Distributed Energy Resources, Capacitor Banks and Fast Charging Stations Allocation using a Multi-Objective Optimization Approach

Electric Vehicles (EVs) have experienced widespread adoption as a sustainable mode of transportation, leading to a significant increase in Electric Vehicle Charging Stations (EVCSs) within the network. However, the installation of EVCSs can have a negative impact on distribution systems due to the increasing demand for EV charging. Therefore, this paper introduces a novel multi-objective optimization approach for the efficient allocation and sizing of Fast Charging Stations (FCSs), Distributed Energy Resources (DERs), and Capacitor Banks (CBs). The primary objectives are to simultaneously minimize investment and operational costs, voltage deviation, and power losses in the network. Furthermore, the methodology accounts for daily variations and uncertainties in DERs generation, load, and EVs traffic in order to ensure the optimization of the objective functions under varying network conditions. The multi-objective optimization problem is solved using Multi-objective Cuckoo Search and Fuzzy Decision-Making method. The effectiveness of the proposed methodology was demonstrated on the 33-bus test system. From the results, it was possible to reduce the voltage deviation and power losses by 14.24% and 19.02%, respectively, when compared to the original system.