Method, system and computer equipment for determining enterprise resumption of work and production based on power base

Abstract

The present invention provides a method, system and computer equipment for determining the resumption of work and production of an enterprise based on the electricity base, including: dividing the analyzed resumption of work and production day into multiple stages; determining the most similar historical days of the same period for each stage of the analyzed resumption of work and production day based on multi-dimensional influences; determining the electricity base for each stage based on the electricity consumption data of each stage and the most similar historical days of the same period corresponding to each stage; determining the resumption of work and production rate based on the actual electricity consumption of the analyzed resumption of work and production day and the electricity base, comprehensively considering the impact of multiple dimensions such as season, working days, weekends, holidays, weather and temperature on electricity consumption in different industries, and intelligently selecting the corresponding electricity base according to the characteristics of each time stage, thereby improving the accuracy of calculation of the resumption of work and production of the enterprise.

Description

Technical Field

[0001] The present invention relates to the technical field of resumption of work and production, and specifically to a method, system and device for determining resumption of work and production based on a power base. Background Art

[0002] In our analysis of the actual resumption of work and production at enterprises, we found that electricity consumption has obvious seasonal characteristics. It is unreasonable to use the average daily electricity consumption in December of last year as a benchmark for resumption of work and production. At the same time, from the perspective of electricity consumption across the industry, peak electricity consumption occurs during the peak winter and peak summer periods, while other periods are relatively low-peak electricity consumption. Different regions and industries have different characteristics. Therefore, a more reasonable intelligent method for selecting the electricity base should be established for the resumption of work and production analysis. Currently, there are two main methods for selecting the electricity base:

[0003] Fixed base: The average daily electricity consumption in December is used as the base for the resumption of work and production analysis. The rules for the resumption of work and production analysis are formally described as follows:

[0004] For users returning to work: daily electricity consumption / average daily electricity consumption in December of the previous year ≥ threshold

[0005] Return to work rate = number of users who have returned to work within the statistical scope / total number of users within the statistical scope * 100%

[0006] Recovery rate = total daily electricity consumption of users within the statistical scope / total daily average electricity consumption of users within the statistical scope in December of the previous year * 100%

[0007] Existing technologies fail to consider the impact of seasons, weather, temperature, workdays, weekends, and holidays on different industries. This results in inaccurate results due to the influence of these multiple factors. As time moves further away from December of last year, the impact of seasons, weather, temperature, workdays, weekends, and holidays gradually increases. Using the average daily electricity consumption in December of last year as a baseline, the resumption rates of work and production in different industries will be severely underestimated or overestimated, failing to reflect the true situation of resumption of work and production. Summary of the Invention

[0008] In order to solve the problem that the existing technology uses a fixed power base and fails to consider the impact of seasons, weather, temperature, working days, weekends and holidays on different industries, resulting in the resumption of work and production analysis results deviating from reality and failing to reflect the real situation, the present invention provides a method for determining the resumption of work and production of an enterprise based on the power base, comprising:

[0009] Divide the analyzed resumption of work and production days into multiple stages;

[0010] Based on the impact of multiple dimensions, determine the most similar historical date for each stage of the resumption of work and production being analyzed;

[0011] Based on the electricity consumption data of each stage and the most similar historical day in the same period corresponding to each stage, the electricity base of each stage is determined;

[0012] The resumption rate of work and production is determined based on the actual electricity consumption on the analyzed resumption day and the electricity base.

[0013] Preferably, the method of determining the most similar historical date of the resumption of work and production in the same period of each stage based on the multi-dimensional impact includes:

[0014] Based on the impact of multiple dimensions, a predetermined distance calculation formula is used to calculate the distance d between the first day of the resumption of work and production and the same day in the same period of history. 11 ; And record the date matching relationship M(x1, y1);

[0015] Use the predetermined distance calculation formula in turn to calculate the distance between each date x in the resumption of work and production days being analyzed. i and date y j+1 The distance d i,j+1 , date x i+1 and date y j The distance d i+1,j , date x i+1 and date y j+1 The distance d i+1,j+1 ; From the d i,j+1 , d i+1,j and d i+1,j+1 Select the smallest one and record the date matching relationship of the smallest one;

[0016] Based on the date matching relationship of all records, determine the date matching relationship with the smallest distance among the matching days corresponding to each day of resumption of work and production being analyzed, and generate the most similar historical day in the same period.

