Shaik Karimulla1 and K. Ravi This email address is being protected from spambots. You need JavaScript enabled to view it.1

1School of Electrical Engineering- SELECT, Vellore Institute of Technology, VIT-Vellore-632014, Tamil Nadu, India


Received: June 21, 2021
Accepted: July 25, 2021
Publication Date: September 30, 2021

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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Renewable energy sources are playing a more active essential part in electrical energy systems in the present and future as a source of energy and an expansion of grid supply. Solar and wind energy are the two sources with the greatest potential for global availability. Wind and solar energy have been investigated with the assistance of a battery energy storage device. The consideration renewable energy sources are due to the free of cost and more available in nature. This system will meet load demand using renewable energy sources. The Fire-fly Algorithm (FFA) is used in this research to minimise energy costs while meeting load demand. The sufficiency of FFA is linked with other metaheuristic methods in connection to performing estimation files, which remain to reduce the cost of energy and to increase the potential power supply. This method considers three different load profiles per year as autumn, winter, and summer seasons, with hourly load-based data used to demonstrate the differences between the three seasons. The results are carried out by using the HOMER (Hybrid Optimization of Multiple Energy Resources) software and MATLAB software. The results show the FFA has better performance than GA, PSO, and IPSO algorithm methods and it shows the comparison for minimization of the cost of energy. Hence, the proposed method shows it is best for minimization of cost with renewable energy sources.

Keywords: Solar energy, Wind energy, Battery storage system and Fire-Fly Algorithm (FFA)


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