Multi-objective Stochastic Planning of Electric Vehicle Charging Stations in Unbalanced Distribution Networks Supported by Smart Photovoltaic Inverters

Due to the environmental concerns, getting deteriorated ongoing, it is becoming essential to encourage people to use sustainable energies. One of the most effective alternatives to mitigate pollution is to promote green mobility via electric vehicles. However, the lack of electric charging stations may decrease individuals’ satisfaction to use electric vehicles in daily life. To bridge the gaps, this paper aims to simultaneously allocate electric vehicle charging stations and smart photovoltaic inverters in distribution networks to optimize three important objective functions, including power loss, voltage deviation, and voltage unbalance factor. To solve such a multi-objective optimization problem, a novel hybrid fuzzy Pareto dominance concept with differential evolution algorithm is proposed. A scenario-based framework is also used to capture the uncertainties of the model comprising loads, PVs’ generation and the demand of electric vehicle charging stations. The effectiveness of the stochastic multi-objective approach is then examined and verified on an unbalanced 37-bus network under different case studies. Attained results illustrate that if smart photovoltaic inverters integrate into the network with charging stations, the network performance is significantly improved, such as keeping voltage unbalance factor under standard value accounting for two percent.