[0017] Preferably, the distance calculation formula is as follows:

[0018]

[0019] Where d is the distance between any day in the range of resumption of work and production being analyzed and any day in the historical year; K represents the total number of dimensions, d k Reflects the distance of the kth dimension, a k is the k-th dimension weight coefficient.

[0020] Preferably, the dimensions include: season dimension, work condition dimension, weather dimension and temperature dimension;

[0021] The working conditions include: weekdays, weekends and holidays.

[0022] Preferably, the dimension weight coefficient a kIt will be determined by the industry in which the enterprise that resumes work and production is located.

[0023] Preferably, the stages include: before the holiday, the transition period before the holiday, the holiday day, the transition period after the holiday, and after the holiday.

[0024] Preferably, the step of obtaining the most similar daily electricity consumption data in the same period of each stage as the electricity base for the stage includes:

[0025] When the period is before / after a holiday, the electricity consumption data of the most similar day in the same period of the period is used as the electricity consumption base for the period;

[0026] When the stage is a holiday, a fixed base number corresponding to the holiday is obtained from historical electricity consumption data according to the holiday type as the electricity base number for the stage;

[0027] When the stage is a transition period before a holiday, the power base corresponding to the pre-holiday and the power base corresponding to the holiday day are used to transition in a proportional alternating rise and fall mode to obtain the power base of the stage;

[0028] When the stage is a transition period after a holiday, based on the electricity base corresponding to the post-holiday period and the electricity base corresponding to the holiday day, a proportional alternating rise and fall mode is adopted to transition to obtain the electricity base of the stage.

[0029] Preferably, determining the resumption rate of work and production based on the power base includes:

[0030] Determine the number of users who have returned to work based on the actual daily power consumption and power base during the analyzed resumption of work and production days;

[0031] When the number of users who have returned to work reaches a certain amount: the resumption rate is determined based on the number of users who have returned to work and the total number of users within the statistical scope; the resumption rate is determined based on the total electricity consumption of users within the statistical scope on that day and the total electricity consumption base of users within the statistical scope.

[0032] Based on the same inventive concept, the present invention also provides a system for determining the resumption of work and production of an enterprise based on the power base, including:

[0033] The phase division module is used to divide the analyzed resumption of work and production days into multiple phases;

[0034] The similar day determination module is used to determine the most similar historical days in the same period of the analyzed resumption of work and production stages based on the impact of multiple dimensions;

[0035] The electricity base calculation module is used to determine the electricity base of each stage based on the electricity consumption data of each stage and the most similar historical day in the same period;

[0036] The resumption of work and production rate calculation module is used to determine the resumption of work and production rate based on the actual electricity consumption on the analyzed resumption of work and production day and the electricity base.

[0037] Based on the same inventive concept, the present invention also provides a computer device, including a processor and a storage medium;

[0038] The storage medium is used to store a program, wherein the program is designed to implement a method of determining the resumption of work and production of an enterprise based on the power base of the present invention;

[0039] The processor is configured to run the program stored in the storage medium.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] The present invention provides a method, system, and computer device for determining the resumption of work and production of an enterprise based on the electricity base, including: dividing the analyzed resumption of work and production day into multiple stages; determining the most similar historical days of the same period for each stage of the analyzed resumption of work and production day based on multi-dimensional influences; determining the electricity base for each stage based on the electricity consumption data of each stage and the most similar historical days of the same period corresponding to each stage; determining the resumption of work and production rate based on the actual electricity consumption of the analyzed resumption of work and production day and the electricity base; the present invention divides the time range of the resumption of work and production analysis into multiple time stages, and intelligently selects the corresponding electricity base according to the characteristics of each time stage, thereby improving the accuracy of the calculation of the resumption of work and production of the enterprise;

