity consumption data set includes:

[0063] Get moving average periods of different time scales;

[0064] Using the moving average period to generate power consumption curves of different time scales based on the user power consumption data set;

[0065] The peak power consumption period and the valley power consumption period of the user at different time scales are obtained according to the power consumption curves at different time scales.

[0066] Among them, the moving average period of different time scales can be the period of the moving average of different time scales within a preset time period. The time unit of the period can be hours, days, weeks, months, etc. For example, the moving period can be 7 days. The moving periods of different time scales can be the same or different, which can be set according to the actual application scenario, and are not specifically limited here.

[0067] The electricity consumption curve includes electricity consumption data at different time scales within a preset time period, and also includes electricity consumption data at different time scales within a future preset time period.

[0068] The electricity consumption variation pattern of the user's electricity consumption data set can be analyzed to obtain electricity consumption data at different time scales within a preset time period, and then the moving average period is used to calculate the moving average of the electricity consumption data at different time scales to obtain electricity consumption data at different time scales in the future preset time period. In this way, electricity consumption curves at different time scales can be obtained based on the electricity consumption data at different time scales in the preset time period and the electricity consumption data at different time scales in the future preset time period.

[0069] For example, the moving average can be calculated as follows:

[0070]

[0071] Among them, Mt is the moving average value of time t (for example, t is 7:00 to 8:00 on the first to seventh days of the moving average period), n is the moving average period (for example, n is 7, which means calculating the moving average of the past 7 days), x i is the electricity consumption at time scale i.

[0072] For example, for a user's daily electricity consumption data for a month (30 days), a 7-day moving average period is used to calculate the moving average for the next 30 days to obtain the electricity consumption curve for the next 30 days. This electricity consumption curve can be used to more intuitively predict the user's electricity consumption fluctuation trend within a week, thereby identifying peak and low electricity consumption periods.

[0073] In this embodiment, the power consumption curve is smoothed by calculating the moving average value, and the power consumption trend of the user in the future moving average period is predicted, so as to facilitate a clearer understanding of the power consumption behavior of the user.

[0074] S103: Identify target energy-consuming electrical appliances according to peak power consumption periods and valley power consumption periods at different time scales.

[0075] The target energy-consuming electrical appliances are electrical devices whose power consumption ratio during peak power consumption period and / or off-peak power consumption period is higher than a preset ratio.

[0076] The power consumption characteristics (such as voltage, current, power, etc.) corresponding to the user power consumption data during peak and valley periods at different time scales on the power consumption curve can be identified through intelligent algorithms such as the K-nearest neighbor (KNN) model or neural network, thereby determining the target energy-consuming appliances.

[0077] According to the power data fluctuation characteristics and power characteristics of electrical equipment in the user power consumption data set, the power consumption proportion of various electrical equipment, such as lighting, air conditioning, refrigerators, televisions, etc., can be estimated, so as to identify the main energy-consuming electrical appliances, that is, the target energy-consuming electrical appliances. That is, in one embodiment, the target energy-consuming electrical appliances are identified according to the peak power consumption periods and the low power consumption periods at different time scales, including:

[0078] Analyzing the correlation between the power consumption curve and the preset power information of the electrical equipment according to the peak power consumption periods and the low power consumption periods of the different time scales;

[0079] Based on the correlation, the proportion of power consumption of each electrical device is estimated;

[0080] The target energy-consuming electrical appliances are identified according to the power consumption proportion.

[0081] Among them, the preset electrical equipment power information includes the power of various electrical equipment. The power consumption ratio is the ratio of the power consumption of the electrical equipment during its use time to the total power consumption during the peak period and the ratio of the power consumption of the electrical equipment during its use time to the total power consumption during the valley period. The correlation between the power consumption curve and the preset electrical equipment power information indicates the degree of matching between the power consumption curve and each power in the preset electrical equipment power information, such as the peak value corresponding to the power of each electrical equipment on the power consumption curve.

[0082] The usage time of each electrical device can be estimated by analyzing the correlation between the power consumption curve and the preset electrical power information, and then the power consumption proportion of each electrical device can be calculated based on the usage time and the corresponding power of each electrical device. Finally, if a sudden change in the power consumption proportion of an electrical device is detected, the electrical device corresponding to the power consumption proportion is determined as the target energy-consuming appliance.

[0083] For example, the usage time T of the corresponding electrical equipment can be estimated by analyzing the correlation between the peak value on the total power consumption curve and the typical power consumption characteristics (i.e., power) of different electrical appliances. i (Unit: hour), for example, the power of the air conditioner is 2 kW, the power of the refrigerator is 0.5 kW, and the power of the washing machine is 1.5 kW. At this time, the peak value of the air conditioner on the power consumption curve can be 2 kW, the peak value of the refrigerator can be 0.5 kW, and the peak value of the washing machine can be 1.5 kW. These peak values ​​represent the instantaneous power consumption of the corresponding electrical equipment during the use period of the electrical equipment. Therefore, the use time T of the electrical equipment can be estimated by the peak value i (Unit: hour) When a corresponding peak value is detected during a peak power consumption period and / or a low power consumption period at a certain time scale in the future, the usage time and power of the electrical equipment during the peak power consumption period and / or the low power consumption period at a certain time scale can be determined.

[0084] The power P of each electrical device is known i (Unit: kilowatt) and usage time T i (Unit: hour), then the power consumption of each electrical equipment is E i =P i *T i , and calculate the total power consumption in the future preset time period on the power consumption curve to obtain the power consumption proportion. When the power consumption proportion is greater than the preset proportion threshold corresponding to the electrical device, the device corresponding to the power consumption is used as the target energy-consuming electrical appliance.

[0085] For another example, assuming that the air conditioner has a large power (such as 2 kilowatts) when it is running and is used in a specific time period (such as the high temperature period during the day in summer, from 2 to 3 pm), the power consumption curve includes the changing trend of power consumption in the next day. By analyzing the change amplitude of the peak power consumption period (12 noon to 5 pm) on the power consumption curve, it is determined that the peak corresponding to the air conditioner appears between 2 and 3 pm, and the power consumption proportion of the air conditioner is estimated by combining the power of the air conditioner and the total power consumption in the next day on the power consumption curve, such as 3 kilowatts. That is, if the total power consumption of the power consumption change curve suddenly increases by a certain value in a few hours (that is, the peak corresponding to the air conditioner appears), and this time period coincides with the local high temperature period in summer, according to the power of the air conditioner, it is roughly calculated that the power consumption of the air conditioner in this hour is 2 kilowatts, and then its proportion in the total power consumption is estimated to be 2 / 3. If 2 / 3 is greater than the preset proportion threshold corresponding to the air conditioner, it can be indicated that the air conditioner has been running for too long or the energy consumption is too high, and the air conditioner can be used as a target energy-consuming appliance.

[0086] S104: Generate a power consumption planning plan according to the peak power consumption period, the valley power consumption period and the target energy-consuming electrical appliances.

[0087] It is difficult for users to fully understand their electricity usage behavior only from traditional electricity bills and simple analysis software. For example, it is unclear which electrical appliances consume more electricity and in which time periods the electricity cost is higher. Users cannot accurately judge the reasons for fluctuations in electricity bills. It may be seasonal changes in electricity consumption (such as increased use of air conditioners in summer) or abnormal power consumption of certain electrical appliances, but existing technologies cannot help users clearly identify them. Users cannot know how to adjust their electricity usage habits or choose appropriate energy-saving equipment to reduce electricity costs. For example, it is not known which electrical appliances can be effectively reduced in a specific time period to reduce the use of electricity bills. Therefore, an electricity consumption planning plan can be generated based on the peak electricity consumption period, the low electricity consumption period and the target energy-consuming appliances.

