Innovative power grid solutions: strengthening resilience against disruptions

The resilience of power systems against disruptive events, such as hurricanes, is crucial for ensuring stability and reliability. This study introduces the Evolutionary Chaotic Cloning-Squirrel Algorithm (ECCSA), an innovative optimization technique designed to enhance power system resilience through optimized load-shedding strategies. ECCSA integrates chaotic dynamics and clonal selection principles with the Squirrel Search Algorithm to address limitations in traditional optimization methods, such as entrapment in local optima, thereby improving solution accuracy and efficiency. The proposed framework was applied to the IEEE 57-Bus Reliability Test System, analyzing two hurricane scenarios with varying reactive power demands. ECCSA demonstrated its ability to determine optimal load-shedding locations and sizes, significantly reducing power losses and improving resilience indices. For example, at Bus 33, power losses were reduced by 40.17% in Scenario 2, with resilience indices improving notably. The uniqueness of ECCSA lies in its hybrid optimization approach, adaptability to dynamic conditions, and effectiveness in minimizing transmission losses. Socio-economically, it ensures reliable power delivery, supports renewable energy integration, and reduces the environmental impact of power outages. Its scalability and cost-effectiveness present strong commercialization prospects, making ECCSA a robust solution for modernizing power grids and addressing the growing demand for resilient energy systems.