Data-Driven Reliability Evaluation of the Integrated Energy System Considering Optimal Service Restoration

The demand for environmental protection and energy utilization transformation has promoted the rapid development of integrated systems (IES). Reliability evaluation is a fundamental element in designing IES as it could instruct planning operation IES. This study proposes novel data-driven reliability improvement method considering three-state model an optimal service restoration (OSR). First, multi-energy flow introduced linearized order to reduce computing complexity. Next, developed, transitional process partial failure mode. Furthermore, established determine best repairment moment minimizing load curtailment, developed that integrates OSR models stochastic state transition using historical measurement data smart meters. Finally, proposed tested on test IES, numerical results validate its effectiveness evaluating improving overall reliability.