[0088] Among them, the electricity consumption planning scheme is a scheme used to optimize users' electricity consumption behavior in order to reduce electricity bills and improve energy efficiency.

[0089] For example, the electricity price during peak hours is higher than that during low-consumption hours. The peak hours are from 18:00 to 22:00 every night, when household electricity consumption is the highest, and the main electrical appliances include air conditioners, televisions, and kitchen appliances. The low-consumption hours are from 0:00 to 6:00 every morning, when household electricity consumption is the lowest, and the main electrical appliances are refrigerators and some standby equipment. The target energy-consuming appliances are air conditioners (power 2 kW), electric water heaters (power 2 kW), and washing machines (power 1.5 kW). The planning scheme may include reducing the use time of air conditioners during peak hours, or setting the air conditioner temperature slightly higher (such as air conditioner temperatures close to human body temperature, and different target temperatures can be set according to different seasons, such as 26 degrees in winter and 21 degrees in summer) to reduce electricity consumption. Use kitchen appliances before or after the peak hours, such as cooking in the afternoon or after 22:00 in the evening. During the period of low electricity consumption, the heating time of the electric water heater is set to the low electricity consumption period, such as 0:00 to 6:00 in the morning, so that the low electricity price can be used to reduce electricity bills, and the washing machine can be used during the low electricity consumption period to reduce electricity bills. If the air conditioner and washing machine are detected to have high energy consumption during the peak electricity consumption period and the low electricity consumption period, the electricity planning plan also includes suggestions for replacing more energy-saving electrical appliances, such as energy-saving air conditioners and washing machines, and making personalized recommendations based on the user's preferences to reduce daily electricity consumption. If the standby equipment is detected to have high power consumption, the electricity planning plan also includes suggestions for reducing the power consumption of standby equipment, such as turning off TVs and computers when not in use. Based on this, users can reduce unnecessary electricity consumption during peak electricity consumption periods and reasonably use electricity resources during low electricity consumption periods, thereby effectively reducing electricity bills and improving energy efficiency.

[0090] Users are not clear about whether their electricity usage habits are reasonable compared with other users, and have a low awareness of saving electricity, which can easily lead to higher electricity costs. Based on this, by comparing the average electricity usage level of users of the same type in the same area, the current electricity efficiency of users is evaluated, and the energy saving space that can be achieved by changing electricity usage habits or using energy-saving equipment is predicted. That is, in one embodiment, the method further includes:

[0091] Obtaining the current power consumption of the user;

[0092] Calculate the difference between the current power consumption and the standard power consumption, where the standard power consumption is the average power consumption of users of the same type and in the same area as the user;

[0093] Comparing the power consumption difference with a preset power consumption threshold;

[0094] When the power consumption difference is greater than the preset power consumption threshold, the power consumption planning scheme generated according to the power consumption peak period, the power consumption valley period and the target energy-consuming electrical appliance is executed.

[0095] The power consumption threshold may be a preset multiple of the standard deviation between the user's current power consumption and the average power consumption.

[0096] If the difference between the user's current power consumption and the average power consumption is greater than the preset multiple of the standard deviation, there may be a large space for energy saving, and the power consumption planning scheme generated according to the peak power consumption period, the low power consumption period and the target energy-consuming electrical appliances is executed. For example, the average monthly power consumption of residents in a certain area is 100 degrees, and the standard deviation is 10 degrees. If the user's current monthly power consumption is 130 degrees, which is greater than 10 times the standard deviation, then the user's power consumption is higher than other users. The power consumption planning scheme generated according to the peak power consumption period, the low power consumption period and the target energy-consuming electrical appliances can be executed to suggest users to adjust their power consumption habits (such as reducing the use time of unnecessary electrical appliances during peak power consumption periods) or replace energy-saving equipment (such as energy-saving lamps) to reduce power consumption through the power consumption planning scheme. This provides users with comprehensive and accurate power consumption analysis results, helping users to gain a deep understanding of their own power consumption and energy-saving directions.

