An electric heating user identification and heating electricity feature analysis method and device

Abstract

The application discloses an electric heating user identification and heating electricity consumption feature analysis method and device. The electric heating user identification and heating electricity consumption feature analysis method comprises the following steps: acquiring user electricity consumption history data in a region to be identified; dividing the user electricity consumption history data in the region to be identified into historical user detailed electricity consumption data and historical regional overall electricity consumption data; acquiring overall electricity consumption and air temperature change relationship information during a heating season, the number of electric heating users and the proportion of the electric heating users in overall users, and the average use rate of electric heating in the region to be identified according to the historical user detailed electricity consumption data and the historical regional overall electricity consumption data. Through the method, the overall electricity consumption and air temperature change relationship information during the heating season, the number of electric heating users and the proportion of the electric heating users in overall users, and the average use rate of electric heating in the region to be identified can be identified, and the information can be displayed on an interface, so that the electricity consumption features of the electric heating users can be intuitively understood.

Description

Technical Field

[0001] This application relates to the field of coal-to-electricity technology, specifically to a method and device for identifying electric heating users and analyzing their heating electricity consumption characteristics. Background Technology

[0002] Since 2017, various regions have successively carried out coal-to-electricity conversion projects, aiming to promote the use of clean energy and reduce pollution emissions from the burning of loose coal in residential areas. While initial construction results have been achieved under this goal, the lack of effective evaluation indicators in the later stages has made it difficult to monitor and evaluate the conversion results. The State Grid Corporation has invested significant funds and manpower in promoting coal-to-electricity conversion, but its understanding of the specific usage is incomplete, hindering further progress. Therefore, it is necessary to accurately identify the number of coal-to-electricity users and their usage rate. This study, based on big data analysis of electricity consumption in residential areas during the heating and non-heating seasons, constructs an electric heating user identification model and develops a real-time monitoring scheme for coal-to-electricity conversion.

[0003] After completing the coal-to-electricity conversion project, it is crucial to quickly ascertain the usage status of the converted equipment. This allows for an overall assessment of the conversion process, summarizing information on user distribution and typical usage periods. This data will help ensure effective handling and support during peak heating loads. Furthermore, understanding the usage information allows for feedback on the coal-to-electricity conversion work and provides valuable reference suggestions for setting electricity prices and subsidy policies for specific periods.

[0004] In the research on the identification and monitoring of coal-to-electricity users, there are two main research methods. The first method is sensor-based data collection, which involves installing dedicated sensor devices on electric heating equipment to collect data in real time. This data, combined with big data analytics, enables relatively accurate identification and monitoring. The advantages of this method are accurate and reliable analysis results and abundant data collection. Its disadvantages include high installation costs, reliance on sensor accuracy, and low resident willingness to install such devices. The second method is a power consumption analysis method based on intelligent algorithms. This method combines specific methods such as neural networks to identify coal-to-electricity usage and predict load changes, analyzing the overall usage in a specific area. This method provides a detailed analysis of power consumption from a holistic perspective but does not involve effective analysis of user-side electricity consumption behavior.

[0005] Therefore, there is a need for a technical solution to improve the aforementioned shortcomings of existing technologies. Summary of the Invention

[0006] The purpose of this invention is to provide a method for identifying electric heating users and analyzing the characteristics of heating electricity consumption to improve the above-mentioned deficiencies of the prior art.

[0007] One aspect of the present invention provides a method for identifying electric heating users and analyzing heating electricity consumption characteristics, the method comprising:

[0008] Obtain historical electricity consumption data of users within the area to be identified;

[0009] The historical electricity consumption data of users in the area to be identified is divided into detailed historical user electricity consumption data and historical overall area electricity consumption data.

[0010] Based on historical detailed user electricity consumption data and historical regional overall electricity consumption data, information on the relationship between overall electricity consumption and temperature changes during the heating season, the number of electric heating users and their proportion of the total number of users, and the average usage rate of electric heating in the area to be identified are obtained.

[0011] Optionally, the method for identifying electric heating users and analyzing heating electricity consumption characteristics further includes:

[0012] Get the current time point;

[0013] Determine whether it is currently the heating season based on the current time. If so, then...

[0014] Based on historical detailed user electricity consumption data and historical regional overall electricity consumption data, the overall utilization rate of electric heating equipment in the future preset time period is predicted.

[0015] Optionally, obtaining information on the relationship between overall electricity consumption and temperature changes during the heating season based on historical detailed user electricity consumption data and historical overall regional electricity consumption data includes:

[0016] The daily power supply curve and daily temperature curve for the heating season are obtained based on historical detailed user electricity consumption data and historical overall regional electricity consumption data.

[0017] The Pearson correlation coefficient was obtained based on the daily power supply curve and the daily temperature curve during the heating season.

[0018] Based on the daily power supply curve, daily temperature curve, and Pearson correlation coefficient, the information on the relationship between overall power consumption and temperature changes during the heating season is provided.

[0019] Optionally, obtaining the number of electric heating users and their proportion of total users based on historical detailed user electricity consumption data and historical regional overall electricity consumption data includes:

[0020] The number of electric heating users in the region is obtained based on historical detailed user electricity consumption data and historical overall regional electricity consumption data.

[0021] Based on the number of electric heating users in the region and the total number of electric heating users and their proportion of the total number of users.

[0022] Optionally, obtaining the average electric heating utilization rate of the area to be identified based on historical detailed user electricity consumption data and historical overall regional electricity consumption data includes:

[0023] The electric heating usage rate for each user during the heating season is obtained based on detailed historical electricity consumption data.

[0024] The average electric heating usage rate of the area to be identified is obtained based on each user's electric heating usage rate during the heating season and the number of users in the area to be identified.

[0025] Optionally, the historical regional overall electricity consumption data includes time information, daily total electricity consumption information, and daily average temperature information;

[0026] The process of obtaining the daily power supply curve and daily temperature curve for the heating season based on historical detailed user electricity consumption data and historical overall regional electricity consumption data includes:

[0027] Obtain daily electricity consumption data for the heating season of the area to be identified based on total daily electricity consumption information;

[0028] Generate a daily power supply curve for the heating season based on the daily power consumption data and time information of the area to be identified.

[0029] A daily temperature curve for the heating season is generated based on the daily average temperature information and time information.

[0030] Optionally, the historical user detailed electricity consumption data includes a time period, the number of users in the area to be identified, and the electricity consumption information of each user within the time period, wherein the electricity consumption information of each user within the time period includes the daily electricity consumption information within that time period;

[0031] The method of obtaining the number of electric heating users in the region based on historical detailed user electricity consumption data and historical overall regional electricity consumption data includes:

[0032] The time period is divided into a non-heating season time period and a heating season time period according to the preset time nodes.

