A priority list based approach for solving thermal unit commitment problem with novel hybrid genetic-imperialist competitive algorithm

This paper has proposed a novel Hybrid modified Genetic - Imperialist Competitive Algorithm (HGICA) for solving thermal Unit Commitment Problem (UCP). The UCP is a mixed integer problem with many equality and inequality constraints like the minimum down and minimum up time, spinning reserve, and ramp rate so need to a complex optimization process. In this paper the constraint handling of the problem is realized without any penalizing of solutions so a wide range of feasible solutions will be available for final optimum response. The proposed modified genetic is a novel method which has better performance than its original version and helps ICA to find more optimized responses and escape for local minimum areas easily. The main advantages of HGICA are good quality of the solution and high computational speed, which make it a suitable method for solving optimization problems. This method is carried out for three case studies including 10 and 20 units systems to efficiency of it be proved. Also the obtained results is compared to other optimization methods represented in literature for different scenarios.