Evaluative Methodologies for Resilience and Reliability in Multi-Terminal HVDC Transmission Systems

Modern energy systems, typified by intricate configurations and dependencies, necessitate advanced analytical methodologies for resilience and reliability assessment. This research delves into two distinct case studies that scrutinize these parameters within varied contexts. The first study methodically ranks the critical components of a transmission system, employing Dynamic Fault Tree (DFT) analysis. This approach elucidates components' significance based on multiple importance measures, thus facilitating pre-emptive maintenance and risk management strategies. The second study focuses on the resilience of multiterminal HVDC-VSC transmission frameworks, especially tailored for expansive offshore wind farms. Utilizing Markov Automata, the study simulates various operational states, from full functionality to detachment scenarios, rendering insights into system behaviors over infinite durations and specific time-bound intervals. These probabilistic and mean time evaluations are pivotal for strategic planning and resource allocation, especially in the face of disruptions. Collectively, the two case studies underscore the importance and versatility of employing advanced analytical tools to address the multifaceted challenges of modern transmission systems, fostering improved reliability and resilience in our energy infrastructure.

Keywords: Reliability, Dynamic fault tree, Markov automata.