CN106600029A - Macro-economy predictive quantization correction method based on electric power data - Google Patents
Macro-economy predictive quantization correction method based on electric power data Download PDFInfo
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Abstract
The present invention discloses a macro-economy predictive quantization correction method based on electric power data. The statistics analysis displays that: there is high correlation between the electric power consumption and the economic development, the electric power provides power support for the national economy industry, but the economic development is deviated from the electric quantity increasing in recent years. The macro-economy predictive quantization correction method based on the electric power data perform correction of the macro-economy predictive quantization from the view of the electric power, and the correction content comprises data processing and construction of a macro-economy quantization correction model. The data processing comprises: obtaining electric power data, and rejecting the part influenced by non-economic factors; and obtaining the economic data and performing comparable price conversion. The macro-economy quantization correction model comprises an industry-classified economy quantization correction model and a GDP gross correction model. The macro-economy predictive quantization correction method based on the electric power data completes the correction of the macro-economy predictive quantization model based on the electric power data and predicts the electricity consumption of the whole society according to the corrected GDP gross so as to reduce the errors of the electricity consumption prediction through adoption of one single variation which is the economy amount.
Description
Technical field
The present invention relates to industrial structure prediction field, specifically a kind of macroeconomic forecasting quantization based on electric power data
Modification method.
Background technology
Electric power is one of baseline power of industrial sectors of national economy development, and with the raising of electrified level, electric power development exists
Effect in economic growth is obvious all the more.Statistical analysiss show there is high correlation between electricity consumption and economic development, use
Electricity, as one of three norms in gram strong index, is to reflect one of leading indicators of economical operation.But the 2014th, Jing in 2015
Ji is increased and is increased the phenomenon for but occurring in that " away from " with electricity, i.e. the economic development of high speed but correspond to the electricity consumption of Ultra-Low Speed
Increase.Can index on power consumption reflect Economic Operation, from Economic View how Accurate Prediction power consumption, be increasingly becoming electric power
The one big hot issue in demand behaviors field.The reason for analyzing its behind, the mainly accidentalia such as extreme meteorology in recent years
Affect.
The content of the invention
The technical problem to be solved is to provide a kind of macroeconomic forecasting based on electric power data and quantifies amendment
Method, contributes to explaining the relation between electricity consumption and economic growth, to reduce from economic total volume the mistake for predicting electricity needs
Difference.
For this purpose, the present invention is adopted the following technical scheme that：A kind of macroeconomic forecasting based on electric power data quantifies amendment
Method, it is characterised in that it is modified from electric power visual angle to macroeconomy quantitative prediction, described amendment content include data
Process and build macroeconomy and quantify correction model；
Described data processing is：Electric power data is obtained, the part that non-economic factors affect is rejected；Obtain economic data,
Carrying out can rate of exchange conversion；
Described macroeconomy quantifies correction model includes that branch trade economy quantifies correction model and GDP total amount amendment moulds
Type.
The present invention rejects the electricity consumption changing unit that the accidentalia such as meteorology cause, and is developed with branch trade power quantity predicting branch trade
Set out, have modified Macroeconomic Development curve, then predict Analyzing Total Electricity Consumption, so as to Accurate Prediction is caused by Macroeconomic Development
Need for electricity increase, perfect electric power demand forecasting method.
Further, the detailed process of the data processing is as follows：
1) electric power data is processed：Finding affects the important accidentalia of operation power in the sample phase, and is rejected (as divided
Analysis extreme high temperature in summer and cooling electricity relation, analysis winter extreme low temperature and heating electricity relation, analysis such as earthquake, related political affairs
Impact of the accidentalia such as plan to electricity)；
2) economic data can rate of exchange conversion：Year in base period is set first, secondly selects different prices to refer to according to economic attribution
Number is carried out can rate of exchange conversion.
