Dimensionality-reduced multi-objective framework for resilient power systems with electric vehicles and hydrogen-based energy storage

Modern power systems are becoming increasingly complex and vulnerable, raising concerns about their ability to withstand disruptive events. As a result, resilience has become a key consideration in system planning and operation. This paper proposes a resilience-oriented framework that coordinates distributed energy resources (DERs) with hydrogen-based energy storage (HESS). The framework also integrates planning for transmission lines, electric vehicles (EVs), and flexible AC transmission systems (FACTS) to enhance overall system performance. The problem is formulated as a multi-objective optimization model. One objective minimizes the cost of the resilience strategy, while the other maximizes the contribution of DERs to system resilience. The formulation includes a large number of decision variables, making it computationally challenging. To address this, two strategies are applied to reduce dimensionality: (i) a power dispatch and load-shedding reduction strategy, and (ii) a transmission line and FACTS-based strategy. To solve the problem, multi-objective versions of five recent metaheuristic algorithms are employed. The effectiveness of the proposed reduced-scale model in improving these algorithms is evaluated on the IEEE 9-bus, IEEE 30-bus, and 53-bus systems. Simulation results showed that the proposed strategies significantly improved both robustness and solution quality. For the IEEE 9-bus system, robustness increased by 20–30% and solution quality by 6–21.75%. In the IEEE 30-bus system, robustness improved by up to 25%, with solution quality gains of 13.43–38.85%. For the 53-bus network, robustness increased by 10–25%, and solution quality improved by 3–12.45%. The results demonstrated the advantages of HESS over conventional battery storage in enhancing system resilience. For the IEEE 9-bus system, HESS achieved a reduction in planning cost of 29.7–55.2%, while for the IEEE 30-bus system, the reduction ranged from 36.3 to 57.66%.