Title :
India´s electricity demand estimation using Genetic Algorithm
Author :
Saravanan, S. ; Kannan, S. ; Amosedinakaran, S. ; Thangaraj, C.
Author_Institution :
Kalasalingam Univ., Krishnankoil, India
Abstract :
This study deals with estimation of electricity demand for India using Genetic Algorithm (GA) based on economic indicators. The economic indicators are population, per capita gross domestic product (GDP), import and export. The Genetic Algorithm-Electricity Demand (GA-ED) model is developed based on past data, and different scenarios (low, high growth and trend line) are used to predict electricity demand. Two forms of the GA-ED models are developed to estimate electricity demand. Mean Absolute Percentage Error (MAPE) is used as an evaluation criterion to choose the best-fit GA-ED model and it is used for future electricity demand prediction. The GA-ED results are compared with the prediction of 18th Electricity Power Survey of India. The GD-ED model estimates electricity demand until 2025.
Keywords :
demand side management; economic indicators; genetic algorithms; GA-ED model; GDP; India; MAPE; economic indicators; electricity demand estimation; genetic algorithm-electricity demand model; gross domestic product; mean absolute percentage error; Economic indicators; Electricity; Estimation; Genetic algorithms; Market research; Sociology; Statistics; Electricity demand; India; future projection; genetic algorithm;
Conference_Titel :
Circuit, Power and Computing Technologies (ICCPCT), 2014 International Conference on
Print_ISBN :
978-1-4799-2395-3
DOI :
10.1109/ICCPCT.2014.7054814