Optimal Resilience Enhancement Strategy for Power Systems Using Multi-Objective Evolutionary Algorithm

The increasing frequency and severity of natural extreme events have significantly impacted the resilience of electric power delivery, highlighting the critical need for investing in more resilient power systems. One effective strategy for enhancing power system resilience is the reinforcement of transmission lines that connect critical nodes within the grid. This study proposes a comprehensive framework aimed at maximizing system resilience by strategically selecting the optimal transmission lines for reinforcement. The approach integrates both technical and economic considerations, seeking to minimize the investment costs associated with line reinforcement while ensuring the stability and reliability of the power system. The optimization problem is formulated as a multi-objective optimization problem, which is solved using the Non-dominated Sorting Genetic Algorithm (NSGA-II) to balance the conflicting resilience and cost objectives. Additionally, the framework accounts for constraints such as the available investment budget, making it a practical tool for decision-makers in the planning and development of resilient power infrastructure.