[0033] Obtain daily electricity consumption information for each user during the heating season;

[0034] Perform the following operations for each user:

[0035] The parameters for starting the coal-to-electricity conversion during the heating season are obtained based on the user's daily electricity consumption information during the non-heating season period.

[0036] Based on the activation parameters of the coal-to-electricity conversion during the heating season, it is determined whether the user used electric heating equipment during the heating season. If so, the user is determined to be an electric heating user in the area.

[0037] Optionally, obtaining the electric heating usage rate for each user during the heating season based on historical detailed electricity consumption data includes:

[0038] Perform the following operations for each user:

[0039] The number of days a user used electric heating was obtained based on detailed historical electricity consumption data.

[0040] Obtain the heating season timeframe;

[0041] The user's electric heating usage rate is obtained based on the number of days the user uses electric heating and the duration of the heating season.

[0042] Optionally, obtaining the number of days a user used electric heating based on historical detailed user electricity consumption data includes:

[0043] A daily electricity consumption curve for the heating season is generated based on the daily electricity consumption information of users during the heating season. The number of daily electricity consumption curves for users during the heating season is the same as the number of days in the heating season period. Each user's daily electricity consumption curve for the heating season includes the electricity consumption information for each hour within 24 hours of that day.

[0044] Obtain daily electricity consumption information of users within a preset period during the non-heating season, and generate year-on-year curves for electric heating activation. The number of year-on-year curves for electric heating activation is the same as the number of days in the preset period. Each user's year-on-year curve for heating activation includes the electricity consumption information for each hour within 24 hours of that day.

[0045] Based on the user's year-on-year heating start-up curve and the coal-to-electricity conversion start-up identification parameters for the heating season, the daily electricity consumption curve for each heating season is identified to determine whether at least one daily electricity consumption curve for the heating season meets preset conditions. If so, the date corresponding to the daily electricity consumption curve that meets the preset conditions is determined as the date the user uses electric heating; where...

[0046] The sum of the number of days each user used electric heating is the total number of days a user used electric heating.

[0047] This application also provides an electric heating user identification and heating electricity consumption characteristic analysis device, the electric heating user identification and heating electricity consumption characteristic analysis device comprising:

[0048] User electricity consumption history data acquisition module, the user electricity consumption history data acquisition module is used to acquire user electricity consumption history data in the area to be identified;

[0049] The segmentation module is used to divide the historical electricity consumption data of users in the identification area into detailed historical user electricity consumption data and historical overall electricity consumption data of the area.

[0050] The user coal-to-electricity conversion utilization rate acquisition module is used to obtain information on the relationship between overall electricity consumption and temperature changes during the heating season, the number of electric heating users and their proportion of the total number of users, and the average utilization rate of electric heating in the area to be identified, based on historical detailed electricity consumption data of users and historical overall regional electricity consumption data.

[0051] Beneficial effects:

[0052] The method for identifying electric heating users and analyzing heating electricity consumption characteristics in this application uses a coal-to-electricity monitoring model to identify key coal-to-electricity usage periods, providing a certain reference value for dynamic allocation of energy supply and better serving the "peak shaving and valley filling" work of power grid load adjustment. This method, based on data analysis, objectively assesses the usage of coal-to-electricity equipment, solving to some extent the problem of difficulty in evaluating coal-to-electricity work. Secondly, the significance of this invention lies in air pollution control. The coal-to-electricity identification and monitoring technology can promote cleaner and lower-carbon energy supply, indirectly demonstrating the improvement of regional air quality caused by "electricity replacing coal," and dynamically assessing whether there is a "risk of returning to coal" in the region. This can both encourage residents to reduce coal consumption and guide them towards a high-quality electrified lifestyle.

[0053] The method described in this application can obtain information on the relationship between overall electricity consumption and temperature changes during the heating season, the number of electric heating users and their proportion of the total number of users, as well as the average usage rate of electric heating in the area to be identified. This information can be displayed on the interface to provide an intuitive understanding of the electricity consumption characteristics of electric heating users. Attached Figure Description

[0054] Figure 1 This is a flowchart illustrating a method for identifying electric heating users and analyzing heating electricity consumption characteristics according to an embodiment of this application.

[0055] Figure 2 It is an electronic device used to achieve Figure 1 The method for identifying electric heating users and analyzing heating electricity consumption characteristics is shown below;

[0056] Figure 3 for Figure 1 A schematic diagram of a single user's daily hourly electricity consumption in the method for identifying electric heating users and analyzing heating electricity consumption characteristics;

[0057] Figure 4 for Figure 1 The diagram shows the year-on-year curve of electric heating activation and the baseline curve of typical daily electricity consumption during the non-heating air conditioning season in the method for identifying electric heating users and analyzing the characteristics of heating electricity consumption.

[0058] Figure 5 for Figure 1A schematic diagram illustrating the overall electricity consumption information during the heating season in the method for identifying electric heating users and analyzing heating electricity consumption characteristics.

[0059] Figure 6 for Figure 1 The diagram illustrates the use of electric heating by electric heating users during the heating season in the method for identifying electric heating users and analyzing the characteristics of heating electricity consumption.

[0060] Figure 7 for Figure 1 A schematic diagram illustrating the electric heating power consumption in the area to be identified in the method for identifying electric heating users and analyzing heating power consumption characteristics.

[0061] Figure 8 for Figure 1 A schematic diagram illustrating the number of coal-to-electricity users in the method for identifying electric heating users and analyzing the characteristics of heating electricity consumption;

[0062] Figure 9 for Figure 1 The diagram illustrates the electric heating power consumption of the area to be identified within a preset time period in the method for identifying electric heating users and analyzing heating power consumption characteristics.

[0063] Figure 10 for Figure 1 A schematic diagram illustrating the electric heating usage within 3 hours in the method for identifying electric heating users and analyzing heating electricity consumption characteristics;

[0064] Figure 11 for Figure 1 A schematic diagram of the 72-hour real-time electricity consumption monitoring curve in the method for identifying electric heating users and analyzing heating electricity consumption characteristics;

[0065] Figure 12 for Figure 1 The diagram shows the predicted electricity consumption in the method for identifying electric heating users and analyzing heating electricity consumption characteristics. Detailed Implementation

[0066] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be described in more detail below with reference to the accompanying drawings. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are some, but not all, embodiments of this application. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application. The embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0067] It should be noted that in the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0068] Figure 1 This is a flowchart illustrating a method for identifying electric heating users and analyzing heating electricity consumption characteristics according to an embodiment of this application.