[0042] The technical means provided by the present invention also comprehensively considers the impact of multiple dimensions such as seasons, working days, weekends, holidays, weather and temperature on electricity consumption in different industries, intelligently selects the corresponding electricity base, and further improves the accuracy of calculations on the resumption of work and production of enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a flow chart of the method for determining the resumption of work and production of an enterprise based on the power base of the present invention;

[0044] Figure 2 This is a block diagram of the system for determining the resumption of work and production of an enterprise based on the electricity base of the present invention. DETAILED DESCRIPTION

[0045] In order to better understand the present invention, the present invention is further described below with reference to the accompanying drawings and examples.

[0046] Example 1:

[0047] like Figure 1 As shown, the present invention provides a method for determining the resumption of work and production of an enterprise based on the power base, including:

[0048] S1: Divide the resumption of work and production days to be analyzed into multiple stages;

[0049] S2: Based on the impact of multiple dimensions, determine the most similar historical date in the same period of each stage of the resumption of work and production being analyzed;

[0050] S3: Determine the electricity base for each stage based on the electricity consumption data of each stage and the most similar historical day in the same period;

[0051] S4: Determine the resumption rate of work and production based on the actual electricity consumption on the analyzed resumption day and the electricity base.

[0052] Since the present invention comprehensively considers the impact of multiple dimensions such as seasons, working days, weekends, holidays, weather and temperature on electricity consumption in different industries, and intelligently selects the corresponding electricity base according to the characteristics of each time stage, it improves the accuracy of the calculation of the resumption of work and production of enterprises.

[0053] First, the variables involved in the present invention are described:

[0054] Since the present invention is based on finding the most similar day in the same period based on season, weather, temperature, working days, weekends and holidays, the electricity consumption of the most similar day in the same period is used as the electricity consumption base. Assume x i represents the i-th day of this year, y j represents the electricity consumption on the jth day of the same period last year. Assume that X(x1,x2,x3,…,x n ) represents the time range of this year’s electricity data, Y(y1,y2,y3,…,y m ) represents the time range of electricity consumption data of the same period last year, d ij Represents date x i and date y j The distance between them. D n×m Represents the distance matrix between time range X and time range Y. M(x i ,y j ) represents the date x i and date y j The matching relationship between them, F(x i ,y j ) represents the date x i and date y j One-to-one matching relationship between gx i Represents date x i It is the gxth day of the Gregorian calendar that year. i God, gy j Indicates date y j It is the gy of the Gregorian calendar that year. j God, nx i Represents date x i It is the nth regional holiday of the year i God, nyj Indicates date y j It is the nyth regional holiday of the year j Day.cx i Represents date x i Celsius temperature, cy j Indicates date y j Celsius temperature.

[0055] Date x i and date y j The distance calculation method is as follows

[0056]

[0057] Among them, K represents the total number of dimensions, d k Reflects the distance of the kth dimension, a k is the weight coefficient, For enterprises in different industries, parameter a k The values ​​of are different.

[0058] This embodiment takes the Chinese Spring Festival as an example and examines the distance in four dimensions, such as d1 reflects the distance in the season dimension, d2 reflects the distance in the work situation dimension, such as the distance in the weekday, (weekend) weekend, and holiday dimensions, d3 reflects the distance in the weather dimension, and d4 reflects the distance in the temperature dimension.

[0059] d1: The distance in the seasonal dimension can be expressed as the order of the days of the year. The smaller the distance, the more similar it is. Therefore, the calculation formula of d1 is shown in formula (1):

[0060]

[0061] Here, Y1 is the time of a Gregorian calendar year, and the value can be referenced to 365. Y2 is the time of a local calendar year. Taking the Chinese lunar calendar year as an example, such as 2020, it is 383.

[0062] For example, March 26th is spring, which is the 85th day in 2021 and the 86th day in 2020 (the difference of one day is determined by whether February is a leap month), so the difference can basically be ignored.

