Natural hazards in electricity grids: from landscape dynamics to optimal mitigation and adaptation approaches
Ayat-Allah Bouramdane
Abstract
This article discusses the increasing significance of microgrids in fortifying electricity grid resilience amidst evolving global energy trends. The study employs the Multi-Criteria Decision-Making Analytic Hierarchy Process (MCDM-AHP) to assess strategies for mitigating and adapting to natural hazards, utilizing a purposeful and structured judgment process with pairwise comparisons and eigenvalue calculations to establish overall preference scores. The chosen methodology, MCDM-AHP, is highlighted for its effectiveness in handling complex, multidimensional decision-making challenges with interrelated criteria and dependencies, guided by subjective expert judgment. The analysis of relative weights underscores the utmost importance of effectiveness, resilience enhancement, and risk reduction while also highlighting the significance of technological maturity, scalability, flexibility, long-term sustainability, integration with other strategies, community engagement, resource availability, cost-effectiveness, ease of implementation, education and training, environmental impact, and regulatory and policy compliance in evaluating strategies for natural hazard mitigation and adaptation. "Distributed Generation" emerges as the top-performing option, followed closely by "Demand Response" and "Artificial Intelligence", while "Scenario Planning", "Hardening Infrastructure", "Collaboration", and "Regular Maintenance" also demonstrate varying levels of effectiveness across evaluated criteria in the mitigation and adaptation of natural hazards. This research investigates the varied responses of electricity grid landscapes to natural hazards, utilizing MCDM-AHP to assess resilience strategies, providing insights into the strengths and weaknesses of different grid types, and offering a comprehensive framework for policymakers and practitioners to enhance energy system resilience and reliability.