Further, described economic data can the rate of exchange conversion in, value-added of the primary industry selects price index of agricultural commodities
Converted, secondary industry increases is converted from commercial production person's producer price index, value-added of the tertiary industry, Ju Minshou
Enter, consumption of resident is converted from consumption of resident person's price index, fixed investment selects prices for investment in fixed assets
Index is converted.
Further, the building process of the branch trade economy quantization correction model is as follows：
New production input factors are added on the basis of Cobb-Douglas production model --- electric power, its model side
Formula is changed into：
Y=ALαKβEλμ
In formula, Y is the gross output value, and A is comprehensive technical level, and L is labour force's number of input, and K is vested capital, and E is to throw
The electric power for entering, coefficient of elasticity of the α for labour force's output, coefficient of elasticity of the β for capital output, coefficient of elasticity of the λ for electric power output,
μ is random disturbances item；Given alpha+beta+λ=1, and equation both sides are taken the logarithm, above-mentioned equation is changed into：
Ln (Y)=Ln (A)+α * L+ β * K+ (1- alpha-betas) * E+ μ,
In a short time, it is believed that comprehensive technical level A keeps constant, as available from the above equation：
Value-added of the primary industry quantifies amendment estimation equation：
In formula,For value-added of the primary industry,For primary industry quantity of employment,For primary industry investment in fixed assets
Volume,For electricity consumption of resident and primary industry power consumption sum, c1For constant term, α1、β1It is parameter coefficient to be estimated；
The value of secondary industry quantifies amendment estimation equation：
In formula,For the value of secondary industry,For secondary industry quantity of employment,Throw for secondary industry fixed assets
Money volume,For secondary industry power consumption, c2For constant term, α2、β2It is parameter coefficient to be estimated；
Value-added of the tertiary industry quantifies amendment estimation equation：
In formula,For the value of secondary industry,For tertiary industry quantity of employment,Throw for tertiary industry fixed assets
Money volume,For tertiary industry power consumption, c3For constant term, α3、β3It is parameter coefficient to be estimated.
Further, the building process of the GDP total amounts correction model is as follows：
According to national economy working system accounting method, GDP total amounts are numerically equal to primary ,secondary and tertiary industries' value added
Sum, i.e. GDP total amounts correction model form is：
Further, compare the GDP total amounts and point industrial added value before and after correcting, using revised GDP Prediction of Total
Following Analyzing Total Electricity Consumption.
The present invention, under the support of macroeconomy growth theory and statistical theory, completes based on electric power data amendment
Macroeconomic forecasting quantitative model, and with revised GDP Prediction of Total whole society power consumption, reduce economic total volume single
The error of variable prediction power consumption, perfect electric power demand forecasting research.
Description of the drawings
Fig. 1 is the schematic diagram of the present invention.
Specific embodiment
The present invention is modified from electric power visual angle to macroeconomy quantitative prediction, and described makeover process includes data processing
Build with correction model.
1st, in the present invention, data handling procedure is as follows：
11) electric power data is processed：Finding affects the important accidentalia of operation power in the sample phase, and is rejected.Such as
Analysis extreme high temperature in summer and cooling electricity relation, analysis winter extreme low temperature and heating electricity relation, analysis such as earthquake, correlation
Impact of the accidentalia such as policy to electricity.
12) economic data can rate of exchange conversion：Year in base period is set first, secondly selects different prices to refer to according to economic attribution
Number is carried out can rate of exchange conversion.Value-added of the primary industry is converted from price index of agricultural commodities, and work is selected in secondary industry increase
Industry Producer producer price index is converted, and consumption of resident person's valency is selected in value-added of the tertiary industry, the income of residents, consumption of resident
Grid index is converted, and fixed investment is converted from fixed assets devaluation preparation.
2nd, in the present invention, correction model is built as follows：
21) branch trade economy quantifies correction model.