[0063] At the same time, because local festivals are affected by local calendars, they cannot be completely replaced by the Gregorian calendar. For example, China's Spring Festival needs to use the lunar calendar because the most similar day to the 29th day of the twelfth lunar month this year is definitely the 29th day of the twelfth lunar month last year. However, there is a certain relationship between the local calendar and the Gregorian calendar that can be converted. For example, the first day of the Lunar New Year in 2020 is January 25, and the first day of the Lunar New Year in 2021 is February 12. Therefore, we can use the function: gx i =f(nx i ), where f() can be expressed as: gxi =nx i +Z converts the Chinese lunar calendar to the Gregorian calendar (Z is the conversion coefficient). In 2020, the correspondence between the first day of the lunar calendar and the Gregorian calendar is: gx i =nx i +24; In 2021, the correspondence between the first day of the lunar calendar and the Gregorian calendar is: gx i =nx i +42 and so on.

[0064] Thanksgiving Day is a national holiday in the United States. It is on the fourth Thursday of November. Although it is generally a day off, many units (such as schools) keep it from Thursday to Sunday. In 2019, it is November 28, but in 2021 it is November 25. Therefore, the corresponding relationship between Thanksgiving Day in 2019 and the Gregorian calendar is: gx i =nx i +333; the corresponding relationship with the Gregorian calendar in 2021 is: gx i =nx i +330, etc. Although the value of Z is different, the Gregorian calendar is used, so only Y1 can be used for calculation.

[0065] d2 is a distance table for working days, weekends, and holidays. The distance between each element can be determined by a table lookup method, for example, it can be Table 1.

[0066] Table 1: Distance table of working days, weekends and holidays

[0067] <![CDATA[d2]]> working day weekends Holidays working day 0 0.7 1 weekends 0.7 0 0.3 Holidays 1 0.3 0

[0068] In this embodiment, 0.3 and 0.7 are obtained by analyzing historical data. The analysis method can use conventional methods such as clustering historical data and taking the average value and square root. The specific analysis algorithm can be reasonably selected based on the historical data of each enterprise, and will not be repeated here.

[0069] Based on the expectation and variance of the output curve of the photovoltaic power station, the EM clustering algorithm is used to cluster a total of 33 weather types: sunny, cloudy, overcast, showers, thunderstorms, thunderstorms with hail, sleet, light rain, moderate rain, heavy rain, rainstorm, heavy rainstorm, extremely heavy rainstorm, snow showers, light snow, moderate snow, heavy snow, blizzard, fog, freezing rain, sandstorm, light rain-moderate rain, moderate rain-heavy rain, heavy rain-rainstorm, rainstorm-heavy rain, heavy rain-extraordinary rainstorm, light snow-moderate snow, moderate snow-heavy snow, heavy snow-blizzard, floating dust, blowing sand, strong sandstorm, and haze. The clustering method will be regularly revised and updated. Among them, sunny, showers, thunderstorms, and thunderstorms with hail are grouped as weather category A; cloudy, overcast, light rain, moderate rain, heavy rain, light rain-moderate rain, moderate rain-heavy rain, and heavy rain-torrential rain are grouped as weather category B; snow showers, light snow, moderate snow, heavy snow, blizzards, freezing rain, light snow-moderate snow, moderate snow-heavy snow, and heavy snow-torrential rain are grouped as weather category C; and floating dust, blowing sand, strong sandstorms, haze, sleet, heavy rain, heavy rainstorm, extremely heavy rainstorm, heavy rainstorm-heavy rainstorm, and heavy rainstorm-extraordinarily heavy rainstorm are grouped as weather category D. The distance d3 between the same weather type is 0, and the distance d3 between different weather types within the same weather category is 0.25. The distances between elements in the distance d3 between weather types in different weather categories can be determined by table lookup, for example, as shown in Table 2.

[0070] Table 2: Distance between weather types in different weather categories

[0071] <![CDATA[d3]]> Weather Category A Weather Category B Weather Category C Weather Category D Weather Category A \ 0.6 0.85 1 Weather Category B 0.6 \ 0.6 0.85 Weather Category C 0.85 0.6 \ 0.6 Weather Category D 1 0.85 0.6 \

[0072] In this embodiment, 0.6 and 0.85 are obtained by analyzing data from previous years.

