Miscellaneous Energy Profile Management Scheme for Optimal Integration of Electric Vehicles in a Distribution Network Considering Renewable Energy Sources

Abstract

The integration of renewable energy and electric vehicles in smart grids aims to improve the grid network and reduce carbon emissions. In this regard, this study presents a new Energy Management Scheme (EMS) for the optimal charging and discharging of electric vehicles in a photovoltaic-present distribution network based on the availability of solar energy and power from the grid. For effective scheduling, the model splits a distribution network into residential and commercial areas, which are handled separately by two Electric Vehicle (EV) aggregators. A newly developed hybrid algorithm, named Chaotic Whale optimization Algorithm and Gravitational Search Algorithm (CWOAGSA), is integrated into a multiobjective framework to simultaneously minimize power loss, improve voltage stability, and reduce carbon emissions. Simulation results show that the proposed model can inject real power at a 60% EV penetration level without destabilizing the distribution network. The comparison of the CWOAGSA to the WOA, PSO, and GA shows a better minimization of real power loss. The CWOAGSA minimizes the total real power network losses with a 55% margin from the increased power loss due to the uncoordinated scheduling, and a 7% margin to the WOA.