Adaptive-robust multi-resolution generation maintenance scheduling with probabilistic reliability constraint

This study presents a reliability-constrained adaptive-robust multi-resolution model for generation maintenance scheduling (GMS) problem considering the uncertainty sources of electricity demand, wind power generation, and equipment unavailabilities. In the proposed tri-level adaptive-robust model, a polyhedral uncertainty set is used to model the electricity demand and wind power generation fluctuations. In addition, equipment unavailabilities as discrete uncertainty sources are modelled in the reliability sub-problem where the expected energy not supplied is determined as a reliability criterion. Accordingly, the proposed model obtains a robust maintenance schedule for generating units immunised against the worst realisation of electricity demand and wind power generation while satisfying the reliability constraint considering equipment unavailabilities. Moreover, maintenance and operation periods are specifically modelled using different resolutions in the proposed multi-resolution GMS approach. To solve the proposed reliability-constrained adaptive-robust multi-resolution model, a new solution approach including Benders cut, reliability cut, and block coordinate descent method is presented. Numerical results on two test systems show the effectiveness of both the proposed GMS model and the proposed solution approach.