Evaluates operational reliability in power systems, suggesting improved accuracy with knowledge-informed approaches.
• Traditional reliability evaluation approaches, e.g., Monte-Carlo simulation (MCS) and analytical approaches, rely on scenario calculations and thus fail to meet the requirement of rapidity. • Compared with traditional reliability evaluation approaches, the data-driven model can accelerate the calculation speed but lacks interpretability. • During operational reliability evaluation, a subset of critical samples can significantly impact system reliability, whereas some samples have negligible effects, from which reliability-related knowledge can be derived. • The knowledge-informed data-driven approach embedded with reliability-related knowledge and power system physical knowledge can enhance interpretability and accuracy significantly.
No takes yet. Share an insight, caveat, or question.
Ni et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: