Power demand forecast method based on vector autoregression model

An autoregressive model and power demand technology, applied in forecasting, instrumentation, data processing applications, etc., can solve the problems of insufficient consideration of economic and power correlation analysis, lack of accuracy of forecasting models, etc., and achieve good empirical results and strong generality The effect of high chemicalization ability and high prediction accuracy

Inactive Publication Date: 2018-03-02
STATE GRID FUJIAN ELECTRIC POWER CO LTD +2
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Problems solved by technology

These methods often use the historical data of electricity consumption to construct corresponding forecasting functions, and seldom describe and quantify other indicators that may affect electricity demand in the

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  • Power demand forecast method based on vector autoregression model
  • Power demand forecast method based on vector autoregression model
  • Power demand forecast method based on vector autoregression model

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Embodiment Construction

[0022] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.

[0023] An electric power demand forecasting method based on a vector autoregressive model of the present invention collects economic data and electric power data of an area to be predicted, and utilizes a vector autoregressive model to forecast electric power demand. The economic data include 3 economic indicators, which are investment in fixed assets, total retail sales of social consumer goods, and total net export trade; the electricity data includes electricity consumption of the whole society.

[0024] The economic data and power data need to be cleaned and logarithmized. After the economic data and electric power data are logarithmized, a stationarity check is required, that is, a dickey-fuller test is used to check whether there is a unit root in each column of sequence data. If there is, the sequence data is differentially process...

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Abstract

The invention relates to a power demand forecast method based on a vector autoregression model. Step one, the economic data and the power demand data of a region (country, province or city) to be forecasted are collected; step two, the data are compiled and cleaned and stored in a database; step three, the time period required to be forecasted and the minimum time interval of the data are definedand logarithmic processing is performed on the corresponding data; step four, stationarity testing is performed on the four columns of processed data (fixed asset investment, total retail sales of consumer goods, total net export trade and the power demand); step five, an equation based on the vector autoregression model is constructed; step six, the lag order of the model is determined by using the AIC Akaike information criterion and the SIC Schwarz criterion; and step seven, the vector autoregression model is corrected and the power demand is forecasted by using the vector autoregression model. The method has the characteristics of high generalization capability and high forecast accuracy.

Description

technical field [0001] The invention relates to a method for predicting electric power demand based on a vector autoregressive model, specifically carrying out electric demand forecasting through the vector autoregressive model in econometrics. Background technique [0002] Traditional With the increasing development of the power system, electricity has become the most important secondary energy in industrial production and residents' lives. As a commodity, electric energy has certain particularities compared with other commodities. Its biggest feature is that it cannot be stored, that is, the production, transportation, distribution and consumption of electric energy are completed at the same time. Therefore, the available power generation capacity in the power system should meet the demand of the load in the system under normal conditions. When the power generation capacity is insufficient, necessary measures should be taken, such as increasing generator sets, reducing lo...

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06
CPCG06Q10/04G06Q10/06315G06Q50/06
Inventor 杜翼胡鹏飞雷勇林红阳李荣敏林章岁洪兰秀刘林项康利沈豫邱柳青易杨
Owner STATE GRID FUJIAN ELECTRIC POWER CO LTD
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