Resilience-oriented optimal integration of photovoltaic, fast-charging stations, and energy storage systems in radial distribution systems

This study proposes a bilevel, resilience-oriented optimization framework for the coordinated allocation of photovoltaic (PV) and fast-charging stations (FCS) and battery energy storage with DSTATCOM (BES–DSTATCOM) in radial distribution networks. Unlike existing approaches, the proposed method captures both the grid-connected performance and islanding resilience within a unified framework. The problem is formulated as a single-objective optimization to minimize the real power loss, while the voltage profile and greenhouse gas (GHG) emissions are evaluated as performance indices. The complexity of the single-objective, multi-constraint, and multivariable optimization problem was solved using the Crayfish Optimization Algorithm (COA), which was selected for its balanced exploration–exploitation capability and fast convergence characteristics compared with conventional algorithms. The results on the IEEE 33-bus radial distribution network reveal that the uncoordinated integration of FCSs significantly deteriorates the system performance, increasing the real power losses by 48, 163, and 183% and GHG emissions by 28, 53, and 67% for one, two, and three FCSs, respectively. However, coordinated PV integration effectively mitigates these impacts, achieving up to ∼93% loss reduction, improving the minimum voltage from 0.913 p.u. to 0.992 p.u., and reducing GHG emissions by up to ∼88%. Furthermore, optimal PV penetration levels (up to 86.6%) are critical for emission reduction. Under islanding conditions, the BES–DSTATCOM ensures energy balance and can effectively neutralize grid-based emissions. Comparative analysis confirmed that COA provided robust and consistent convergence compared to HPO and AOA.