Enhancing green energy integration through strategic planning of renewable generators, EV parking lots, and stationary battery storage systems

Renewable energy sources (RESs) and electric vehicles (EVs) are central to global efforts to reduce carbon emissions and promote sustainable energy transitions. The increasing integration of renewable resources, such as solar and wind power, along with the rising adoption of EVs, underscores the need for robust strategies to optimize their incorporation into power systems. This study proposes a strategic, long-term planning optimization framework for the effective integration of green energy technologies. The framework emphasizes the optimal deployment of wind and photovoltaic (PV) distributed generators (DGs) for RESs and the establishment of plug-in electric vehicle (PEV) charging infrastructure within distribution systems (DS). Furthermore, stationary battery energy storage systems (SBESSs) are integrated to enhance the penetration of RESs and EVs. The proposed framework determines optimal locations, sizes, and operational strategies for RESs, PEV infrastructure, and SBESSs while addressing technical, operational, and economic constraints. It accounts for uncertainties such as renewable generation variability, energy prices, electricity demand, and EV energy and time dynamics. Monte Carlo simulations (MCS) and the backward reduction method (BRM) are employed to analyse various scenarios and ensure computational efficiency. Additionally, a coordinated charging and discharging control mechanism for SBESSs and EVs is developed to manage active and reactive power, thereby improving overall system performance. The framework simultaneously minimizes three objectives: long-term planning and operation cost, total power loss, and voltage deviation. Advanced optimization algorithms, including the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO), are utilized to achieve these goals. The methodology is validated on a 69-bus system under four distinct configurations. Results indicate that the integration of wind, PV, PEV infrastructure, and SBESSs significantly enhances green energy penetration and system efficiency compared to other configurations. For instance, the integration of RESs and PEVs increases RES penetration from 3.35 MVA to 3.80 MVA with an optimal EV fleet size of 249 vehicles, achieving a 2.14 % reduction in total cost, albeit with a 6.33 % increase in power loss and a 2.03 % rise in voltage deviation compared to the RES-only scenario. The addition of SBESSs further improves RES penetration to 3.90 MVA, reduces costs by an additional 0.88 %, and mitigates power loss and voltage deviation by 13.36 % and 9.80 %, respectively, though it reduces the EV fleet size from 249 to 168 vehicles. These findings highlight the effectiveness of the proposed framework in optimizing green energy integration and advancing sustainable energy systems.