A method and terminal for correcting electric power data

Abstract

The present invention discloses a method and terminal for correcting electric power data; the present invention obtains the electric power consumption data and GDP data of each industry in a region within a preset time series; calculates the electric power data deviation rate index of each industry in each year within the time series based on the electric power consumption data and the GDP data; corrects the electric power consumption data based on the electric power data deviation rate index; utilizes the characteristics of the development correlation between electric power data and economic data, utilizes economic data, and calculates the electric power data deviation rate index of each industry in a specific time series in combination with the economic data and the electric power data, thereby correcting the electric power data and improving the accuracy and effectiveness of the electric power data.

Description

Technical Field

[0001] The present invention relates to the technical field of power consumption data analysis, and in particular to a power data correction method and terminal. Background Art

[0002] Electricity is one of the basic driving forces for the development of the national economy. With the improvement of electrification level, the role of electricity development in economic growth has become more and more obvious. Statistical analysis shows that there is a high correlation between electricity consumption and economic development.

[0003] When collecting power data, a small amount of power data may contain errors due to interference from various external environments, so there may be a need to correct the power data. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method and a terminal for correcting power data, which can correct the power data and improve the accuracy of the power data.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] A method for correcting power data, comprising the steps of:

[0007] S1. Obtain electricity consumption data and GDP data of various industries in the region within the preset time series;

[0008] S2. Calculate the power data deviation rate index of each industry in each year within the time series based on the power consumption data and the GDP data;

[0009] S3. Correcting the power consumption data according to the power data deviation rate indicator.

[0010] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0011] A power data correction terminal comprises a processor, a memory and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps in the above power data correction method when executing the computer program.

[0012] The beneficial effects of the present invention are as follows: the present invention utilizes the characteristics of the development correlation between power data and economic data, utilizes economic data, and combines economic data and power data to calculate the power data deviation rate index of each industry within a specific time series, thereby correcting the power data and improving the accuracy and effectiveness of the power data. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1A flowchart of a method for correcting power data according to an embodiment of the present invention;

[0014] Figure 2 A structural diagram of a power data correction terminal according to an embodiment of the present invention;

[0015] Figure 3 An example graph of industrial coordination degree of power indicators of various industries in four regions within a preset time series in a method for correcting power data in an embodiment of the present invention;

[0016] Figure 4 An example graph of industrial coordination degree broken lines of industrial economic indicators of four regions in a preset time series in a method for correcting power data in an embodiment of the present invention;

[0017] Description of labels:

[0018] 1. A power data correction terminal; 2. A processor; 3. A memory. DETAILED DESCRIPTION

[0019] In order to explain the technical content, achieved objectives and effects of the present invention in detail, the following is an explanation in combination with the implementation modes and the accompanying drawings.

[0020] Please refer to Figure 1 as well as Figure 2 , a method for correcting power data, comprising the steps of:

[0021] S1. Obtain electricity consumption data and GDP data of various industries in the region within the preset time series;

[0022] S2. Calculate the power data deviation rate index of each industry in each year within the time series based on the power consumption data and the GDP data;

[0023] S3. Correcting the power consumption data according to the power data deviation rate indicator.

[0024] From the above description, it can be seen that the beneficial effects of the present invention are: the present invention utilizes the characteristics of the development correlation between power data and economic data, utilizes economic data, combines economic data and power data to calculate the power data deviation rate index of each industry in a specific time series, thereby correcting the power data and improving the accuracy and effectiveness of the power data.

[0025] Furthermore, the step S2 specifically includes:

[0026] S21, standardizing the electricity consumption data of each industry and the GDP data to obtain standardized data;

[0027] S22. Calculate the annual power index industry coordination degree and economic index industry coordination degree according to the standardized data;

[0028] S23, calculating the deviation rate of the coordinated development degree between the power indicators and the economic indicators each year according to the industrial coordination degree of the power indicators and the industrial coordination degree of the economic indicators each year;

[0029] S24. Calculate the corresponding power data deviation rate index according to the coordinated development degree deviation rate each year.

[0030] From the above description, it can be seen that the standardized data can be used to calculate the industrial coordination degree of power indicators and the industrial coordination degree of economic indicators among various industries. The industrial coordination degree of power indicators can provide a new perspective for analyzing the degree of coordinated development among industries, and can be combined with the industrial coordination degree of economic indicators for verification, so that relevant departments can make timely judgments on the development and transformation and upgrading of industries. Through further calculation of the industrial coordination degree of power indicators and the industrial coordination degree of economic indicators, the power data deviation rate index is finally obtained, which indicates the deviation between power data and economic data, and is used to correct power data.

