1 Application of Information-Gap Decision Theory to Risk-constrained Self-scheduling of GenCos Behnam Mohammadi-Ivatloo, Student Member, IEEE, Hamidreza Zareipour, Senior Member, IEEE, Nima Amjady, Senior Member, IEEE, Mehdi Ehsan 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 oppor- tunity function. The proposed models are applied to a 54-unit thermal GenCo. Information-Gap Decision Theory (IGDT), Electricity mar- kets, Self-scheduling, Price forecasts, Uncertainty. NOMENCLATURE A. Indices: i Index for generation units running from 1 to N . t Index for operation intervals running from 1 to T . j Index for modeling of minimum ON-time and OFF-time limits running from 1 to Max{MUT i , MDT i }. B. Parameters: a i Quadratic cost coefficient of thermal genera- tion unit i [$/(MW ) 2 h] b i Linear cost coefficient of thermal generation unit i [$/MWh] c i No-load cost coefficient of thermal generation unit i [$/h] ˜ λ(t) Forecasted market price for interval t P min (i) Minimum power generation of unit i SU (i) Start up cost of unit i SDC(i) Constant shut down cost of unit i B. Mohammadi-ivatloo and M. Ehsan are with the Center of Excel- lence in Power System Management and Control, Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran, e-mail: (bmo- hamma@ucalgary.ca, ehsan@sharif.edu) H. Zareipour is with the Department of Electrical and Computer Engineer- ing, University of Calgary, Alberta, Canada; http://www.ucalgary.ca/power (e- mail: h.zareipour@ucalgary.ca). N. Amjady is with the Department of Electrical Engineering, Semnan University, Semnan 35195-363, Iran (e-mail: amjady@tavanir.org.ir) UR(i) Ramp up limit of unit i (MW/hr) DR(i) Ramp down limit of unit i (MW/hr) MUT i Minimum up time of unit i MDT i Minimum down time of unit i ˜ u Nominal value of uncertain variable B c Critical profit B w Target profit C. Variables: B Total profit of the GenCo over the operation period Cost(t) Total cost at time t λ(t) Market clearing price at interval t SDC(i, t) Shut-down cost of i-th unit at time t SUC(i, t) Start-up cost of i-th unit at time t P (i, t) Power generation of unit i in operation interval t V (i, t) Binary variable to represent on-off status of unit i at time t ΔP (i, t) A continuous positive auxiliary variable for defining the power generation u Uncertain parameter in IGDT model q Decision variable in IGDT model α Horizon of the uncertain variable D. Functions: ⌢ α(q,r c ) Information-gap robustness function ⌢ β (q,r w ) The information-gap opportunity function R(q,u) System model in IGDT method U (α, ˜ u) Uncertainty model in IGDT method I. I NTRODUCTION I N a deregulated electricity market, generation companies (GenCos) schedule their short-term operation with the objective of maximizing their profit [1]. Optimal operation schedules are determined by solving a self-scheduling prob- lem, and are used as the basis of GenCo’s bidding strategies. However, various sources of uncertainty, such as unknown market dynamics or forced outrages, may impact a GenCo’s profit. In particular, electricity market price uncertainty is a major factor in short-term self-scheduling problem, and thus, it has been widely addressed in the literature. The literature on GenCo self-scheduling can be generally categorized into two main groups, i.e., risk-neutral and risk- constrained. In the first group, it is assumed that accurate