[0073] d4 is shown in formula (2).

[0074] d4=(cx i -cy j ) / 60 formula (2)

[0075] The following describes step S2, which involves determining the most similar historical dates for each stage of the resumption of work and production, based on multi-dimensional influences, using a specific example:

[0076] (1) i takes the value 1, j takes the value 1, calculate the date x i and date y j The distance d ij ;

[0077] (2) Record date matching relationship M(x i ,y j );

[0078] (3) If date x i It is not the last day of this year's electricity range, date yj If the date x is not the last day of the same period last year, go to (4). i It is not the last day of this year's electricity range, date y j Is the last day of the same period last year, go to (6), if date x i It is the last day of this year's electricity range, date y j If the date x is not the last day of the same period last year, go to (7). i It is the last day of this year's electricity range, date y j If it is the last day of the same period last year, go to (8);

[0079] (4) Calculate date x i and date y j+1 The distance d i,j+1 , calculate date x i+1 and date y j The distance d i+1,j , calculate date x i+1 and date y j+1 The distance d i+1,j+1 ;

[0080] (5) From d i,j+1 , d i+1,j and d i+1,j+1 Choose the smallest one among them, if d i,j+1 Minimum, j increases by 1, if d i+1,j Minimum, i increases by 1, if d i+1,j+1 Minimum, i increases by 1, j increases by 1, go to (2);

[0081] (6) Calculate date x i+1 and date y j The distance d i+1,j , i increases by 1, go to (2);

[0082] (7) Calculate date x i and date y j+1 The distance d i,j+1 , j increases by 1, go to (2);

[0083] (8) i takes the value 1;

[0084] (9) Judgment and x i Matching y j Is it unique? If so, set M(x i ,y j ) Add F, go to (11), otherwise, go to (10);

[0085] (10) From x i Matching multiple y jSelect d ij The smallest one, M(x i ,y j )Add F, turn (11)

[0086] (11) If date x i If it is the last day of the missing electricity interval, then the most similar date for each day in the missing electricity interval already exists in F, otherwise, go to (9).

[0087] Step S3 determines the electricity base of each stage based on the electricity consumption data of each stage and the most similar historical day in the same period, as follows:

[0088] The time range for the resumption of work and production analysis is divided into five stages based on holiday electricity consumption: before the holiday, the transition period before the holiday, the holiday day, the transition period after the holiday, and the five time periods after the holiday. The corresponding electricity base is intelligently selected based on the characteristics of each time period. The transition period increases daily and smoothly transitions. The following describes the specific implementation of the present invention using the Chinese Lunar New Year (Spring Festival) as an example:

[0089] (1) Before the Spring Festival, the above method is used to select the most similar day in the same period, and the electricity consumption on the most similar day in the same period is used as the electricity consumption base.

[0090] (2) After the Spring Festival, the above method is used to select the most similar day in the same period, and the electricity consumption on the most similar day in the same period is used as the electricity consumption base.

[0091] (3) During the Spring Festival holiday, the fixed base number corresponding to each holiday can be obtained from the historical electricity consumption data. Here, taking the Spring Festival as an example, the average daily electricity consumption of the month ranked third among the 12 months of the previous year (upper 1 / 4 quartile) is used as the electricity base number.

[0092] (4) During the transition period before the Spring Festival, the transition is carried out by alternating the electricity consumption of the most similar day during the same period and the average daily electricity consumption of the month ranked third among the 12 months of the previous year in a proportional manner. If the transition period is 15 days, the benchmark electricity consumption on the first day of the transition period before the Spring Festival is: the electricity consumption of the most similar day during the same period * 14 / 15 + the average daily electricity consumption of the month ranked third among the 12 months of the previous year * 1 / 15; the benchmark electricity consumption on the second day of the transition period is the electricity consumption of the most similar day during the same period * 13 / 15 + the average daily electricity consumption of the month ranked third among the 12 months of the previous year * 2 / 15, and so on.