[0097] To predict the energy saving space that can be achieved by changing electricity usage habits or using energy-saving equipment, the standard deviation can be used to measure the difference between the current electricity usage and the average electricity usage. In one embodiment, the preset electricity usage threshold is obtained based on the average electricity usage.

[0098] The standard deviation can be calculated according to the following formula:

[0099]

[0100] Among them, p i is the standard deviation, N is the number of samples (i.e. the number of users of the same type in the same area), x i is the power consumption of the i-th user of the same type in the same area within a preset time period (such as a week or month, which is not specifically limited here), After the standard deviation is calculated, the standard deviation can be multiplied by a preset multiple to obtain the power consumption threshold, so that power consumption planning can be carried out more accurately to save power costs and improve energy utilization.

[0101] The uploaded Excel data or uploaded image data may be cleaned, and dimensionless processing (normalization and standardization) such as conversion and integration may be performed. That is, in one embodiment, the user power consumption data set includes user basic information and power consumption information, and the obtaining of the user power consumption data set includes:

[0102] Performing data cleaning on the electricity usage information;

[0103] Convert the cleaned electricity usage information into a new format;

[0104] The user's basic information and the electricity usage information after format conversion are associated and integrated to obtain the user's electricity usage data set.

[0105] User basic information includes user identity information, user account and other basic information, and electricity usage information includes user number, user electricity usage, electricity charges, electricity prices and timestamp and other information.

[0106] Data cleaning of electricity consumption information may include identifying and deleting duplicate data records, for example, by comparing key identifiers in the electricity consumption information (such as timestamps, user numbers, etc.) to determine duplicate data. It may also include correcting erroneous data, for example, discovering erroneous data through data verification rules (such as electricity consumption should not be negative, electricity prices should be within a reasonable range, etc.), and correcting it based on historical data or reasonable default values. It may also include processing missing data. Among them, for a small amount of missing electricity consumption data, the average value of electricity consumption data in adjacent time periods is used to fill in; for key data missing (such as electricity price information), a request is made to the power supply enterprise data interface to retrieve it.

[0107] Convert electricity consumption information in different formats into a format for data analysis, such as converting text-based electricity consumption data into numeric data and unifying the date format into the "YYYY-MM-DD HH:MM:SS" format. In addition, electricity consumption data can be classified and marked according to peak, valley, and normal periods, which is conducive to quickly identifying peak and low electricity consumption periods.

[0108] The user's basic information s is associated and integrated (eg, spliced) with electricity consumption information such as electricity consumption data and electricity fee data, thereby obtaining a user electricity consumption data set.

[0109] In this embodiment, by cleaning the electricity usage information, converting its format, and associating and integrating it with the basic information of the user, it is helpful to improve the data quality, make the data more suitable for in-depth analysis, and enhance the accuracy of the analysis results.

[0110] In one embodiment, the method further comprises:

[0111] Generate visual charts corresponding to the user's current power consumption, the peak power consumption period, the low power consumption period, and the target energy-consuming electrical appliances respectively;

[0112] Each of the visual charts is displayed.

[0113] Among them, the visual chart can mark the electricity consumption, electricity charges, electricity prices and other information of the corresponding time period during peak and low electricity consumption periods, and can also mark the name, model, electrical usage time and other information of the target energy-consuming appliances.

[0114] Exemplarily, a visualization component in the python language can be used to generate visualization charts corresponding to the user's current power consumption, the peak power consumption period, the low power consumption period, and the target energy-consuming electrical appliances, such as a bar chart used to show the power consumption ratio of different target energy-consuming electrical appliances, a line chart used to present the trend of power consumption over time, and a pie chart used to show the ratio of power consumption during peak power consumption periods to during low power consumption periods. Fill the analysis result data, i.e., the user's current power consumption, the peak power consumption period, the low power consumption period, and the target energy-consuming electrical appliances, into the corresponding visualization chart to ensure that the chart accurately reflects the analysis results. In addition, necessary elements such as chart titles, axis labels, and legends can be added to the visualization chart to make the chart easy to understand. At the same time, a brief text description is added next to or below the chart to explain the visualization chart, such as explaining the meaning of the chart and key findings (such as the air conditioner is used for too long).

[0115] In this embodiment, the user can intuitively and quickly understand the complex power consumption analysis results through visual charts, which is convenient for finding problems and taking improvement measures. Each visual chart is visually laid out, that is, each visual chart is combined on a display interface, which is convenient for users to compare and view. This enables users to have a deep understanding of their own power consumption behavior and clarify the direction of energy saving, such as reasonably arranging the use time of electrical appliances, replacing energy-saving equipment in a targeted manner, etc., effectively reducing electricity costs and improving electricity efficiency.

[0116] The above is the process of generating the electricity consumption planning scheme for this application.

[0117] As mentioned above, the present application provides a method, device, computer equipment and storage medium for generating a power consumption planning scheme, by acquiring a user power consumption data set; identifying the user's power consumption peak hours and power consumption trough hours at different time scales based on the user power consumption data set; identifying target energy-consuming appliances based on the power consumption peak hours and power consumption trough hours at different time scales; and generating a power consumption planning scheme based on the power consumption peak hours, the power consumption trough hours and the target energy-consuming appliances. In the power consumption planning scheme generation scheme provided by the present application, the user's power consumption data set is used to accurately identify the user's power consumption peak hours and power consumption trough hours at different time scales, which helps to understand the user's power consumption behavior, and identify the target energy-consuming appliances in the power consumption peak hours and power consumption trough hours. Based on the power consumption peak hours, power consumption trough hours and target energy-consuming appliances, a personalized power consumption planning scheme is generated for the user, helping the user to optimize the power consumption behavior, thereby reducing electricity bills and improving energy utilization efficiency.

[0118] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0119] In one embodiment, a device for generating a power consumption planning scheme is provided, and the device for generating a power consumption planning scheme corresponds one-to-one to the method for generating a power consumption planning scheme in the above embodiment. Figure 3 As shown, the power consumption planning scheme generating device includes:

[0120] An acquisition module 201 is used to acquire a user's electricity consumption data set;

[0121] A first identification module 202 is used to identify the peak power consumption period and the low power consumption period of the user at different time scales according to the user power consumption data set;

[0122] The second identification module 203 is used to identify target energy-consuming electrical appliances according to peak power consumption periods and valley power consumption periods at different time scales;

[0123] The generating module 204 is used to generate a power consumption planning scheme according to the power consumption peak period, the power consumption valley period and the target energy-consuming electrical appliances.

[0124] In the electricity consumption planning scheme generation scheme provided in the present application, by obtaining the user's electricity consumption data set; identifying the user's electricity consumption peak hours and electricity consumption trough hours at different time scales based on the user's electricity consumption data set; identifying the target energy-consuming appliances based on the electricity consumption peak hours and electricity consumption trough hours at different time scales; and generating the electricity consumption planning scheme based on the electricity consumption peak hours, the electricity consumption trough hours and the target energy-consuming appliances. In the electricity consumption planning scheme generation scheme provided in the present application, accurately identifying the user's electricity consumption peak hours and electricity consumption trough hours at different time scales through the user's electricity consumption data set helps to understand the user's electricity consumption behavior, and identifies the target energy-consuming appliances during the electricity consumption peak hours and electricity consumption trough hours. Based on the electricity consumption peak hours, electricity consumption trough hours and target energy-consuming appliances, a personalized electricity consumption planning scheme is generated for the user to help the user optimize the electricity consumption behavior, thereby reducing electricity bills and improving energy efficiency.

[0125] Optionally, in some embodiments of the present application, the first identification module includes:

[0126] The acquisition submodule is used to obtain the moving average period of different time scales;

[0127] A generating submodule, configured to generate power consumption curves of different time scales based on the user power consumption data set using the moving average period;

[0128] The submodule is used to obtain the peak power consumption period and the valley power consumption period of the user at different time scales according to the power consumption curves at different time scales.

[0129] Optionally, in some embodiments of the present application, the second identification module includes:

[0130] An analysis submodule, used for analyzing the correlation between the power consumption curve and the preset power information of the electrical equipment according to the peak power consumption periods and the valley power consumption periods of the different time scales;

[0131] An estimation submodule, used for estimating the proportion of power consumption of each electrical device based on the correlation;

[0132] The identification submodule is used to identify the target energy-consuming electrical appliance according to the power consumption ratio.

[0133] Optionally, in some embodiments of the present application, the device further includes a comparison module, and the comparison module is used to:

[0134] Obtaining the current power consumption of the user;

[0135] Calculate the difference between the current power consumption and the standard power consumption, where the standard power consumption is the average power consumption of users of the same type and in the same area as the user;

[0136] Comparing the power consumption difference with a preset power consumption threshold;

[0137] When the power consumption difference is greater than the preset power consumption threshold, the power consumption planning scheme generated according to the power consumption peak period, the power consumption valley period and the target energy-consuming electrical appliance is executed.

[0138] Optionally, in some embodiments of the present application, the preset power consumption threshold is obtained according to the average power consumption.

[0139] Optionally, in some embodiments of the present application, the user electricity consumption data set includes user basic information and electricity consumption information, and the acquisition module includes an integration submodule, and the integration submodule is specifically used to:

[0140] Performing data cleaning on the electricity usage information;

[0141] Convert the cleaned electricity usage information into a new format;

[0142] The user's basic information and the electricity usage information after format conversion are associated and integrated to obtain the user's electricity usage data set.

[0143] Optionally, in some embodiments of the present application, the device further includes a display module, and the display module is specifically used to:

[0144] Generate visual charts corresponding to the user's current power consumption, the peak power consumption period, the low power consumption period, and the target energy-consuming electrical appliances respectively;

[0145] Each of the visual charts is displayed.

[0146] In one embodiment, a computer device is provided, the internal structure diagram of which can be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server through a network connection. When the computer program is executed by the processor, the functions or steps of a method for generating a power consumption planning scheme are realized.

[0147] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following steps are implemented:

[0148] Obtain user electricity consumption data sets; identify users' electricity consumption peak hours and electricity consumption valley hours at different time scales based on the user electricity consumption data sets; identify target energy-consuming appliances based on the electricity consumption peak hours and electricity consumption valley hours at different time scales; generate electricity consumption planning schemes based on the electricity consumption peak hours, electricity consumption valley hours and target energy-consuming appliances.

[0149] In this embodiment, the user's electricity consumption data set is used to accurately identify the user's electricity consumption peak hours and electricity consumption low hours at different time scales, which helps to understand the user's electricity consumption behavior and identify the target energy-consuming appliances during the peak electricity consumption hours and electricity consumption low hours. Based on the peak electricity consumption hours, electricity consumption low hours and target energy-consuming appliances, a personalized electricity consumption planning plan is generated for the user to help the user optimize the electricity consumption behavior, thereby reducing electricity bills and improving energy utilization efficiency.

[0150] In one embodiment, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0151] Obtain user electricity consumption data sets; identify users' electricity consumption peak hours and electricity consumption valley hours at different time scales based on the user electricity consumption data sets; identify target energy-consuming appliances based on the electricity consumption peak hours and electricity consumption valley hours at different time scales; generate electricity consumption planning schemes based on the electricity consumption peak hours, electricity consumption valley hours and target energy-consuming appliances.

