Abstract

This paper proposes a mixed-integer nonlinear programming approach to maximize the total expected profit of a price-taker hydro producer operating in a pool-based electricity market. Head dependence, commitment decisions, discharge ramping, startup costs and forbidden zones are all effectively handled in our approach. Market uncertainty is modeled via price scenarios and risk management is suitably addressed using conditional value-at-risk. Appropriate offering strategies to the day-ahead market are developed, consisting of hourly supply functions generated for different risk levels. A realistic cascaded hydro system with seven reservoirs is considered as a case study for analyzing and comparing risk-neutral vs. risk-averse results. Conclusions are duly drawn.

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