New production input factors are added on the basis of Cobb-Douglas production model --- electric power, its model side
Formula is changed into：
Y=ALαKβEλμ
In formula, Y is the gross output value, and A is comprehensive technical level, and L is labour force's number of input, and K is vested capital, and E is to throw
The electric power for entering, coefficient of elasticity of the α for labour force's output, coefficient of elasticity of the β for capital output, coefficient of elasticity of the λ for electric power output,
μ is random disturbances item；Given alpha+beta+λ=1, and equation both sides are taken the logarithm, above-mentioned equation is changed into：
Ln (Y)=Ln (A)+α * L+ β * K+ (1- alpha-betas) * E+ μ,
In a short time, it is believed that comprehensive technical level A keeps constant, as available from the above equation：
Value-added of the primary industry quantifies amendment estimation equation：
In formula,For value-added of the primary industry,For primary industry quantity of employment,For primary industry investment in fixed assets
Volume,For electricity consumption of resident and primary industry power consumption sum, c1For constant term, α1、β1It is parameter coefficient to be estimated；
The value of secondary industry quantifies amendment estimation equation：
In formula,For the value of secondary industry,For secondary industry quantity of employment,Throw for secondary industry fixed assets
Money volume,For secondary industry power consumption, c2For constant term, α2、β2It is parameter coefficient to be estimated；
Value-added of the tertiary industry quantifies amendment estimation equation：
In formula,For the value of secondary industry,For tertiary industry quantity of employment,Throw for tertiary industry fixed assets
Money volume,For tertiary industry power consumption, c3For constant term, α3、β3It is parameter coefficient to be estimated.
22) GDP total amounts correction model.According to national economy working system accounting method, GDP is numerically equal to first,
The secondary industry and the tertiary industry value added sum, i.e. GDP total amounts correction model form is：
23) compare the GDP and point industrial added value before and after correcting, the electricity consumption of the following whole society is predicted using revised GDP
Amount.
3rd, the present invention in, based on electric power data amendment macroeconomic forecasting quantitative model after, it is pre- with revised GDP total amounts
Whole society's power consumption is surveyed, reduces the error that economic total volume unitary variant predicts power consumption, supplement electric power demand forecasting research.
Claims (6)
1. a kind of macroeconomic forecasting based on electric power data quantifies modification method, it is characterised in that it is from electric power visual angle to grand
See economic quantitative prediction to be modified, described amendment content includes data processing and build macroeconomy quantifying correction model；
Described data processing is：Electric power data is obtained, the part that non-economic factors affect is rejected；Economic data is obtained, is carried out
Can rate of exchange conversion；
Described macroeconomy quantifies correction model includes that branch trade economy quantifies correction model and GDP total amount correction models.
2. macroeconomic forecasting according to claim 1 quantifies modification method, it is characterised in that the tool of the data processing
Body process is as follows：
1) electric power data is processed：Finding affects the important accidentalia of operation power in the sample phase, and is rejected；
2) economic data can rate of exchange conversion：Year in base period is set first, secondly selects different price index to enter according to economic attribution
Row can rate of exchange conversion.
3. macroeconomic forecasting according to claim 2 quantifies modification method, it is characterised in that described economic data can
In rate of exchange conversion, value-added of the primary industry is converted from price index of agricultural commodities, and commercial production is selected in secondary industry increase
Person's producer price index is converted, and consumption of resident person's price index is selected in value-added of the tertiary industry, the income of residents, consumption of resident
Converted, fixed investment is converted from fixed assets devaluation preparation.
