DIndustry Electricity Data Analysis Method Considering Seasonal Factors

Abstract

The electricity consumption of the industry is affected by economy, policy, holidays and temperature, showing obvious trend and seasonality. At the same time, accidental events also have an impact on electricity consumption, manifested as disturbances in the time series of electricity consumption. In studies such as the correlation between electricity consumption and other economic factors, the demand electricity consumption sequence must be a stationary time series. According to the problem of seasonal fluctuation of the electricity consumption time series, the electricity consumption curve is seasonally adjusted based on the high-order sliding average method. The Henderson weighted moving average algorithm is used to calculate the trend cycle component. After three iterations, the seasonal influence factors are removed from the electricity consumption time series to achieve seasonal adjustment. The results of the example show that the seasonally adjusted electricity consumption curve is smoother and the stability of the time series is improved, which is the basis of applied research such as subsequent power forecasting.