Application of Monte Carlo Simulation for the Probabilistic Assessment of Hydropower Generator Capacity Loss Due to Forced Outages
Open Access DepositedThe Bonneville Power Administration (BPA), the federal transmission and marketing agency for the 31-dam Federal Columbia River Power System (FCRPS), is preparing to join the Western Resource Adequacy Program (WRAP) as a binding participant in FY 2027. WRAP participation requires BPA to commit generation capacity for grid reliability seven months in advance, creating operational challenges for capacity planning across the multi-agency FCRPS system. Forced outages present significant risks to BPA's capacity commitments, potentially resulting in lost revenue from marketable surplus capacity or costly capacity deficits. The current deterministic planning approach inadequately accounts for forced outage probabilities and limits BPA's ability to optimize capacity commitments while maintaining capacity obligations. This study develops a probabilistic Monte Carlo simulation model to forecast hydropower generator capacity loss due to forced outages, enabling more accurate capacity planning and revenue optimization. The model utilizes five years of historical forced outage data (2019-2023) from FCRPS hydropower plants to predict capacity loss in 2024. Validation results demonstrate significant improvements over current deterministic methods. The probabilistic model achieved greater accuracy in forced outage capacity loss estimates, increased marketable surplus capacity for WRAP by over 50 MW, and established capacity reserve levels that avoided potential capacity deficits. These improvements were validated despite 2024 experiencing anomalously high forced outage rates. This research contributes to capacity planning methodologies for cooperative resource adequacy programs and provides practical benefits for WRAP's 22 utility members in advancing regional resource adequacy. The validated probabilistic assessment offers broader applications for the energy sector through its use of actual forced outage data and generator availability modeling. The model will support BPA's operational planning for seven-month forward-showing capacity commitments during critical summer and winter peak load periods in WRAP.
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