Optimizing energy management in electric vehicle charging using firefly algorithm

Abstract

The transition to electric vehicles (EVs) poses significant challenges in the management of electric vehicle charging stations (EVCS), especially regarding the integration of renewable energy to ensure efficiency and sustainability. This study aims to optimize the energy management system in EVCS that takes into account technological aspects. The algorithm being proposed is specifically created for a 100 kW EVCS and utilizes the firefly algorithm to maximize renewable energy utilization and minimize charging costs. The research methodology includes the development of an optimization framework that combines solar power generation with the Firefly-based optimization algorithm, which considers factors such as power demand, battery capacity, and tariff fluctuations. Simulations show that the algorithm is able to increase solar energy utilization by up to 80%, while reducing charging costs during peak hours. The results also emphasize the importance of real-time energy management to address power demand fluctuations and reduce adverse impacts on the electricity grid. This study concludes that the firefly algorithm is effective in supporting energy management in renewable energy-based EVCS, providing essential knowledge for the development of sustainable charging system within the future.