[0031] Furthermore, the step S21 is specifically as follows:

[0032] The electricity consumption data and GDP data of each industry are standardized:

[0033]

[0034]

[0035] Among them, K ita represents the standardized data of electricity consumption of the ith industry in the tth year within the preset time series, max(k ia ) represents the maximum value of the electricity consumption data of the i-th industry in the preset time series, min(k ia ) represents the minimum value of the electricity consumption data of the ith industry within the preset time series, k ita represents the electricity consumption data of the ith industry in the tth year in the preset time series, K itb represents the standardized data of GDP data of the ith industry in the tth year within the preset time series, max(k ib ) represents the maximum value of GDP data of the ith industry in the preset time series, min(k ib ) represents the minimum GDP data value of the i-th industry in the preset time series, k itb Represents the GDP data of the ith industry in the tth year in the preset time series.

[0036] From the above description, it can be seen that the electricity consumption data by industry and the GDP data by industry are standardized through the above formula.

[0037] Furthermore, the step S22 specifically includes:

[0038] S221. Calculate the annual power index industry coupling degree and economic index industry coupling degree according to the standardized data:

[0039]

[0040]

[0041] Among them, X ta K represents the industry coupling degree of power indicators in the tth year in the preset time series, ita represents the standardized data of electricity consumption of the ith industry in the tth year within the preset time series, n represents the total number of industries, K itb The standardized data representing the GDP data of the ith industry in the tth year within the preset time series;

[0042] S222. Calculate the power index industry coordination degree and the economic index industry coordination degree according to the power index coupling degree and the industry index coupling degree:

[0043]

[0044]

[0045] Among them, Y ta represents the industrial coordination degree of power indicators in the tth year within the preset time series, X ta K represents the industry coupling degree of power indicators in the tth year in the preset time series, ita represents the standardized data of electricity consumption of the ith industry in the tth year in the preset time series, n represents the total number of industries, α ita represents the percentage of electricity consumption of the ith industry in the tth year to the total electricity consumption of all industries, and:

[0046]

[0047] Y tb represents the coordination degree of economic indicators in the tth year of the preset time series, X tb represents the industrial coupling degree of economic indicators in the tth year in the preset time series, K itb represents the standardized data of GDP data of the ith industry in the tth year in the preset time series, α itb It represents the percentage of the GDP of the ith industry in the tth year to the total GDP of all industries, and:

[0048]

[0049] From the above description, it can be seen that the annual power index industry coupling degree and economic index industry coupling degree are calculated based on standardized data, so as to further calculate the power index industry coordination degree and economic index industry coordination degree among industries.

[0050] Furthermore, the step S23 is specifically as follows:

[0051] According to the annual power index industry coordination degree Y ta and the industrial coordination degree Y of the economic indicator tb , calculate the deviation rate of the coordinated development degree between the power indicators and economic indicators each year:

[0052] ε t =Y ta / Y tb -1.

[0053] From the above description, it can be seen that by subtracting 1 from the ratio between the industrial coordination degree of power indicators and the industrial coordination degree of economic indicators, we can get the difference ratio between the two, that is, the deviation rate of the degree of coordinated development between power indicators and economic indicators, which is used for the calculation of subsequent power data deviation rate indicators.

[0054] Furthermore, the step S24 is specifically as follows:

[0055] According to the annual deviation rate of the coordinated development level ε t Calculate the corresponding power data deviation rate indicator:

[0056]

[0057] Among them, K ita represents the standardized data of electricity consumption of the ith industry in the tth year within the preset time series, α ita Indicates the percentage of electricity consumption of the ith industry in the tth year to the total electricity consumption of all industries, K itb represents the standardized data of GDP data of the ith industry in the tth year in the preset time series, α itb represents the percentage of the GDP of the ith industry in the tth year to the total GDP of all industries, X ta represents the industry coupling degree of power indicators in the tth year in the preset time series, X tb It represents the industrial coupling degree of economic indicators in the tth year in the preset time series, and n represents the total number of industries.

[0058] It can be seen from the above description that the power data deviation rate indicator used for power data correction is finally calculated by the above formula.

