Raja Tahir Iqbal, Sheeraz Iqbal, Ausnain Naveed, Md Shafiullah, Muhammad Aurangzeb, Salah S. Alharbi, Saleh S. Alharbi, Saleh S. Alharbi, Saleh S. Alharbi, Muhammad Ali
The growing integration of electric vehicles (EVs) and renewable energy sources is introducing new operational challenges in modern distribution systems. To address these issues, a robust multi objective optimization (MOO) framework for coordinated EV charging and vehicle to grid (V2G) scheduling is proposed. The framework simultaneously addresses three major objectives: minimizing EV charging cost, reducing peak load demand, and maximizing renewable energy utilization. To solve this complex optimization problem, the study employs the Ring Seal Search (RSS) algorithm, a novel bio-inspired metaheuristic approach with strong exploration and exploitation capabilities. The proposed framework incorporates a Pareto-based optimization strategy to produce a set of non-dominated solutions, enabling system operators and decision-makers to select suitable operating strategies according to real-time grid conditions, market signals, and policy priorities. Unlike many existing approaches that rely on simplified assumptions, the proposed model explicitly considers practical operational aspects, including EV mobility patterns, stochastic renewable energy generation, dynamic electricity pricing, and distribution network constraints. This enhances the realism, flexibility, and applicability of the framework under uncertain operating conditions. The proposed RSS-based method is evaluated on the IEEE 33-bus system and benchmarked against GA and PSO. The MATLAB Simulink results validate that the RSS algorithm achieves superior performance in terms of solution quality, convergence characteristics, cost reduction, peak load minimization, and renewable energy integration. Additional statistical analysis based on multiple independent runs confirms the consistency, robustness, and reliability of the proposed approach. In addition to improving economic and technical performance, the study highlights the broader role of V2G framework in improve grid flexibility, ancillary services, and system resilience. The results demonstrate that EVs can function not only as transportation loads but also as active distributed energy resources (DERs) capable of supporting future smart grid operation. Overall, the proposed framework provides a scalable, adaptive, and practically applicable solution for sustainable energy management in renewable-rich and highly electrified distribution systems.