Multi-Objective Optimization of Electric Vehicle Charging Schedule with Time of Use Tariff


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The increased uptake of electric vehicles (EVs) leads to increased demand for electricity, and sometime pressure to power grids. Uncoordinated charging of EVs may result in putting pressure on distribution networks, and often some form of optimisation is required in the charging process. Optimal coordinated charging is a multi-objective optimisation problem in nature, with objective functions such as minimum price charging and minimum disruptions to the grid. In this manuscript, we propose a general multi-objective EV charging/discharging schedule (MOEVCS) framework, where the time of use (TOU) tariff is designed according to the load request at each time stamp. To obtain the optimal scheduling scheme and balance the competing benefits from different stakeholders, such as EV owners, EV charging stations (EVCS), and the grid operator, we design three conflicting objective functions including EV owner cost, EVCS profit, and the network impact. Moreover, we create four application scenarios with different charging request distributions over the investigated periods. We use a constraint multi-objective evolutionary algorithm (MOEA) to solve the problem. Our results demonstrate the effectiveness of MOEVCS in making a balance between three conflicting objectives.

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