[0059] Furthermore, the step S3 is specifically as follows:

[0060] The power consumption data is corrected according to the power data deviation rate index, and the correction formula is as follows:

[0061] k′ ita =k ita *(1+ε it );

[0062] Among them, k ita represents the electricity consumption data of the ith industry in the tth year, ε it Represents the power data deviation rate index, k′ ita Indicates k ita The correction result.

[0063] From the above description, it can be seen that according to the power data deviation rate index, the power data is corrected by the above correction formula, so as to obtain power data that is more in line with the economic data and improve the validity of the power data.

[0064] Please refer to Figure 2 , a power data correction terminal includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps in the above power data correction method when executing the computer program.

[0065] A method and terminal for correcting electric power data of the present invention are applicable to a scenario where electric power data and economic data can be collected but the electric power data needs to be corrected.

[0066] Please refer to Figure 1 , Figure 3 and Figure 4 , Embodiment 1 of the present invention is:

[0067] A method for correcting power data, comprising the steps of:

[0068] S1. Obtain electricity consumption data and GDP data of various industries in the region within the preset time series;

[0069] In this embodiment, considering the relationship between the validity of the example and the authenticity of the data, the industrial classification method stipulated by the state is adopted, and the coordinated development degree between the primary, secondary and tertiary industries in some cities in Fujian Province is used as the analysis object. First, the annual electricity consumption data of the primary, secondary and tertiary industries in a certain area in the past ten years are collected from the power department of a certain area as the industrial electricity consumption data set. The annual output value of the primary, secondary and tertiary industries in the past ten years is collected from the statistics bureau of the area as industrial economic data. In this example, the coordinated development of the tertiary industries in Fuzhou and Ningde in the coastal areas of Fujian and Sanming and Longyan in the inland areas is selected as the research object, and the corresponding electricity data and GDP data are obtained.

[0070] Among them, each industry in this embodiment represents the primary, secondary and tertiary industries classified by the industrial classification method prescribed by the state. In other equivalent embodiments, each industry can also be certain specific industries, or industry types obtained by other classification methods.

[0071] S2. Calculate the power data deviation rate index of each industry in each year within the time series based on the power consumption data and the GDP data;

[0072] The step S2 specifically includes:

[0073] S21, standardizing the electricity consumption data of each industry and the GDP data to obtain standardized data;

[0074] The step S21 is specifically as follows:

[0075] The electricity consumption data and GDP data of each industry are standardized:

[0076]

[0077]

[0078] Among them, K ita represents the standardized data of electricity consumption of the ith industry in the tth year within the preset time series, max(k ia ) represents the maximum value of the electricity consumption data of the i-th industry in the preset time series, min(k ia ) represents the minimum value of the electricity consumption data of the ith industry within the preset time series, k ita represents the electricity consumption data of the ith industry in the tth year in the preset time series, K itb represents the standardized data of GDP data of the ith industry in the tth year within the preset time series, max(k ib ) represents the maximum value of GDP data of the ith industry in the preset time series, min(k ib ) represents the minimum GDP data value of the i-th industry in the preset time series, k itb Represents the GDP data of the ith industry in the tth year in the preset time series.

[0079] S22. Calculate the annual power index industry coordination degree and economic index industry coordination degree according to the standardized data;

[0080] The step S22 specifically includes:

[0081] S221. Calculate the annual power index industry coupling degree and economic index industry coupling degree according to the standardized data:

[0082]

[0083]

[0084] Among them, X ta K represents the industry coupling degree of power indicators in the tth year in the preset time series, ita represents the standardized data of electricity consumption of the ith industry in the tth year within the preset time series, n represents the total number of industries, K itb The standardized data representing the GDP data of the ith industry in the tth year within the preset time series;

[0085] S222. Calculate the power index industry coordination degree and the economic index industry coordination degree according to the power index coupling degree and the industry index coupling degree:

[0086]

[0087]

[0088] Among them, Y ta represents the industrial coordination degree of power indicators in the tth year within the preset time series, X ta K represents the industry coupling degree of power indicators in the tth year in the preset time series, ita represents the standardized data of electricity consumption of the ith industry in the tth year in the preset time series, n represents the total number of industries, α ita represents the percentage of electricity consumption of the ith industry in the tth year to the total electricity consumption of all industries, and:

[0089]

