Forecasting electricity demand : a time series approach

An unfortunate consequence of the widespread fascination for econometrics in the context of the Indian power sector analysis has been the fatality of a consistent, logical approach to power demand analysis, in the particular confines of its objective environment. Correlating aggregate electricity consumption and gross domestic product in the industrialized, advanced, countries where electricity service contributes significantly to everyday life, social and work life, has become a standard tool of simple analysis for some obviously general conclusions and is beyond any methodological error as such there. However, the story is different and turns vicious with attempts at mapping this methodology on to an alien range in an underdeveloped power system where the contribution of the service of electricity is insignificant. This is so even in the industrial sector in India. Adoption of this methodology here then amounts to correlating the national/state domestic product or industrial product exclusively with an insignificant input, in violation of the ethics of a consistent and logical analytical exercise, and results in gross specification error.

Forecasting of electricity consumption has become a significant element of utmost necessity of the planning exercise in the power sector, especially in the backdrop of the continuing energy crisis. The present work critically evaluates the electricity demand forecasting methodology available in general and proposes a methodology in the classical time series framework of multi-variate autoregressive-moving average (MARMA) model.