Fast solutions for UC problems by a new metaheuristic approach

Abstract

Due to its combinatorial nature, the Unit Commitment problem has for long been an important research challenge, with several optimization techniques, from exact to heuristic methods, having been proposed to deal with it. In line with one current trend of research, metaheuristic approaches have been studied and some interesting results have already been achieved and published. However, a successful utilization of these methodologies in practice, when embedded in Energy Management Systems, is still constrained by the reluctance of industrial partners in using techniques whose performance highly depends on a correct parameter tuning. Therefore, the application of metaheuristics to the Unit Commitment problem does still justify further research. In this paper we propose a new search strategy, for Local Search based metaheuristics, that tries to overcome this issue. The approach has been tested in a set of instances, leading to very good results in terms of solution cost, when compared either to the classical Lagrangian Relaxation or to other metaheuristics. It also drastically reduced the computation times. Furthermore, the approach proved to be robust, always leading to good results independently of the metaheuristic parameters used.