[0090] Y tb represents the coordination degree of economic indicators in the tth year of the preset time series, X tb represents the industrial coupling degree of economic indicators in the tth year in the preset time series, K itb represents the standardized data of GDP data of the ith industry in the tth year in the preset time series, α itb It represents the percentage of the GDP of the ith industry in the tth year to the total GDP of all industries, and:

[0091]

[0092] The collected power data and GDP data of the primary, secondary and tertiary industries are standardized, and then the industrial coupling degree is calculated based on the standardized data of the three industries. The power index industrial coordination degree and economic index industrial coordination degree, which can better show the coordinated development level between different industries, are calculated from the industrial coupling degree and the percentage of the power consumption of the three industries in the total power consumption of the industry. The relative status of the coordinated development of the industries in the four cities over the past 10 years under the power data and economic data is obtained. The data view is as follows: Figure 3 and Figure 4 shown.

[0093] From the results, we can find that from the perspective of electricity, the overall trend of the four cities is ultimately growth. Fuzhou's coordinated development degree has risen steadily, while the others have slightly fluctuated. Sanming's coordinated development degree fluctuates greatly. The main reason is that the decline in electricity consumption in the secondary industry in 2016 has led to less coordinated consumption distribution of electricity consumption in the three industries than in the previous year. The decline in coordination in Longyan and Ningde in the handover year is also due to similar reasons. From the figure, Fuzhou's coordinated development of the three industries is the best, but the other three cities also maintain a steady upward trend.

[0094] From the perspective of output value, the coordination between the three industries in Fuzhou, Ningde, Sanming and Longyan has been growing steadily, basically maintaining a stable growth rate every year, and the level of coordinated development is getting higher and higher. Figure 1 and Figure 2 In comparison, although the degree of coordinated industrial development obtained from power big data has fluctuated, it is only a local phenomenon. It may be a decline in electricity consumption caused by climate or policy influences, but it will eventually move towards a more coordinated level, which is generally consistent with the results obtained from economic indicators.

[0095] When analyzing and verifying previous data, the power big data method can provide a new perspective for analyzing the degree of coordinated development among industries, so that the government can make timely judgments on the development and transformation and upgrading of industries. The model can also be applied to multiple different industrial clusters according to actual conditions, pointing out the direction for industrial development and promoting high-quality development of the local economy.

[0096] S23, calculating the deviation rate of the coordinated development degree between the power indicators and the economic indicators each year according to the industrial coordination degree of the power indicators and the industrial coordination degree of the economic indicators each year;

[0097] The step S23 is specifically as follows:

[0098] According to the annual power index industry coordination degree Y ta and the industrial coordination degree Y of the economic indicator tb , calculate the deviation rate of the coordinated development degree between the power indicators and economic indicators each year:

[0099] ε t =Y ta / Y tb -1.

[0100] S24, calculating the corresponding power data deviation rate index according to the coordinated development degree deviation rate each year;

[0101] The step S24 is specifically as follows:

[0102] According to the annual deviation rate of the coordinated development level ε t Calculate the corresponding power data deviation rate indicator:

[0103]

[0104] Among them, K ita represents the standardized data of electricity consumption of the ith industry in the tth year within the preset time series, α ita Indicates the percentage of electricity consumption of the ith industry in the tth year to the total electricity consumption of all industries, K itb represents the standardized data of GDP data of the ith industry in the tth year in the preset time series, α itb represents the percentage of the GDP of the ith industry in the tth year to the total GDP of all industries, X ta represents the industry coupling degree of power indicators in the tth year in the preset time series, X tb It represents the industrial coupling degree of economic indicators in the tth year in the preset time series, and n represents the total number of industries.

[0105] S3, correcting the power consumption data according to the power data deviation rate indicator;

[0106] The step S3 is specifically as follows:

[0107] The power consumption data is corrected according to the power data deviation rate index, and the correction formula is as follows:

[0108] k′ ita =k ita *(1+ε it );

[0109] Among them, k ita represents the electricity consumption data of the ith industry in the tth year, ε it Represents the power data deviation rate index, k′ ita Indicates k ita The correction result.

[0110] Please refer to Figure 2 , Embodiment 2 of the present invention is:

[0111] A power data correction terminal 1 includes a processor 2, a memory 3, and a computer program stored in the memory 3 and executable on the processor 2. When the processor 2 executes the computer program, the steps in the above power data correction method are implemented.

