Extended neighborhood search algorithm for constrained unit commitment

This paper presents an efficient approach to short term unit commitment based on tabu search and Benders decomposition. Additional constraints representing fuel consumption, emission limits, transmission flows and MWh limits are discussed. The augmented Lagrangian relaxation is applied for calculating the initial solution. Starting from the initial solution, the Benders cut is embedded in the extended neighborhood search to form an efficient optimization method. A 53 unit system is tested and results are provided to show the features of the proposed method. The results show that, in spite of the feasibility of the initial solution, a better solution can be searched by the proposed method. The method can be used to verify and improve the results obtained by other methods. It also provides a means for power systems real-rime rescheduling when various constraints are to be considered. (C) 1997 Elsevier Science Ltd.