Preprint Article Version 1 This version not peer reviewed

Hybrid GA-PSO Optimization of Artificial Neural Network for Forecasting Electricity Demand

Version 1 : Received: 18 January 2018 / Approved: 23 January 2018 / Online: 23 January 2018 (15:30:10 CET)

How to cite: Anand, A.; Suganthi, L. Hybrid GA-PSO Optimization of Artificial Neural Network for Forecasting Electricity Demand. Preprints 2018, 2018010216 (doi: 10.20944/preprints201801.0216.v1). Anand, A.; Suganthi, L. Hybrid GA-PSO Optimization of Artificial Neural Network for Forecasting Electricity Demand. Preprints 2018, 2018010216 (doi: 10.20944/preprints201801.0216.v1).

Abstract

In the present study, a hybrid optimizing algorithm has been proposed using Genetic Algorithm (GA)and Particle Swarm Optimization (PSO) for Artificial Neural Network (ANN) to improve the estimation of electricity demand of the state of Tamil Nadu in India. The GA-PSO model optimizes the coefficients of factors of gross state domestic product (GSDP) , electricity consumption per capita, income growth rate and consumer price index (CPI) that affect the electricity demand. Based on historical data of 25 years from 1991 till 2015 , the simulation results of GA-PSO models are having greater accuracy and reliability than single optimization methods based on either PSO or GA. The forecasting results of ANN-GA-PSO are better than models based on single optimization such as ANN-BP, ANN-GA, ANN-PSO models. Further the paper also forecasts the electricity demand of Tamil Nadu based on two scenarios. First scenario is the "as-it-is" scenario , the second scenario is based on milestones set for achieving goals of "Vision 2023" document for the state. The present research also explores the causality between the economic growth and electricity demand in case of Tamil Nadu. The research indicates that a direct causality exists between GSDP and the electricity demand of the state.

Subject Areas

Electricity Demand; ANN; PSO; GA; Hybrid Optimization; Forecasting

Readers' Comments and Ratings (0)

Leave a public comment
Send a private comment to the author(s)
Rate this article
Views 0
Downloads 0
Comments 0
Metrics 0
Leave a public comment

×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.