Assessing Resource Adequacy in Power Systems Using Mid-Term Unit Commitment Models

Abstract

The increasing penetration of renewable energy sources and the displacement of conventional generation pose significant challenges for ensuring an uninterrupted power supply in modern power systems. Accurate resource adequacy (RA) assessments are therefore essential for maintaining security of supply and supporting system operation planning. This work proposes an RA assessment framework by developing two mid-term Unit Commitment (UC) models to calculate RA metrics. A detailed UC model is formulated as a mixed-integer linear program (MILP) that minimizes load shedding while considering operational constraints and hourly dispatch detail to enhance solution accuracy. To reduce computational complexity, a linear program (LP) is also developed by relaxing the binary variables of the UC model. These models are applied within a rolling-horizon framework, enabling fast and high-quality solutions for seasonal and mid-term planning horizons. Both mid-term UC models are applied to the Cyprus power system using real data. Simulation results based on 900 annual scenarios show that the MILP-based UC model improves solution accuracy by 11% compared to a base-case approach, while the LP-based model generates solutions approximately four times faster with a small optimality gap of 0.25%. The results also show the probability distribution of RA metrics across the scenarios, enabling the assessment of system reliability and resilience through their mean, Value-at-Risk, and Conditional Value-at-Risk indicators.