Cuckoo search algorithm using different distributions for short-term hydrothermal scheduling with cascaded hydropower plants

This paper proposes a cuckoo search algorithm (CSA) using different distributions for solving short-term hydrothermal scheduling (ST-HTS) problem with cascaded hydropower plants. The CSA method is a new meta-heuristic algorithm inspired from the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds of other species for solving optimization problems. The advantages of the CSA method are few control parameters and effective for optimization problems with complicated constraints. In the proposed CSA, three distributions have been used including Lévy distribution, Gaussian distribution and Cauchy distribution. The proposed methods have been tested on one system having one thermal plant and four cascaded hydropower plants scheduled in twenty-four subintervals and the obtained results have been compared to those from other methods available in the literature. The result comparisons have indicated that the proposed method is a very favorable method for solving the short term hydrothermal scheduling problems with cascaded hydropower plants.