[0112] The present invention provides a method and terminal for correcting electric power data, the main principle of which is to utilize the correlation between electric power data and economic data, thereby correcting the electric power data in combination with the economic data.

[0113] In summary, the present invention utilizes the characteristics of the development correlation between power data and economic data, utilizes economic data, and combines economic data and power data to calculate the power data deviation rate index of each industry within a specific time series, thereby correcting the power data and improving the accuracy and effectiveness of the power data.

[0114] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for correcting power data, characterized in that: Includes steps: S1. Obtain electricity consumption data and GDP data of various industries in the region within the preset time series; S2. Calculate the power data deviation rate index of each industry in each year within the time series based on the power consumption data and the GDP data; The step S2 specifically includes: S21, standardizing the electricity consumption data of each industry and the GDP data to obtain standardized data; S22. Calculate the annual power index industry coordination degree and economic index industry coordination degree according to the standardized data; The step S22 specifically includes: S221. Calculate the annual power index industry coupling degree and economic index industry coupling degree according to the standardized data: ； ； in, Indicates the industry coupling degree of power indicators in the tth year in the preset time series, represents the standardized data of electricity consumption of the ith industry in the tth year in the preset time series, n represents the total number of industries, The standardized data representing the GDP data of the ith industry in the tth year within the preset time series; S222. Calculate the power index industry coordination degree and the economic index industry coordination degree according to the power index industry coupling degree and the economic index industry coupling degree: ； ； in, It represents the industrial coordination degree of power indicators in the tth year in the preset time series, Indicates the industry coupling degree of power indicators in the tth year in the preset time series, represents the standardized data of electricity consumption of the ith industry in the tth year in the preset time series, n represents the total number of industries, represents the percentage of electricity consumption of the ith industry in the tth year to the total electricity consumption of all industries, and: ； It represents the industrial coordination degree of economic indicators in the tth year of the preset time series. It represents the industrial coupling degree of economic indicators in the tth year in the preset time series. Represents the standardized data of GDP data of the ith industry in the tth year within the preset time series, It represents the percentage of the GDP of the ith industry in the tth year to the total GDP of all industries, and: ； S23, calculating the deviation rate of the coordinated development degree between the power indicators and the economic indicators each year according to the industrial coordination degree of the power indicators and the industrial coordination degree of the economic indicators each year; The step S23 is specifically as follows: According to the annual power indicators industry coordination Coordination with the economic indicators , calculate the deviation rate of the coordinated development degree between the power indicators and economic indicators each year: ； S24, calculating the corresponding power data deviation rate index according to the coordinated development degree deviation rate each year; The step S24 is specifically as follows: Deviation rate according to the degree of coordinated development each year Calculate the corresponding power data deviation rate indicator: ； in, The standardized data representing the electricity consumption data of the ith industry in the tth year within the preset time series, It represents the percentage of electricity consumption of the ith industry in the tth year to the total electricity consumption of all industries. Represents the standardized data of GDP data of the ith industry in the tth year within the preset time series, It represents the percentage of the GDP of the ith industry in the tth year to the total GDP of all industries. Indicates the industry coupling degree of power indicators in the tth year in the preset time series, It represents the industrial coupling degree of economic indicators in the tth year in the preset time series, and n represents the total number of industries; S3, correcting the power consumption data according to the power data deviation rate indicator; The step S3 is specifically as follows: The power consumption data is corrected according to the power data deviation rate index, and the correction formula is as follows: ； in, represents the electricity consumption data of the ith industry in the tth year, Indicates the power data deviation rate indicator, express The correction result.

2. A method for correcting power data according to claim 1, characterized in that: The step S21 is specifically as follows: The electricity consumption data of each industry and the GDP data are standardized respectively: ； ； in, represents the standardized data of electricity consumption of the ith industry in the tth year within the preset time series, represents the maximum value of electricity consumption data of the i-th industry in the preset time series, It represents the minimum value of electricity consumption data of each industry in the preset time series of the ith industry. represents the electricity consumption data of the ith industry in the tth year in the preset time series, represents the standardized data of GDP data of the ith industry in the tth year within the preset time series, It represents the maximum value of GDP data of the ith industry in the preset time series. It represents the minimum GDP data value of the ith industry in the preset time series. Represents the industrial GDP data of the ith industry in the tth year in the preset time series.

3. A power data correction terminal, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps in the method for correcting power data described in any one of claims 1-2 are implemented.

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