4. macroeconomic forecasting according to claim 1 quantifies modification method, it is characterised in that the branch trade economic magnitude
The building process for changing correction model is as follows：
New production input factors are added on the basis of Cobb-Douglas production model --- electric power, its model equation
It is changed into：
Y=ALαKβEλμ
In formula, Y is the gross output value, and A is comprehensive technical level, and L is labour force's number of input, and K is vested capital, and E is input
Electric power, coefficient of elasticity of the α for labour force's output, coefficient of elasticity of the β for capital output, coefficient of elasticity of the λ for electric power output, μ is
Random disturbances item；Given alpha+beta+λ=1, and equation both sides are taken the logarithm, above-mentioned equation is changed into：
Ln (Y)=Ln (A)+α * L+ β * K+ (1- alpha-betas) * E+ μ,
In a short time, it is believed that comprehensive technical level A keeps constant, as available from the above equation：
Value-added of the primary industry quantifies amendment estimation equation：
In formula,For value-added of the primary industry,For primary industry quantity of employment,For primary industry fixed investment,For electricity consumption of resident and primary industry power consumption sum, c1For constant term, α1、β1It is parameter coefficient to be estimated；
The value of secondary industry quantifies amendment estimation equation：
In formula,For the value of secondary industry,For secondary industry quantity of employment,For secondary industry fixed investment,For secondary industry power consumption, c2For constant term, α2、β2It is parameter coefficient to be estimated；
Value-added of the tertiary industry quantifies amendment estimation equation：
In formula,For the value of secondary industry,For tertiary industry quantity of employment,For tertiary industry fixed investment,For tertiary industry power consumption, c3For constant term, α3、β3It is parameter coefficient to be estimated.
5. macroeconomic forecasting according to claim 4 quantifies modification method, it is characterised in that the GDP total amounts amendment
The building process of model is as follows：
According to national economy working system accounting method, GDP total amounts are numerically equal to primary ,secondary and tertiary industries' value added sum,
That is GDP total amounts correction model form is：
6. macroeconomic forecasting according to claim 5 quantifies modification method, it is characterised in that before and after comparing amendment
GDP total amounts and point industrial added value, using revised GDP Prediction of Total future Analyzing Total Electricity Consumption.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107220763A (en) * | 2017-05-24 | 2017-09-29 | 国网安徽省电力公司 | A kind of method for separating temperature electricity and economic electricity in industrial electricity |
| CN107748938A (en) * | 2017-11-06 | 2018-03-02 | 国网福建省电力有限公司 | A kind of electric power demand forecasting method based on Vector Autoression Models |
| WO2018219097A1 (en) * | 2017-06-01 | 2018-12-06 | 王二丹 | Method for carrying out economic aggregate analysis using employment function |
| CN110046759A (en) * | 2019-04-19 | 2019-07-23 | 重庆交通大学 | The appraisal procedure that construction industry total factor productivity is influenced based on the rural migrant worker of Solow's Residual Method |
| CN116523687A (en) * | 2023-06-26 | 2023-08-01 | 国网能源研究院有限公司 | Multi-factor electricity consumption growth driving force decomposition method, device and storage medium |
-
2016
- 2016-11-02 CN CN201610944924.6A patent/CN106600029A/en active Pending
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107220763A (en) * | 2017-05-24 | 2017-09-29 | 国网安徽省电力公司 | A kind of method for separating temperature electricity and economic electricity in industrial electricity |
| WO2018219097A1 (en) * | 2017-06-01 | 2018-12-06 | 王二丹 | Method for carrying out economic aggregate analysis using employment function |
| CN107748938A (en) * | 2017-11-06 | 2018-03-02 | 国网福建省电力有限公司 | A kind of electric power demand forecasting method based on Vector Autoression Models |
| CN110046759A (en) * | 2019-04-19 | 2019-07-23 | 重庆交通大学 | The appraisal procedure that construction industry total factor productivity is influenced based on the rural migrant worker of Solow's Residual Method |
| CN116523687A (en) * | 2023-06-26 | 2023-08-01 | 国网能源研究院有限公司 | Multi-factor electricity consumption growth driving force decomposition method, device and storage medium |
| CN116523687B (en) * | 2023-06-26 | 2023-10-03 | 国网能源研究院有限公司 | Multi-factor electricity consumption growth driving force decomposition method, device and storage medium |
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