Long term energy demand modeling and forecasting for tamilnadu using historical data and socio economic variables

Abstract

The forecasting of Future Electrical Energy Demand FEED is extremely important for the deregulated power industry throughout the world A diverse mathematical models are available in the literature for the future prediction of electrical energy Many researchers are also involved in developing the novel methods to estimate the closer energy demand values In this research work the author attempted to apply newer models while minimizing the forecasting errors Hence it is very important to develop suitable energy forecasting models for any country A fast developing state of Tamil Nadu in India is focused here to predict its future electrical energy demand by considering the past historical electrical energy consumption data and the socioeconomic indicators of the state such as Annual Peak Demand AP Population PoP Gross State Domestic Product GSDP and Per Capita Income PCI Population and GSDP are the most influencing factors which are given importance by most of the countries in their future energy demand prediction and the APD and PCI are the new factors which are also taken into consideration in the forecasting of the FEED for Tamil Nadu The forecasting is done for the influencing factors in three stages In the first stage the future values of APD PoP GSDP and PCI from the years 2017 to 2030 were projected based on minimum maximum and average values obtained by two methods i e difference between two consecutive years and difference between current year to first year data from the past data set from 1983 to 2016 Then a MLR model in its three forms such as linear interaction and quadratic equations have been developed and their coefficients were optimized using Genetic Algorithm GA and Simulated Annealing SA with the objective of minimizing the MAPE newline