Next Article in Journal
Economically Efficient Design of Market for System Services under the Web-of-Cells Architecture
Previous Article in Journal
A Load-Shedding Model Based on Sensitivity Analysis in on-Line Power System Operation Risk Assessment
Open AccessArticle

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

Department of Management Studies, College of Engineering, Guindy, Anna University, Chennai, Tamil Nadu 600025, India
*
Author to whom correspondence should be addressed.
Energies 2018, 11(4), 728; https://doi.org/10.3390/en11040728
Received: 18 January 2018 / Revised: 4 February 2018 / Accepted: 15 March 2018 / Published: 23 March 2018
In the present study Artificial Neural Network (ANN) has been optimized using a hybrid algorithm of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The hybrid GA-PSO algorithm has been used to improve the estimation of electricity demand of the state of Tamil Nadu in India. The ANN-GA-PSO model uses gross domestic product (GSDP); electricity consumption per capita; income growth rate and consumer price index (CPI) as predictors that affect the electricity demand. Using the historical demand data of 25 years from 1991 till 2015 it is found that ANN-GA-PSO models have higher accuracy and performance reliability than single optimization models such as ANN-PSO or ANN-GA. In addition, the paper also forecasts the electricity demand of the state based on “as-it-is” scenario and the scenario based on milestones set by the “Vision-2023” document of the state. View Full-Text
Keywords: electricity demand; ANN; PSO; GA; hybrid optimization; forecasting electricity demand; ANN; PSO; GA; hybrid optimization; forecasting
Show Figures

Figure 1

MDPI and ACS Style

Anand, A.; Suganthi, L. Hybrid GA-PSO Optimization of Artificial Neural Network for Forecasting Electricity Demand. Energies 2018, 11, 728.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop