Residential electricity consumption prediction method based on time series model

Abstract

The present invention relates to the data analysis technology field, especially to a residential electricity consumption prediction method based on a time series model. The method comprises the following steps: performing analysis modeling through historical data, fully employing electricity consumption data over the years, considering seasonal fluctuation and temperature influence in the condition of long-term growth trend, and predicting electricity consumption through the time series model. The residential electricity consumption prediction method based on the time series model assists a program construction department and a finance department in performing power network program construction and financial budget management to perform prediction of future electricity consumption. The time series model is employed to perform residential electricity consumption prediction according to data such as resident user growth trend condition and the resident electricity consumption over the years and on a quarterly and year basis.

Description

technical field [0001] The present invention relates to the technical field of data analysis, and more specifically, to a method for predicting residential electricity consumption based on a time series model. Background technique [0002] Traditional power forecasting mainly uses the current user scale, current power consumption, and current economic index data such as GDP to estimate. For the forecast target value, there is no rigorous relationship between the target value and the conditional value. More is Subjective estimation is based on past experience, and the statistical sources of economic indicators such as GDP also include electricity consumption, so it is difficult to meet the accuracy requirements of forecasting using this as the estimation condition. Contents of the invention [0003] In order to overcome at least one of the above-mentioned defects in the prior art, the present invention provides a method for predicting residential electricity consumption bas...

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Problems solved by technology

[0002] Traditional power forecasting mainly uses the current user scale, current power consumption, and current economic index data such as GDP to estimate. For the forecast target value, there is no rigorous relationship between the target value and the conditional value. More is Subjective estimation is based on past experience, and the statistical sources of economic indicators such as GDP also include electricity consumption, so it is difficult to meet the accuracy requirements of forecasting using this as the estimation condition

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