Determining Planning Reserve Margin Levels Through Probabilistic Reliability Assessment

This paper investigates the appropriate Planning Reserve Margin (PRM) level to ensure power system adequacy in capacity expansion planning (CEP) models. Recognizing that capacity adequacy is inherently a stochastic issue, this study bridges the deterministic PRM approach with probabilistic reliability assessment, combining the strengths of both methods. A CEP model is developed and applied including adequacy constraints with PRM levels spanning from 0 % to 30 %. The different system development scenarios generated for each PRM level are then fed into a stochastic adequacy assessment model, built upon Monte Carlo simulations technique. For each scenario, the Loss of Load Expectation (LOLE) and Expected Energy Not Served (EENS) indicators are associated with the corresponding PRM level. Results indicate that a PRM level of at least 17.5 % is necessary to meet the reliability criterion. Furthermore, an analysis regarding the optimal balance between investment costs and EENS reduction suggests an optimal PRM range between 15 % and 20 % as well, indicating that excessive PRM levels would lead to unnecessary investments in underutilized capacity.