Electric vehicles (EVs) are transforming transportation, requiring planned charging networks to handle rising demand, manage power systems, reduce congestion, and integrate renewables. This work develops a stochastic optimization framework for EV charging stations with transactive control to cut carbon emissions and promote EV adoption. Consequently, deploying EVCS will become a crucial strategy for addressing the integration of renewable energy. An innovative approach to supplying electric power stored in EV fleets involves using transportation networks as supplementary infrastructure .The article explores how transportation networks affect EVCS and DR scheduling under uncertain PV output, highlighting the benefits of DR integration for improved efficiency and grid reliability. A mixed-integer linear programming (MILP) model is proposed to enhance the solution quality of the DC power flow method, thereby reducing computational complexity. A detailed evaluation of economic and environmental factors is included, showing a 1.288% overall system cost reduction with EV fleets and DR in scheduling costs, and a 2.431% decrease in EV fleet and solar PV power costs. This research aims to offer a sustainable, cost-effective, and scalable solution for EV charging infrastructure to support future electric mobility, with the dispatching problem verified on a modified IEEE 30-bus system.
Bharti et al. (Mon,) studied this question.