Minimization of Cost of Energy with Renewable Energy Sources by using Fire-Fly Algorithm

Abstract

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 of renewable energy sources is due to free of cost and more available in nature. This system will meet load demand using renewable energy sources. The Firefly Algorithm (FFA) is used in this research to minimize 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 the minimization of cost with renewable energy sources.

Keywords

• solar energy
• wind energy
• battery storage system and fire-fly algorithm (ffa)