RISK-BASED DECISION-MAKING STRATEGIES FOR ENHANCING GRID RESILIENCE IN SMART POWER SYSTEMS

Abstract

Pre-catastrophe safety techniques are essential for enhancing the resilience of electric strength structures in opposition to natural disasters, particularly given the dependency of other infrastructure systems on strength. This paper develops risk-impartial and threat management models to optimize pre-disaster safety techniques, thinking about budget constraints, disaster uncertainty, and device interdependencies. The hazard-impartial version maximizes the anticipated fee of resilience (EVR), while the threat control version additionally consists of threat minimization metrics. A case observe on energy infrastructure within the Greater Toronto Area validates the fashions, revealing that: (i) growing budgets improves EVR, however beyond a threshold, incremental profits lessen; (ii) reducing disadvantage chance can lead to better EVR, with a non-linear trade-off among the two goals; and (iii) price range choices have to balance catastrophe depth and protection costs. Furthermore, the paper examines historic transmission outage statistics from the North American Electric Reliability Corporation (NERC) and suggests that figuring out clusters of nearby outages may want to improve operator reaction instances, enhancing grid resilience beneath N-1 security. The paper also surveys existing methodologies for enhancing electricity grid resilience in opposition to extreme climate occasions, highlighting gaps in present day answers and offering destiny research guidelines. Finally, a novel technique integrating asset management with grid resilience, together with the Value of Lost Load (VoLL), is proposed, demonstrating its ability thru a North American application case take a look at for knowledgeable upkeep strategies.