[0152] In this embodiment, the user's electricity consumption data set is used to accurately identify the user's electricity consumption peak hours and electricity consumption low hours at different time scales, which helps to understand the user's electricity consumption behavior and identify the target energy-consuming appliances during the peak electricity consumption hours and electricity consumption low hours. Based on the peak electricity consumption hours, electricity consumption low hours and target energy-consuming appliances, a personalized electricity consumption planning plan is generated for the user to help the user optimize the electricity consumption behavior, thereby reducing electricity bills and improving energy utilization efficiency.

[0153] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can refer to the relevant descriptions on the server side and the client side in the aforementioned method embodiment. To avoid repetition, they will not be described one by one here.

[0154] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0155] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0156] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A method for generating a power consumption planning scheme, characterized in that: include: Obtain user electricity consumption data set; Identify the user's peak electricity consumption period and the user's low electricity consumption period at different time scales according to the user's electricity consumption data set; Identify target energy-consuming appliances based on peak and valley periods of electricity consumption at different time scales; A power consumption planning scheme is generated according to the power consumption peak period, the power consumption valley period and the target energy-consuming electrical appliances.

2. The method for generating a power consumption planning scheme according to claim 1, characterized in that: The step of identifying the peak power consumption period and the valley power consumption period of the user at different time scales according to the user power consumption data set comprises: Get moving average periods of different time scales; Using the moving average period to generate power consumption curves of different time scales based on the user power consumption data set; The peak power consumption period and the valley power consumption period of the user at different time scales are obtained according to the power consumption curves at different time scales.

3. The method for generating a power consumption planning scheme according to claim 1, characterized in that: The identifying target energy-consuming electrical appliances according to peak power consumption periods and valley power consumption periods at different time scales includes: Analyzing the correlation between the power consumption curve and the preset power information of the electrical equipment according to the peak power consumption periods and the low power consumption periods of the different time scales; Based on the correlation, the proportion of power consumption of each electrical device is estimated; The target energy-consuming electrical appliances are identified according to the power consumption proportion.

4. The method for generating a power consumption planning scheme according to claim 1, characterized in that: The method further comprises: Obtaining the current power consumption of the user; Calculate the difference between the current power consumption and the standard power consumption, where the standard power consumption is the average power consumption of users of the same type and in the same area as the user; Comparing the power consumption difference with a preset power consumption threshold; When the power consumption difference is greater than the preset power consumption threshold, the power consumption planning scheme generated according to the power consumption peak period, the power consumption valley period and the target energy-consuming electrical appliance is executed.

5. The method for generating a power consumption planning scheme according to claim 4, characterized in that: The preset power consumption threshold is obtained according to the average power consumption.

6. The method for generating a power consumption planning scheme according to any one of claims 1 to 5, characterized in that: The user electricity consumption data set includes basic information of the user and electricity consumption information, and obtaining the user electricity consumption data set includes: Performing data cleaning on the electricity usage information; Convert the cleaned electricity usage information into a new format; The user's basic information and the electricity usage information after format conversion are associated and integrated to obtain the user's electricity usage data set.

7. The method for generating a power consumption planning scheme according to any one of claims 1 to 5, characterized in that: The method further comprises: Generate visual charts corresponding to the user's current power consumption, the peak power consumption period, the low power consumption period, and the target energy-consuming electrical appliances respectively; Each of the visual charts is displayed.

8. A device for generating a power consumption planning scheme, characterized in that: include: An acquisition module is used to acquire a user's electricity consumption data set; A first identification module is used to identify the user's peak electricity consumption period and the low electricity consumption period at different time scales according to the user's electricity consumption data set; The second identification module is used to identify target energy-consuming electrical appliances according to peak power consumption periods and valley power consumption periods at different time scales; A generation module is used to generate a power consumption planning plan according to the peak power consumption period, the low power consumption period and the target energy-consuming electrical appliances.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method for generating a power consumption planning scheme as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for generating a power consumption planning scheme as described in any one of claims 1 to 7 are implemented.

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