[0093] (5) During the transition period after the Spring Festival, the transition is carried out by alternating the electricity consumption of the most similar day during the same period and the average daily electricity consumption of the month ranked third among the 12 months of the previous year in a proportional manner. If the transition period is 15 days, the benchmark electricity consumption on the first day of the transition period after the Spring Festival is: the electricity consumption of the most similar day during the same period * 1 / 15 + the average daily electricity consumption of the month ranked third among the 12 months of the previous year * 14 / 15; the benchmark electricity consumption on the second day of the transition period is the electricity consumption of the most similar day during the same period * 2 / 15 + the average daily electricity consumption of the month ranked third among the 12 months of the previous year * 13 / 15, and so on.

[0094] Step S4: Determine the resumption rate based on the actual power consumption on the resumption day and the power base. Specifically, the following method can be used:

[0095] The formal description of the resumption of work and production analysis rules is as follows:

[0096] For users returning to work: daily power consumption / smart power base ≥ threshold

[0097] Return to work rate = number of users who have returned to work within the statistical scope / total number of users within the statistical scope * 100%

[0098] Recovery rate = total daily electricity consumption of users within the statistical range / total smart electricity base of users within the statistical range * 100%

[0099] Among them, the intelligent power base is determined according to the base intelligent selection strategy.

[0100] Example 2:

[0101] Based on the same inventive concept, the present invention also provides a system for determining the resumption of work and production of enterprises based on the power base, such as Figure 2 As shown, including:

[0102] The phase division module is used to divide the analyzed resumption of work and production days into multiple phases;

[0103] The similar day determination module is used to determine the most similar historical days in the same period of the analyzed resumption of work and production stages based on the impact of multiple dimensions;

[0104] The electricity base calculation module is used to determine the electricity base of each stage based on the electricity consumption data of each stage and the most similar historical day in the same period;

[0105] The resumption of work and production rate calculation module is used to determine the resumption of work and production rate based on the actual electricity consumption on the analyzed resumption of work and production day and the electricity base.

[0106] Each module in this system is designed to implement the method of Example 1. For specific implementation, please refer to Example 1 and will not be repeated here.

[0107] Example 3:

[0108] In order to implement the above method and system, the present invention also provides a computer device, including a processor and a storage medium;

[0109] The storage medium is used to store a program, wherein the program is designed to implement a method of determining the resumption of work and production of an enterprise based on the power base of the present invention;

[0110] The processor is configured to run the program stored in the storage medium.

[0111] The specific implementation method can be referred to Example 1, which will not be repeated here.

[0112] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0113] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0114] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0115] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0116] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0117] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are included in the scope of the claims of the present invention to be approved.

Claims

1. A method for determining whether an enterprise should resume work and production based on electricity consumption, characterized in that: include: Divide the analyzed resumption of work and production days into multiple stages; Based on the impact of multiple dimensions, determine the most similar historical date for each stage of the resumption of work and production being analyzed; Based on the electricity consumption data of each stage and the most similar historical day in the same period corresponding to each stage, the electricity base of each stage is determined; Determine the resumption rate based on the actual electricity consumption on the analyzed resumption day and the electricity base; The stages include: before the holiday, the transition period before the holiday, the holiday day, the transition period after the holiday, and after the holiday; The obtaining of the most similar daily electricity consumption data in the same period of each stage as the electricity base of the stage includes: When the period is before / after a holiday, the electricity consumption data of the most similar day in the same period of the period is used as the electricity consumption base for the period; When the stage is a holiday, a fixed base number corresponding to the holiday is obtained from historical electricity consumption data according to the holiday type as the electricity base number for the stage; When the stage is a transition period before a holiday, the power base corresponding to the pre-holiday and the power base corresponding to the holiday day are used to transition in a proportional alternating rise and fall mode to obtain the power base of the stage; When the stage is a transition period after a holiday, based on the power base corresponding to the post-holiday and the power base corresponding to the holiday day, a proportional alternating rise and fall mode is adopted to transition to obtain the power base of the stage; Based on the multi-dimensional impact, the most similar historical dates for the respective stages of the resumption of work and production are determined, including: Based on the impact of multiple dimensions, a predetermined distance calculation formula is used to calculate the distance d between the first day of the resumption of work and production and the same day in the same period of history. 11 ; and record the date matching relationship M(x1, y1); Use the predetermined distance calculation formula in turn to calculate the distance between each date x in the resumption of work and production days being analyzed. i and date y j+1 The distance d i,j+1 , date x i+1 and date y j The distance d i+1,j , date x i+1 and date y j+1 The distance d i+1,j+1 ; From the d i,j+1 , d i+1,j and d i+1,j+1 Select the smallest one and record the date matching relationship of the smallest one; Based on the date matching relationship of all records, determine the date matching relationship with the smallest distance among the matching days corresponding to each day of resumption of work and production being analyzed, and generate the most similar historical day in the same period.