[0069] like Figure 1 The methods for identifying electric heating users and analyzing heating electricity consumption characteristics shown include:

[0070] Step 1: Obtain historical electricity consumption data of users within the area to be identified;

[0071] Step 2: Divide the historical electricity consumption data of users in the area to be identified into detailed historical user electricity consumption data and historical overall regional electricity consumption data;

[0072] Step 3: Based on historical detailed user electricity consumption data and historical regional overall electricity consumption data, obtain information on the relationship between overall electricity consumption and temperature changes during the heating season, the number of electric heating users and their proportion of the total users, and the average usage rate of electric heating in the area to be identified.

[0073] The method described in this application can obtain information on the relationship between overall electricity consumption and temperature changes during the heating season, the number of electric heating users and their proportion of the total number of users, as well as the average usage rate of electric heating in the area to be identified. This information can be displayed on the interface to provide an intuitive understanding of the electricity consumption characteristics of electric heating users.

[0074] In this embodiment, the method for identifying electric heating users and analyzing heating electricity consumption characteristics further includes:

[0075] Get the current time point;

[0076] Determine whether it is currently the heating season based on the current time. If so, then...

[0077] Based on historical detailed user electricity consumption data and historical regional overall electricity consumption data, the overall utilization rate of electric heating equipment in the future preset time period is predicted.

[0078] This application can predict the overall utilization rate of electric heating equipment within a future preset time period by using detailed historical user electricity consumption data and historical regional overall electricity consumption data, thereby assisting users in monitoring electricity consumption.

[0079] In this embodiment, obtaining information on the relationship between overall electricity consumption and temperature changes during the heating season based on historical detailed user electricity consumption data and historical overall regional electricity consumption data includes:

[0080] The daily power supply curve and daily temperature curve for the heating season are obtained based on historical detailed user electricity consumption data and historical overall regional electricity consumption data.

[0081] The Pearson correlation coefficient was obtained based on the daily power supply curve and the daily temperature curve during the heating season.

[0082] Based on the daily power supply curve, daily temperature curve, and Pearson correlation coefficient, the information on the relationship between overall power consumption and temperature changes during the heating season is provided.

[0083] In this embodiment, the historical regional overall electricity consumption data includes time information, daily total electricity consumption information, and daily average temperature information;

[0084] See Figure 5 Based on historical detailed user electricity consumption data and historical overall regional electricity consumption data, the daily power supply curve and daily temperature curve for the heating season are obtained, including:

[0085] The daily electricity consumption data for the heating season of the area to be identified is obtained based on the total daily electricity consumption information. Specifically, the start date of the heating season is usually set manually according to the local conditions. For example, if a certain area starts heating after November 15, then November 15 to March 15 is the heating season. The total daily electricity consumption information between November 15 and March 15 is obtained from the historical regional overall electricity consumption data, which is the daily electricity consumption data for the heating season of the area to be identified.

[0086] The heating season daily power supply curve is generated based on the daily electricity consumption data and time information of the area to be identified. Specifically, a two-dimensional coordinate system is established with the date as the horizontal axis and the electricity consumption as the horizontal axis. The daily electricity consumption data of the heating season is marked in the two-dimensional coordinate system, and the line connecting the daily electricity consumption data of each day is the heating season daily power supply curve.

[0087] The daily temperature curve for the heating season is generated based on the daily average temperature information and time information. Specifically, the total daily electricity consumption information between November 15 and March 15 is obtained from the historical regional overall electricity consumption data, which is the daily average temperature information of the area to be identified. In other words, a two-dimensional coordinate system is established with the date as the horizontal axis and the temperature as the horizontal axis. The daily average temperature information is marked in this two-dimensional coordinate system, and the line connecting the average temperature information of each day is the daily temperature curve for the heating season.

[0088] See Figure 6 In this embodiment, obtaining the number of electric heating users and their proportion of total users based on historical detailed user electricity consumption data and historical regional overall electricity consumption data includes:

[0089] The number of electric heating users in the region is obtained based on historical detailed user electricity consumption data and historical overall regional electricity consumption data. Specifically, the historical detailed user electricity consumption data includes a time period, the number of users in the area to be identified, and the electricity consumption information of each user within the time period. The electricity consumption information of each user within the time period includes the daily electricity consumption information within that time period. The start date of the heating season is usually set manually according to the situation of the region. For example, if a region starts heating after November 15, then November 15 to March 15 is the heating season. The daily electricity consumption data of each user between November 15 and March 15 is obtained from the historical detailed user electricity consumption data. Based on the user's daily electricity consumption data, it can be determined whether the user has engaged in electric heating. In this embodiment, as long as a user is determined to have engaged in electric heating on one day during the entire heating season, the user is an electric heating user.

[0090] Based on the number of electric heating users in the region and the total number of electric heating users and their proportion in the total user base, specifically, in this embodiment, the number of users in the region to be identified is included in the historical detailed electricity consumption data.

[0091] In this embodiment, obtaining the average electric heating utilization rate of the area to be identified based on historical detailed user electricity consumption data and historical overall regional electricity consumption data includes:

[0092] The electric heating usage rate for each user during the heating season is obtained based on detailed historical electricity consumption data.

[0093] The average electric heating usage rate of the area to be identified is obtained based on each user's electric heating usage rate during the heating season and the number of users in the area to be identified.

[0094] In this embodiment, obtaining the number of electric heating users in the region based on historical detailed user electricity consumption data and historical overall regional electricity consumption data includes:

[0095] The time period is divided into a non-heating season time period and a heating season time period according to the preset time nodes. Taking the above description as an example, November 15th is the preset time node.

[0096] Obtain daily electricity consumption information for each user during the heating season;

[0097] Perform the following operations for each user:

[0098] The heating season coal-to-electricity conversion activation identification parameters for the user are obtained based on the user's daily electricity consumption information during the non-heating season period (i.e., each user needs to have their heating season coal-to-electricity conversion activation identification parameters calculated individually, but the calculation method is the same for each user); specifically, this application uses the following method to obtain the heating season coal-to-electricity conversion activation identification parameters:

[0099] The parameters β and A for initiating the coal-to-electricity conversion during the heating season are calculated. β is a threshold for measuring the fluctuation of a user's normal residential electricity consumption during the non-heating / air conditioning season, and A is a threshold for measuring the user's lowest hourly electricity consumption level during the non-heating / air conditioning season, reflecting the user's overall electricity consumption boundaries. The electricity data for the month preceding the heating season (taking November 15th as an example in this embodiment, the heating season begins after November 15th, so electricity data from October 15th to November 14th is obtained) are analyzed, and the set of maximum hourly electricity consumption E is calculated daily. max (For example, the maximum hourly electricity consumption is obtained on October 15th, October 16th, and so on, up to November 14th. The maximum hourly electricity consumption on each date is combined to form the set E.) max ) and minimum hourly electricity consumption E min Daily fluctuation level set E V =E max -E min (That is, the daily fluctuation level on October 15 is the difference between the maximum hourly electricity consumption obtained on October 15 and the minimum hourly electricity consumption obtained on October 15).

