Application of information-gap decision theory to risk-constrained self-scheduling of GenCos

Abstract

In a competitive electricity market, a generation company (GenCo) optimizes its operation schedules, referred to as self-scheduling, in order to maximize its profit. However, various sources of uncertainty, such as market price fluctuations or forced outage of generating units, may impact the GenCo's profit. In this paper, a non-probabilistic information-gap model is proposed to model the uncertainties in short-term scheduling of a GenCo. The self-scheduling problem is formulated for risk-neutral, risk-averse, and risk-seeker GenCos. Robustness of the decisions against low market prices are evaluated using a robustness model. Furthermore, windfall higher profit due to unpredicted higher market prices is modeled using an opportunity function. The proposed models are applied to a 54-unit thermal GenCo.