Multi-Criteria Optimization of Vehicle-to-Grid Service to Minimize Battery Degradation and Electricity Costs

Abstract

Increased use of renewable energy sources in energy sector as well as improvements and electrification in transportation sector significantly contribute to reduction of green-house gasses emissions and mitigation of problems with fossil fuel dependency. Optimal integration of electric vehicles (EVs) into the grids and their charging/discharging schedules have to be realized in accordance with electricity demand, day-ahead electricity market prices and intermittency of photovoltaic and wind generators electricity production. A microgrid that includes non-deferrable loads, renewable energy sources, EV fleet and its charging station is analyzed in this paper. Its Vehicle-to-Grid (V2G) service is optimized with the aim of minimizing the operational costs and obtaining peak load shaving and valley filling of the load curve, which is especially effective in the case of EVs fleet with occupational time intervals known in advance. Optimized schedule of EVs charging and discharging is obtained as a result of the procedure that uses multi-criteria optimization function. These criteria include minimization of microgrid electricity costs as the local aggregator’s benefit, maximization of the flattening of total microgrid demand curve as main grid operator’s benefit, and minimization of battery degradation (due to a number of charging/discharging cycles) as EVs owner’s benefit which is the novelty of this paper. Experimental analysis is performed on several scenarios and program Lingo is used to solve the optimization problem.

Solar Based Wireless EV Charging

“…There was no electricity at the residence, therefore it was impossible to charge the car there. Homes needed to be electrified in order to increase the public's access to electric vehicles [2]. This would result in more people buying and utilizing electric vehicles, which is the intended outcome.…”