[0100] Because the daily fluctuation levels of users will change significantly after the coal-to-electricity conversion equipment is activated, this can be used as a factor to determine the activation of the coal-to-electricity conversion. The set of fluctuation levels E during the non-heating / air conditioning season can be calculated. V (The daily fluctuation levels on October 15th, October 16th, ... November 15th constitute the set E of the non-heating air conditioning season fluctuation levels.) V The fluctuation level is set into two states, and the K-means algorithm is used to set the fluctuation level set E of the non-heating and air conditioning season. V Classified as high-level fluctuation category E vh With low-level fluctuations, class E vl Take E vh The lower boundary is parameter β = min(E) vh The parameter β is used as an indicator to determine whether to initiate coal-to-electricity conversion based on the daily electricity consumption fluctuation analysis during the heating season;

[0101] Similarly, the maximum hourly electricity consumption will vary significantly depending on whether it is the heating season. Using the maximum hourly electricity consumption (A) during the non-heating / air conditioning season as the minimum hourly electricity consumption threshold for users on the day the coal-to-electricity conversion is initiated, and setting the maximum hourly electricity consumption into two states, the K-means algorithm is used to classify the maximum hourly electricity consumption into a high-level maximum hourly electricity consumption class (E). maxh With low-level maximum hourly electricity consumption category E maxl Take E maxl The upper boundary is parameter A = max(E) maxl ).

[0102] Based on the parameters for activating the coal-to-electricity conversion during the heating season, it is determined whether the user used electric heating equipment during the heating season. If so, the user is identified as an electric heating user in the area. For example, the user's daily electricity consumption information is obtained, and the user's maximum daily electricity consumption D is obtained. max (If a user's electricity consumption in a certain hour of the day is greater than in other hours, then the electricity consumption in that hour is the maximum electricity consumption for that day.) and the user's minimum daily electricity consumption D. min If |D max -D min |<β, and D max When <A, it is determined that electric heating equipment is not used; if |D max -D min |>β, and there is a moment when the charge x i If the electricity consumption is greater than the electricity consumption at the same time the electric heating is turned on, then the electric heating equipment is considered to be in use.

[0103] In this embodiment, for example, suppose there are 2 users in a region, and both of them are electric heating users in the region, then the number of electric heating users in the region is 2.

[0104] In this embodiment, obtaining the electric heating usage rate for each user during the heating season based on historical detailed electricity consumption data includes:

[0105] Perform the following operations for each user:

[0106] The number of days a user used electric heating is obtained based on detailed historical electricity consumption data.

[0107] Obtain the heating season timeframe;

[0108] The user's electric heating usage rate during the heating season is obtained based on the number of days the user uses electric heating and the heating season duration.

[0109] In this embodiment, obtaining the number of days a user used electric heating based on historical detailed user electricity consumption data includes:

[0110] A daily electricity consumption curve for the heating season is generated based on the daily electricity consumption information of users during the heating season period. The number of daily electricity consumption curves for users during the heating season is the same as the number of days in the heating season period. Each user's daily electricity consumption curve for the heating season includes the electricity consumption information for each hour within 24 hours of that day.

[0111] The daily electricity consumption information of users within a preset period during the non-heating season is obtained to generate a year-on-year curve for the start of electric heating. The number of year-on-year curves for the start of electric heating is the same as the number of days in the preset period. The year-on-year curve for the start of heating for each user includes the electricity consumption information for each hour within 24 hours of that day.

[0112] Based on the user's year-on-year heating start-up curve and the coal-to-electricity conversion start-up identification parameters for the heating season, the daily electricity consumption curve for each heating season is identified to determine whether at least one daily electricity consumption curve for the heating season meets preset conditions. If so, the date corresponding to the daily electricity consumption curve that meets the preset conditions is determined as the date the user uses electric heating; where...

[0113] The sum of the number of days each user used electric heating is the total number of days a user used electric heating.

[0114] See Figure 4 In this embodiment, the daily heating start-up curve for users is expressed as follows:

[0115] in,

[0116] P 阈值 This indicates the power threshold for the start of the coal-to-electricity conversion program.

[0117] See Figure 4 , Figure 4 The daily heating start-up curve is based on the typical daily electricity consumption baseline curve E during the non-heating and air conditioning season. day Specifically, based on users' historical electricity consumption data, we can obtain each user's daily and hourly electricity consumption data during the non-heating season (e.g., October 15th to November 14th as described above). Based on the users' daily and hourly electricity consumption data, we can generate a typical daily electricity consumption baseline curve E for the non-heating air conditioning season. day Specifically, extract the daily electricity consumption data set X∈S for each user (e.g., user A, user B) in the previous month (e.g., October 15th to November 14th as described above), and derive the result according to the formula. in To obtain the average electricity consumption at each time point within each day, the average electricity consumption at each time point is calculated, thereby obtaining the typical daily electricity consumption baseline curve E for each individual user during the non-heating and air conditioning season. day The horizontal axis of the curve represents hours, and the vertical axis represents electricity consumption. This curve provides information on the user's electricity consumption per hour within a 24-hour period.

[0118] In this embodiment, the power threshold P for the start-up hour of the coal-to-electricity conversion is... 阈值 Obtain it using the following method:

[0119] Based on literature review and field survey, the operating power, average power, and power fluctuation of electric heating equipment in the region were determined. An hourly power threshold for coal-to-electricity conversion was set, calculated as follows, where α represents the fluctuation level:

[0120] P 阈值 =P 平均功率 *(1-α).

[0121] In this embodiment, the daily electricity consumption curve for each heating season is identified based on the user's heating start-up year-on-year curve and the heating season coal-to-electricity conversion start-up identification parameters. This allows for the determination of whether at least one daily electricity consumption curve for a heating season meets preset conditions. If so, the date corresponding to the daily electricity consumption curve that meets the preset conditions is determined as the date the user uses electric heating. The determination is made using the following method:

[0122] The daily electricity consumption status is divided into three types: when D b =0(D b (See the daily electricity consumption curve during the heating season, item b). There was no electricity consumption by any equipment during the 24-hour period, so the day was judged to be in an unused state. Since no one was home and there were no electrical appliances in the resident's house throughout the day, it was judged that the electric heating equipment was not used on that day.

[0123] When D b When not equal to 0, and |D max -D min |<β and Dmax D max If <A, the user is judged to be out all day and will not use electric heating equipment that day.

