This paper is published in Volume-6, Issue-6, 2020
Area
Electrical Engineering
Author
Rishav, Puneet Jain, Chakshu Goel
Org/Univ
Adesh Institute of Engineering and Technology, Faridkot, Punjab, India
Pub. Date
27 November, 2020
Paper ID
V6I6-1170
Publisher
Keywords
Load Forecasting, Artificial Neural Network, Firefly Algorithm

Citationsacebook

IEEE
Rishav, Puneet Jain, Chakshu Goel. Optimal load forecasting by hybrid the artificial neural network and firefly algorithm, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Rishav, Puneet Jain, Chakshu Goel (2020). Optimal load forecasting by hybrid the artificial neural network and firefly algorithm. International Journal of Advance Research, Ideas and Innovations in Technology, 6(6) www.IJARIIT.com.

MLA
Rishav, Puneet Jain, Chakshu Goel. "Optimal load forecasting by hybrid the artificial neural network and firefly algorithm." International Journal of Advance Research, Ideas and Innovations in Technology 6.6 (2020). www.IJARIIT.com.

Abstract

In the smart grid, load forecasting algorithms used for estimating the electricity demand based on historical data. It helps in generating accurate electricity and overcoming the two challenges such as a shortage of electricity and excess generation cost. In the literature, various traditional load forecasting algorithms proposed to predict the electricity demand but never the accurate results. Therefore, advanced algorithms come into the picture such as artificial intelligence algorithms. In this paper, we have hybrid the Artificial Neural Network (ANN) and firefly algorithm for load prediction. Initially, the ANN algorithm is trained based on the historical data then applied to it. After that, the firefly algorithm is used for searching for the optimal learning rate for ANN. The experimental results are performed in the MATLAB 2015a. We have measured various performance analysis parameters and compared with the existing results. From the study, we found that the proposed algorithm gives better accuracy as compared to the existing algorithms