A Cost-Effective Corona-Virus Search Optimization Based Approach to Joint Expansion Planning of Distribution Networks with Heavy-Duty Electric Truck Dedicated Urban Charging Stations

The increasing demand for operational efficiency and redundancy in electric distribution networks necessitates continuous advancements in power distribution network expansion planning methodologies. Traditional approaches are no longer sufficient due to the integration of distributed generation resources, capacitor banks, and the proliferation of heavy-duty electric trucks. This paper presents a novel approach that integrates dedicated heavy-duty electric truck urban charging stations into modern electric distribution networks. The proposed framework employs joint expansion planning for both electric distribution networks and dedicated heavy-duty electric truck urban charging stations, encompassing constructed elements such as substation construction, circuit reinforcement, distributed generation allocation, and capacitor bank installation. To address computational complexities, the study leverages a novel metaheuristic algorithm called corona-virus search optimization, inspired by the dynamics of the COVID-19 virus. The model’s efficiency and scalability are demonstrated through evaluations using an 18 -bus and a 54 -bus system. The analysis reveals that depot charging of HDETs presents a more challenging scenario with higher costs. However, integrating dedicated heavy-duty electric truck urban charging stations in Scenario II leads to significant cost reductions $(4.34 \%$ and $7.56 \%$ for two systems). The model’s adaptability make it a valuable solution for integrating modern multi-energy electric distribution networks with dedicated charging urban infrastructure.