[0124] When D b When |D is not equal to 0, max -D min |>β, the day is judged as a normal home life state, in which there is a possibility of using electric heating, and the electricity consumption x at each time is identified in sequence. i Relationship between electricity consumption at the same time as the start of electric heating, and determine the relationship between D and E′. day The relationship of electricity in the middle, when If the coal-to-electricity conversion equipment is used, it is considered that electric heating equipment has been used and an hourly usage tag is assigned to it. Based on the tag, the number of hours N of electric heating used on that day is counted, and the status of N hours of electric heating used on that day is assigned. In particular, when N=0, the status of no electric heating is assigned. The overall status classification is shown in Table 1.

[0125] Table 1 Daily Status Classification Table

[0126]

[0127] In this embodiment, the user's electric heating usage rate for the heating season is obtained based on the number of days the user uses electric heating and the heating season duration. The specific calculation method is as follows:

[0128]

[0129] Among them, Rate i To improve the utilization rate of users' coal-to-electricity conversion, DAY 使用电采暖天数 This refers to the number of days a user uses electric heating.

[0130] In this embodiment, the average electric heating usage rate of the area to be identified is obtained based on each user's electric heating usage rate during the heating season and the number of users in the area to be identified, as follows:

[0131] Where M represents the number of users.

[0132] In this embodiment, the information on the relationship between overall electricity consumption and temperature changes, the number of electric heating users and their proportion of the total number of users, and the average utilization rate of electric heating in the area to be identified can be displayed, such as... Figures 5 to 7 As shown, in Figure 5 The third subplot shows the baseline daily electricity consumption curve for a typical day during the non-heating season and the year-on-year curve for when electric heating is turned on. Figure 6 The data shows that 0.83% of users used electric heating for N hours, 23.33% did not use electric heating (they were away all day), and 75.83% did not use electric heating.

[0133] In this embodiment, the electricity consumption data in the user's electricity consumption history data is typically 96 data points. Therefore, this application further includes processing the acquired user electricity consumption history data to convert the electricity consumption data into 24-hour electricity consumption data, as follows:

[0134] In existing power data acquisition systems, smart meters collect users' cumulative electricity consumption every 15 minutes, totaling 96 data points collected daily (24 hours). To effectively correlate this with hourly power consumption, the 96 cumulative electricity consumption points are calculated as hourly electricity consumption over 24 hours. A sample of a user's hourly daily electricity consumption is provided below. Figure 3 As shown. During the data extraction process, the electricity consumption data set S = {s} is extracted based on the formula shown. T}, T∈(T1,T2), where s T This represents the electricity consumption characteristics over a 24-hour period on a certain day, where T1 and T2 represent the start and end dates of data extraction, respectively.

[0135] In this embodiment, the electric heating user identification and heating electricity consumption characteristic analysis method of this application further includes:

[0136] Get the current time point;

[0137] Determine whether it is currently the heating season based on the current time. If so, then...

[0138] Based on historical detailed user electricity consumption data and historical regional overall electricity consumption data, the overall utilization rate of electric heating equipment in the future preset time period is predicted.

[0139] For example, if the date is December 1st, as can be seen from the above description, the heating season begins after November 15th, so we are currently in the heating season.

[0140] Based on historical detailed user electricity consumption data and historical regional overall electricity consumption data, the overall utilization rate of electric heating equipment in the future preset time period is predicted to include:

[0141] Obtain the year-on-year start-up curve for each user's coal-to-electricity conversion. The construction method is the same as the year-on-year start-up curve for coal-to-electricity conversion above, both using the same formula. The acquisition process will not be elaborated upon here.

[0142] The system extracts real-time electricity consumption information for the area to be identified within the current 72 hours (November 28th to 30th). It compares the electricity consumption data of each individual user with the corresponding year-on-year start-up curve for the coal-to-electricity conversion for that user's date, determining whether the hourly electricity consumption reaches the threshold for the year-on-year start-up of electric heating (for example, if a user's electricity consumption data at 3:00 AM on November 28th is 100, while the data obtained from the corresponding year-on-year start-up curve for the same user's coal-to-electricity conversion for that date shows a user's electricity consumption data at 3:00 AM on October 28th is 90). If 100 is greater than 90, it is determined that electric heating was used at 3:00 AM on November 28th. After this process, the usage status of the electrically heated equipment is assigned for each hour within the 72-hour period (November 28th to 30th).

[0143] A monitoring table for coal-to-electricity conversion users is generated based on the usage status of electric heating equipment in each hour within 72 hours (November 28 to 30). The overall utilization rate of electric heating equipment within 72 hours is calculated based on the monitoring table, as shown in Table 2.

[0144] Table 2 Monitoring Table for Coal-to-Electricity Conversion Users

[0145] user Is it currently in use? Use within the first hour? … Use within the first 72 hours? A Unused Unused … Unused B Unused Unused … use C Unused use … use D Unused Unused … use E Unused Unused … Unused F Unused Unused … Unused G Unused Unused … Unused H Unused Unused … Unused I Unused Unused … Unused J Unused Unused … use … … … … … Overall utilization rate 0％ 1％ … 3％

[0146] Based on the monitoring table of coal-to-electricity users, the overall utilization rate of electric heating equipment within 72 hours was calculated, as shown in Table 2. The utilization rate was effectively predicted using an LSTM (Long Short-Term Memory) model. The model input was the overall utilization rate over 72 hours. A single-step prediction method was adopted, using the latest time as input, to effectively predict the overall utilization rate for the next hour.

[0147] In this embodiment, the data obtained in any step of this application can be graphically displayed. For example... Figure 5 The text displays a line chart of the data visualization unit, where sub-data... Figure 1 This data shows monthly electricity consumption changes, which can be used to determine the changes in monthly electricity consumption before and after the heating season, and can be used to preliminarily determine whether electric heating equipment should be turned on. Figure 2 This displays the daily electricity consumption changes, used to refine the assessment of electricity consumption variations during the heating season. Red dots in the graph indicate hours where the daily electricity consumption did not reach the minimum threshold. Figure 3 By comparing the year-on-year curve of the electric heating system, we can identify the electric heating equipment that was not turned on on that day.

[0148] For example, see Figure 6 The pie chart shows that this user spent 75.83% of the entire heating season at home without using electric heating, 23.33% of the days were spent away from home, and 0.83% of the days used electric heating for N hours. Overall, this analysis indicates a low utilization rate of the user's coal-to-electricity conversion equipment, a strong tendency to be away from home, and a high probability of the electric heating equipment being idle.

[0149] For example, as shown in Table 3:

[0150] Table 3 Summary of Regional Characteristics

[0151] user Unused percentage Usage rate % A 100 0 B 1 0 C 1 0 D 87.5 12.5 E 1 0 F 1 0 G 1 0 H 1 0 I 1 0 J 1 0 … … …

[0152] The area identification unit aggregates user parameters from the user identification unit, as shown in Table 3, with a focus on the usage rate parameters of electric heating equipment. Based on data statistics, it aggregates the number of users in the area, the average user usage rate, and the percentage of electric heating equipment turned on during the heating season, and transmits this data to the area display unit.

[0153] See Figure 7 , Figure 7 To sum the electricity consumption within the identified area, monthly electricity consumption was statistically analyzed. This line graph shows that since the start of the heating season, electricity consumption has increased significantly compared to previous months, with February, which includes the Spring Festival holiday, experiencing the highest electricity consumption. Daily electricity consumption statistics are as follows: Figure 7 son Figure 2 As shown in the analysis, the electricity consumption increases significantly during the heating season, indicating the possibility of using electric heating equipment. The specific usage situation needs to be analyzed based on the specific circumstances of each user.

[0154] See Figure 8 This reflects the basic distribution of users, specifically the number of users who have switched from coal to electricity. Secondly, it calculates the percentage of users who have switched from coal to electricity, reflecting the actual usage of electric heating equipment from a data perspective. Finally, it displays the top 10 users in terms of coal-to-electricity usage rate within the region, analyzing historical coal-to-electricity usage during different heating seasons. Figure 8 Of these, 10.26% were electric heating users, and the rest were non-heating users.

[0155] See Figure 9 This data reflects the electricity consumption information of users within the identified area for the most recent few hours. This application can display hourly electricity consumption information in real time and show the theoretically required electricity usage level for electric heating, providing a more intuitive reflection of user usage. The table below displays the electric heating usage information for the latest 3 hours in text form. For details, please see... Figure 10 .exist Figure 9 In the first sub-graph, the upper curve represents the threshold of electric heating power consumption, and the lower curve represents the real-time power consumption.

[0156] See Figure 10 The regional monitoring unit aggregates historical electricity consumption data from users, and the table shows that the key parameter is whether electric heating equipment is in use. Based on the data statistics, it summarizes the number of users in the area, the average user usage rate, and the percentage of electric heating equipment turned on during the heating season, and transmits this data to the prediction unit and the regional display unit.

[0157] See Figure 11 , Figure 11 The data shows the 72-hour real-time electricity consumption monitoring curve for the area. The curve reflects the basic patterns of electricity consumption in the area. Peak electricity consumption is mainly concentrated during the evening rest period, when electric heating equipment is most likely to be turned on.

[0158] See Figure 12 ,from Figure 12 It can be seen that the electric heating equipment is mainly used from 8 PM to midnight, with an activation rate of 1% to 3%, indicating a low utilization rate. The current activation rate is 0%, and the predicted activation rate for the next moment is also 0%.

[0159] This application also provides an electric heating user identification and heating electricity consumption characteristic analysis device. The electric heating user identification and heating electricity consumption characteristic analysis device includes a user electricity consumption history data acquisition module, a division module, and a user coal-to-electricity conversion usage rate acquisition module. The user electricity consumption history data acquisition module is used to acquire user electricity consumption history data in the area to be identified; the division module is used to divide the user electricity consumption history data in the identification area into historical user detailed electricity consumption data and historical area overall electricity consumption data; the user coal-to-electricity conversion usage rate acquisition module is used to acquire information on the relationship between overall electricity consumption and temperature changes during the heating season, the number of electric heating users and their proportion of the total number of users, and the average electric heating usage rate in the area to be identified, based on the historical user detailed electricity consumption data and the historical area overall electricity consumption data.

[0160] The above description of the method also applies to the description of the apparatus.

[0161] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the processor executes the computer program, it implements the electric heating user identification and heating electricity consumption characteristic analysis method as described above.

[0162] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the electric heating user identification and heating electricity consumption characteristic analysis method described above.

[0163] Figure 2This is an exemplary structural diagram of an electronic device capable of implementing the electric heating user identification and heating electricity consumption characteristic analysis method provided in one embodiment of this application.

[0164] like Figure 2 As shown, the electronic device includes an input device 501, an input interface 502, a central processing unit 503, a memory 504, an output interface 505, and an output device 506. The input interface 502, central processing unit 503, memory 504, and output interface 505 are interconnected via a bus 507. The input device 501 and output device 506 are connected to the bus 507 via the input interface 502 and output interface 505, respectively, and thus connected to other components of the electronic device. Specifically, the input device 501 receives input information from the outside and transmits it to the central processing unit 503 via the input interface 502. The central processing unit 503 processes the input information based on computer-executable instructions stored in the memory 504 to generate output information, temporarily or permanently storing the output information in the memory 504, and then transmitting the output information to the output device 506 via the output interface 505. The output device 506 outputs the output information to the outside of the electronic device for user use.

[0165] In other words, Figure 2 The illustrated electronic device may also be implemented as including: a memory storing computer-executable instructions; and one or more processors, which can be coupled when executing the computer-executable instructions. Figure 1 The method described is for identifying electric heating users and analyzing the characteristics of heating electricity consumption.

[0166] In one embodiment, Figure 2 The electronic device shown can be implemented as including: a memory 504 configured to store executable program code; and one or more processors 503 configured to run the executable program code stored in the memory 504 to execute the electric heating user identification and heating electricity consumption characteristic analysis method in the above embodiments.

[0167] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0168] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0169] Computer-readable media include both permanent and non-permanent, removable and non-removable media, and information storage can be achieved by any method or technology. 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 technologies, CD-ROM, DVD or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0170] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0171] Furthermore, it is clear that the word "comprising" does not exclude other units or steps. Multiple units, modules, or devices recited in a device claim may also be implemented by a single unit or overall device through software or hardware. The terms "first," "second," etc., are used to identify names, not to indicate any specific order.

[0172] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which includes one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutively marked blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or the overall flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0173] In this embodiment, the processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0174] Memory can be used to store computer programs and / or modules. The processor implements various functions of the device / terminal equipment by running or executing the computer programs and / or modules stored in the memory, and by accessing data stored in the memory. Memory can mainly include a program storage area and a data storage area. The program storage area can store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area can store data created based on the use of the mobile phone (such as audio data, phonebook, etc.). In addition, memory can include high-speed random access memory, and can also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0175] In this embodiment, if the modules / units integrated into the device / terminal equipment are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by hardware related to computer program instructions. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0176] It should be noted that the content contained in a computer-readable medium may be appropriately added to or reduced according to the requirements of legislation and patent practice in the jurisdiction. Although this application discloses preferred embodiments as described above, it is not intended to limit this application. Any person skilled in the art can make possible changes and modifications without departing from the spirit and scope of this application. Therefore, the scope of protection of this application should be determined by the scope defined in the claims of this application.

