Solving Nonlinear Single-Unit Commitment Problem by Genetic Algorithm Based Clustering Technique

M.A El-Shorbagy; A.A Mousa; M Farag

doi:10.18488/journal.76.2017.41.11.29

Authors

M.A El-Shorbagy Department of Basic Engineering Science, Faculty of Engineering, Shebin El-Kom, