Distributed Consensus-Based Optimal Power Sharing Between Grid and EV Charging Stations Using Derivative-Free Charging Scheduling

Abstract

The trending penetration of electric vehicles (EVs) and the emergence of new charging stations to the existing power grid pose challenges to power supply security, reliability, and economics. The optimal coordination strategy between the EV and power grid is mandatory for the secure and reliable operation of the EV-connected entire system and to fulfil the EV charging needs at a lower cost. Therefore, the current study looks at improving energy economics through optimal coordination for smart power allocation and EV charging station scheduling. This paper uses a distributed consensus-based optimization algorithm (DCBOA) to identify the best power-sharing arrangement amongst three charging stations for motorbikes, small EVs, and large EVs. Moreover, the EVs are also scheduled optimally at each charging station using a derivative-free optimization algorithm (DFOA). The results show that optimal power sharing has resulted in a considerable decrease in the amount of electricity purchased from the power grid and offers EV charging at a lower cost. Furthermore, the smart scheduling of the EVs reduces the overall load burden on the grid network. The findings emphasize the robustness and effectiveness of the proposed optimal power-sharing approach in raising the energy economics of EV charging stations.

Keywords

• Electric vehicle
• charging station
• energy scheduling
• distributed consensus algorithm
• power sharing