[0177] Although the present invention has been described in detail above with general descriptions and specific embodiments, modifications or improvements can be made to it, which will be obvious to those skilled in the art. Therefore, all such modifications or improvements made without departing from the spirit of the present invention fall within the scope of protection claimed by the present invention.

Claims

1. A method for identifying electric heating users and analyzing heating electricity consumption characteristics, characterized in that, The method for identifying electric heating users and analyzing heating electricity consumption characteristics includes: Acquire historical electricity consumption data of users in the area to be identified; the smart meter collects the user's cumulative electricity consumption once every 15 minutes, for a total of 96 data points collected in 24 hours per day; in order to effectively correspond with hourly power consumption, the 96 cumulative electricity consumption points are calculated as the hourly electricity consumption for 24 hours; The historical electricity consumption data of users in the area to be identified is divided into detailed historical user electricity consumption data and historical overall area electricity consumption data; the historical overall area electricity consumption data includes time information, daily total electricity consumption information and daily average temperature information. The detailed historical user electricity consumption data includes a time period, the number of users in the area to be identified, and the electricity consumption information of each user within the time period, wherein the electricity consumption information of each user within the time period includes the daily electricity consumption information within that time period. Based on historical detailed user electricity consumption data and historical regional overall electricity consumption data, information on the relationship between overall electricity consumption and temperature changes during the heating season, the number of electric heating users and their proportion of the total users, and the average usage rate of electric heating in the area to be identified are obtained. The process of obtaining information on the relationship between overall electricity consumption and temperature changes during the heating season based on historical detailed user electricity consumption data and historical overall regional electricity consumption data includes: The daily power supply curve and daily temperature curve for the heating season are obtained based on historical detailed user electricity consumption data and historical overall regional electricity consumption data. The process of obtaining the daily power supply curve and daily temperature curve for the heating season based on historical detailed user electricity consumption data and historical overall regional electricity consumption data includes: Obtain daily electricity consumption data for the heating season of the area to be identified based on total daily electricity consumption information; Generate a daily power supply curve for the heating season based on the daily power consumption data and time information of the area to be identified. Generate a daily temperature curve for the heating season based on daily average temperature information and time information; The Pearson correlation coefficient was obtained based on the daily power supply curve and the daily temperature curve during the heating season. Based on the daily power supply curve, daily temperature curve, and Pearson correlation coefficient, the information on the relationship between overall power consumption and temperature changes during the heating season is provided. The process of obtaining the number of electric heating users and their proportion of total users based on historical detailed user electricity consumption data and historical regional overall electricity consumption data includes: The number of electric heating users in the region is obtained based on historical detailed user electricity consumption data and historical overall regional electricity consumption data. The method of obtaining the number of electric heating users in the region based on historical detailed user electricity consumption data and historical overall regional electricity consumption data includes: The time period is divided into a non-heating season time period and a heating season time period according to the preset time nodes. Obtain daily electricity consumption information for each user during the heating season; Perform the following operations for each user: The parameters for starting the coal-to-electricity conversion during the heating season are obtained based on the user's daily electricity consumption information during the non-heating season period. Based on the activation identification parameters of the coal-to-electricity conversion during the heating season, it is determined whether the user used electric heating equipment during the heating season. If so, the user is determined to be an electric heating user in the area. Based on the number of electric heating users in the region and the total number of users, the number of electric heating users and their proportion of the total number of users are obtained; The process of obtaining the average electric heating utilization rate of the area to be identified based on historical detailed user electricity consumption data and historical overall regional electricity consumption data includes: The electric heating usage rate for each user during the heating season is obtained based on detailed historical electricity consumption data. The process of obtaining each user's electric heating usage rate during the heating season based on detailed historical electricity consumption data includes: Perform the following operations for each user: The number of days a user used electric heating was obtained based on detailed historical electricity consumption data. The method of obtaining the number of days a user uses electric heating based on historical detailed user electricity consumption data includes: A daily electricity consumption curve for the heating season is generated based on the daily electricity consumption information of users during the heating season. The number of daily electricity consumption curves for users during the heating season is the same as the number of days in the heating season period. Each user's daily electricity consumption curve for the heating season includes the electricity consumption information for each hour within 24 hours of that day. Obtain daily electricity consumption information of users within a preset period during the non-heating season, and generate year-on-year curves for electric heating activation. The number of year-on-year curves for electric heating activation is the same as the number of days in the preset period. Each user's year-on-year curve for heating activation includes the electricity consumption information for each hour within 24 hours of that day. Based on the user's year-on-year heating start-up curve and the coal-to-electricity conversion start-up identification parameters for the heating season, the daily electricity consumption curve for each heating season is identified to determine whether at least one daily electricity consumption curve for the heating season meets preset conditions. If so, the date corresponding to the daily electricity consumption curve that meets the preset conditions is determined as the date the user uses electric heating; where... The sum of the number of days each user used electric heating is the total number of days a user used electric heating. Obtain the heating season timeframe; The user's electric heating usage rate is obtained based on the number of days the user uses electric heating and the duration of the heating season. The average electric heating usage rate of the area to be identified is obtained based on each user's electric heating usage rate during the heating season and the number of users in the area to be identified. Based on the user's heating start-up year-on-year curve and the heating season coal-to-electricity conversion start-up identification parameters, the daily electricity consumption curve for each heating season is identified to determine whether at least one daily electricity consumption curve for a heating season meets preset conditions. If so, the date corresponding to the daily electricity consumption curve for a heating season that meets the preset conditions is determined as the date the user uses electric heating. The determination method is as follows: The daily electricity consumption status is divided into three types: when D b =0, D b For the daily electricity consumption curve during the heating season, there is no electricity consumption of any equipment in 24 hours. The day is judged to be in an unused state. The user's home is unoccupied and there are no electrical appliances in the house all day. The day is judged to be a state where electric heating equipment is not used. When D b When not equal to 0, and and If the user is determined to be out all day, it is determined that the user will not use electric heating equipment on that day. When D b When not equal to 0, when The day was determined to be a normal home life situation, in which electric heating may be used. The electricity consumption at each time point was then identified. Determine the relationship between electricity consumption at the same time as the start of electric heating. D and The relationship of electricity in the middle, when If the electric heating equipment is used, it is considered that the coal-to-electricity equipment has been used and an hourly usage tag is assigned. Based on the tag, the number of hours N of electric heating used on that day is counted, and the status of N hours of electric heating used on that day is assigned. When N=0, the status of no electric heating is assigned.

