Unit Maintenance Scheduling by means of Fuzzy-Game Theory, Considering Uncertainty in Rival-Genco's Data
A. H. Bozorgi, M.M. Pedarm, G. Reza Yousefi, “Unit Maintenance Scheduling by means of Fuzzy-Game Theory, Considering Uncertainty in Rival-Genco's Data”, 18th Iranian Conference on Electrical Engineering, 11-13 May 2010, ICEE2010, Isfahan, Iran, pp. 889 – 894.
Gencos, in a restructured power system, try to schedule their generators' maintenance in order to maximize their profit. Besides, Unit Maintenance Scheduling (UMS) as a mid-term plan has a significant effect on the Genco's profit in a power market. In a regulated power system, UMS is usually determined by a central system, such as System Operator (SO). On the other hand, in a de-regulated power system, UMS is determined through multiple interactions between the market players, mainly Gencos and SO. Considering these, it would be a desire to solve both short term and mid-term problems, in a single framework. In this case, Gencos can offer a price curve with an outlook to mid-term goals in a game-theoretic approach. The approach would be based on some predictions of parameters such as production cost factors. This article, addresses the uncertainty in the cost factors of a Rival-Genco in a fuzzy game theoretic scheme and experimental results show the effectiveness of the proposed approach.