Publication: Hybrid metaheuristic of artificial neural network - Bat algorithm in forecasting electricity production and water consumption at Sultan Azlan shah Hydropower plant
Date
2017
Authors
Hussin S.N.H.S.
Malek M.A.
Jaddi N.S.
Hamid Z.A.
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
Hydropower is one of the technologies in renewable energy that is commercially viable on a large scale. A hybrid of metaheuristic Artificial Neural Network (ANN) technique with Bat Algorithm (BA), a bio-inspired algorithm is proposed to forecast future electricity production and water consumption at Sultan Azlan Shah Hydropower Dam located upstream of Perak river. In this study, both the ANN and Hybrid ANN-Bat Algorithm coding was designed and written explicitly to tailor the time series input data and assumptions used in this study. Comparison on results obtained from ANN and the proposed hybrid ANN - BA was conducted. Simulations conducted in this study exhibited that the proposed hybrid algorithm is much superior then the conventional ANN. � 2016 IEEE.
Description
Hydroelectric power; Hydroelectric power plants; Neural networks; Bat algorithms; Bio-inspired algorithms; Electricity production; Forecasting electricity; Hybrid Meta-heuristic; Hydropower; Renewable energies; Water consumption; Electric power generation