Multi-objective optimization of hybrid energy management system for expressway chargers

Abstract

Fuel combustion is considered a vast energy source for transportation, resulting in the emission of pollutants into the environment. In contrast, electric vehicles (EVs) do not emit direct emissions and protect the environment from hazardous emissions. The rapid and enormous expansion of electric vehicles in China made electric chargers a crucial component of the transportation management system. The present study suggests a hybrid energy management approach to boost the amount of renewable energy going into the electric charger. Wind turbines and solar power generating modules generate energy for electric charging. Excessive energy is stored in energy storage modules and sent to power grid modules, making reverse supply more flexible. Three optimization algorithms, including PSO, GA, and BBO, were employed to find the highest energy cost and power grid dependence with different combinations. The system is considered on-grid and can purchase or sell electricity to maintain energy balance for electric charging devices. The optimization results show that the highest energy cost in a reasonable scheme can reach 0.034546 $/kWh with a share of maximum renewable energy of 96.50 %. Finally, the balance between energy cost and dependency on the power grid can be reached based on the present analysis findings, as the energy cost of the final equilibrium scheme is 0.057475 $/kWh, with a share of 90.82 % in renewable energy. The proposed study can effectively balance energy supply and demand and further support the global agenda of UN-2030 for sustainable development, especially SDG-7.