Economic assessment of hydropower capacity expansions and multi-market participation using a multi-stage stochastic framework

The growing need for flexibility in modern power systems increases the value of hydropower in capacity markets. This paper presents a stochastic optimization framework for quantifying the benefits of capacity market participation and evaluating hydropower capacity upgrades. Spot price outcomes for the 2030 electricity market have been simulated across multiple historical weather years and clustered using the K-means method. Uncertainty in energy prices and inflow is represented through a scenario tree constructed using Markov chain logic. Stochastic Dual Dynamic Programming has been applied to generate cuts embedded in a simulation model for statistical analysis. A case study of a NO₂ hydropower plant indicates that combining energy and capacity market participation with a 75% capacity upgrade could enhance revenues by nearly 50% compared to energy-only participation. Future work could incorporate stochastic modeling of capacity market prices, reserve activation and market saturation, and tax-related considerations for hydropower producers.