2. The method according to claim 1, wherein The distance calculation formula is as follows: Where d is the distance between any day within the range of resumption of work and production being analyzed and any day in the historical year; K represents the total number of dimensions, Reflect the The distance in dimensions, For the Dimension weight coefficient.

3. The method according to claim 1 or 2, wherein: The dimensions include: season dimension, work situation dimension, weather dimension and temperature dimension; The working conditions include: weekdays, weekends and holidays.

4. The method according to claim 2, wherein The dimension weight coefficient is determined by the industry in which the enterprise that resumes work and production is located.

5. A system for determining the resumption of work and production of enterprises based on the power base, characterized by: include: The phase division module is used to divide the analyzed resumption of work and production days into multiple phases; The similar day determination module is used to determine the most similar historical days in the same period of the analyzed resumption of work and production stages based on the impact of multiple dimensions; The electricity base calculation module is used to determine the electricity base of each stage based on the electricity consumption data of each stage and the most similar historical day in the same period; A resumption rate calculation module, configured to determine the resumption rate based on the actual power consumption on the analyzed resumption day and the power base; The stages include: before the holiday, the transition period before the holiday, the holiday day, the transition period after the holiday, and after the holiday; The obtaining of the most similar daily electricity consumption data in the same period of each stage as the electricity base of the stage includes: When the period is before / after a holiday, the electricity consumption data of the most similar day in the same period of the period is used as the electricity consumption base for the period; When the stage is a holiday, a fixed base number corresponding to the holiday is obtained from historical electricity consumption data according to the holiday type as the electricity base number for the stage; When the stage is a transition period before a holiday, the power base corresponding to the pre-holiday and the power base corresponding to the holiday day are used to transition in a proportional alternating rise and fall mode to obtain the power base of the stage; When the stage is a transition period after a holiday, based on the power base corresponding to the post-holiday and the power base corresponding to the holiday day, a proportional alternating rise and fall mode is adopted to transition to obtain the power base of the stage; Based on the multi-dimensional impact, the most similar historical dates for the respective stages of the resumption of work and production are determined, including: Based on the impact of multiple dimensions, a predetermined distance calculation formula is used to calculate the distance d between the first day of the resumption of work and production and the same day in the same period of history. 11 ; and record the date matching relationship M(x1, y1); Use the predetermined distance calculation formula in turn to calculate the distance between each date x in the resumption of work and production days being analyzed. i and date y j+1 The distance d i,j+1 , date x i+1 and date y j The distance d i+1,j , date x i+1 and date y j+1 The distance d i+1,j+1 ; From the d i,j+1 , d i+1,j and d i+1,j+1 Select the smallest one and record the date matching relationship of the smallest one; Based on the date matching relationship of all records, determine the date matching relationship with the smallest distance among the matching days corresponding to each day of resumption of work and production being analyzed, and generate the most similar historical day in the same period.

6. A computer device, characterized in that: including processors and storage media; The storage medium is used to store a program, wherein the program is designed based on implementing the method according to any one of claims 1 to 4; The processor is configured to run the program stored in the storage medium.

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