Risk-Constrained Profit Maximization in Day-Ahead Electricity Market

• Published in: IEEE transactions on power systems Vol. 24; no. 3; pp. 1107 - 1114
• Main Authors: Dicorato, M., Forte, G., Trovato, M., Caruso, E.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2009; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Conditional value at risk; Constraint optimization; day-ahead energy market; Deregulation; Economic forecasting; efficient frontier; Electric power generation; Electric variables measurement; Electricity; electricity price uncertainty; Electricity supply industry; Electricity supply industry deregulation; Energy management; expected profit; Job shop scheduling; Markets; Maximization; Optimization; Power generation; Risk; Risk management; Scheduling; Stochastic processes
• ISSN: 0885-8950; 1558-0679
• DOI: 10.1109/TPWRS.2009.2022975

The deregulation of the electricity industry has caused for the generation company (Genco) the need of tools for measuring and managing the risk, beyond the classical problem of generating unit scheduling. In this paper, a probabilistic framework for the problem of managing risk faced by Gencos trading in day-ahead energy market is proposed. In particular, a stochastic forecast of electricity price and the technical features of hydrothermal units are considered. The approach is based on an optimization procedure for maximizing expected profits in the presence of risk constraints. Conditional value at risk for the distribution of daily profit is used as risk measure.