A fuzzy optimization-based approach to large scale thermal unit commitment

This paper presents a new fuzzy optimization based approach to solve the thermal unit commitment (UC) problem. In this approach load demand, reserve requirements, and production cost are expressed by fuzzy set notations, while unit generation limits, ramp rate limits, and minimum up/down limits are handled as crisp constraints. A fuzzy optimization based algorithm is then, developed to find the optimal solution by using fuzzy operations and "if-then" rules. Some heuristics such as dividing hourly load and generating units into levels are used to speed the solution. The approach has been applied to a 38 units thermal power system. The results are compared with that obtained by the dynamic programming (DP), the Lagrangiane-relaxation (LR), constraint logic programming (CLP), and simulated annealing (SA) methods. The achieved results prove the effectiveness, and validity of the proposed approach to solve the large-scale UC problem. The effects of unit ramp rate limits and minimum up/down times are also, investigated. (C) 2004 Published by Elsevier B.V.