2. The method for identifying electric heating users and analyzing heating electricity consumption characteristics as described in claim 1, characterized in that, The method for identifying electric heating users and analyzing heating electricity consumption characteristics further includes: Get the current time point; Determine whether it is currently the heating season based on the current time. If so, then... Based on historical detailed user electricity consumption data and historical regional overall electricity consumption data, the overall utilization rate of electric heating equipment in the future preset time period is predicted.

3. A device for identifying electric heating users and analyzing heating electricity consumption characteristics, characterized in that, The electric heating user identification and heating electricity consumption characteristic analysis device includes: The user electricity consumption history data acquisition module is used to acquire the user electricity consumption history data in the area to be identified; the smart meter collects the user's cumulative electricity consumption once every 15 minutes, and collects a total of 96 data points in 24 hours a day; in order to effectively correspond to the hourly power, the 96 cumulative electricity points are calculated as the hourly electricity consumption for 24 hours; The segmentation module is used to divide the historical electricity consumption data of users within the identification area into detailed historical user electricity consumption data and historical overall regional electricity consumption data; the historical overall regional electricity consumption data includes time information, daily total electricity consumption information, and daily average temperature information. The detailed historical user electricity consumption data includes a time period, the number of users in the area to be identified, and the electricity consumption information of each user within the time period, wherein the electricity consumption information of each user within the time period includes the daily electricity consumption information within that time period. The user coal-to-electricity conversion rate acquisition module is used to obtain information on the relationship between overall electricity consumption and temperature changes during the heating season, the number of electric heating users and their proportion of the total number of users, and the average electric heating rate of the area to be identified, based on historical detailed electricity consumption data of users and historical overall regional electricity consumption data. The process of obtaining information on the relationship between overall electricity consumption and temperature changes during the heating season based on historical detailed user electricity consumption data and historical overall regional electricity consumption data includes: The daily power supply curve and daily temperature curve for the heating season are obtained based on historical detailed user electricity consumption data and historical overall regional electricity consumption data. The process of obtaining the daily power supply curve and daily temperature curve for the heating season based on historical detailed user electricity consumption data and historical overall regional electricity consumption data includes: Obtain daily electricity consumption data for the heating season of the area to be identified based on total daily electricity consumption information; Generate a daily power supply curve for the heating season based on the daily power consumption data and time information of the area to be identified. Generate a daily temperature curve for the heating season based on daily average temperature information and time information; The Pearson correlation coefficient was obtained based on the daily power supply curve and the daily temperature curve during the heating season. Based on the daily power supply curve, daily temperature curve, and Pearson correlation coefficient, the information on the relationship between overall power consumption and temperature changes during the heating season is provided. The process of obtaining the number of electric heating users and their proportion of total users based on historical detailed user electricity consumption data and historical regional overall electricity consumption data includes: The number of electric heating users in the region is obtained based on historical detailed user electricity consumption data and historical overall regional electricity consumption data. The method of obtaining the number of electric heating users in the region based on historical detailed user electricity consumption data and historical overall regional electricity consumption data includes: The time period is divided into a non-heating season time period and a heating season time period according to the preset time nodes. Obtain daily electricity consumption information for each user during the heating season; Perform the following operations for each user: The parameters for starting the coal-to-electricity conversion during the heating season are obtained based on the user's daily electricity consumption information during the non-heating season period. Based on the activation identification parameters of the coal-to-electricity conversion during the heating season, it is determined whether the user used electric heating equipment during the heating season. If so, the user is determined to be an electric heating user in the area. Based on the number of electric heating users in the region and the total number of users, the number of electric heating users and their proportion of the total number of users are obtained; The process of obtaining the average electric heating utilization rate of the area to be identified based on historical detailed user electricity consumption data and historical overall regional electricity consumption data includes: The electric heating usage rate for each user during the heating season is obtained based on detailed historical electricity consumption data. The process of obtaining each user's electric heating usage rate during the heating season based on detailed historical electricity consumption data includes: Perform the following operations for each user: The number of days a user used electric heating was obtained based on detailed historical electricity consumption data. The method of obtaining the number of days a user uses electric heating based on historical detailed user electricity consumption data includes: A daily electricity consumption curve for the heating season is generated based on the daily electricity consumption information of users during the heating season. The number of daily electricity consumption curves for users during the heating season is the same as the number of days in the heating season period. Each user's daily electricity consumption curve for the heating season includes the electricity consumption information for each hour within 24 hours of that day. Obtain daily electricity consumption information of users within a preset period during the non-heating season, and generate year-on-year curves for electric heating activation. The number of year-on-year curves for electric heating activation is the same as the number of days in the preset period. Each user's year-on-year curve for heating activation includes the electricity consumption information for each hour within 24 hours of that day. Based on the user's year-on-year heating start-up curve and the coal-to-electricity conversion start-up identification parameters for the heating season, the daily electricity consumption curve for each heating season is identified to determine whether at least one daily electricity consumption curve for the heating season meets preset conditions. If so, the date corresponding to the daily electricity consumption curve that meets the preset conditions is determined as the date the user uses electric heating; where... The sum of the number of days each user used electric heating is the total number of days a user used electric heating. Obtain the heating season timeframe; The user's electric heating usage rate is obtained based on the number of days the user uses electric heating and the duration of the heating season. The average electric heating usage rate of the area to be identified is obtained based on each user's electric heating usage rate during the heating season and the number of users in the area to be identified. Based on the user's heating start-up year-on-year curve and the heating season coal-to-electricity conversion start-up identification parameters, the daily electricity consumption curve for each heating season is identified to determine whether at least one daily electricity consumption curve for a heating season meets preset conditions. If so, the date corresponding to the daily electricity consumption curve for a heating season that meets the preset conditions is determined as the date the user uses electric heating. The determination method is as follows: The daily electricity consumption status is divided into three types: when D b =0, D b For the daily electricity consumption curve during the heating season, there is no electricity consumption of any equipment in 24 hours. The day is judged to be in an unused state. The user's home is unoccupied and there are no electrical appliances in the house all day. The day is judged to be a state where electric heating equipment is not used. When D b When not equal to 0, and and If the user is determined to be out all day, it is determined that the user will not use electric heating equipment on that day. When D b When not equal to 0, when The day was determined to be a normal home life situation, in which electric heating may be used. The electricity consumption at each time point was then identified. Determine the relationship between electricity consumption at the same time as the start of electric heating. D and The relationship of electricity in the middle, when If the electric heating equipment is used, it is considered that the coal-to-electricity equipment has been used and an hourly usage tag is assigned. Based on the tag, the number of hours N of electric heating used on that day is counted, and the status of N hours of electric heating used on that day is assigned. When N=0, the status of no electric heating is assigned.

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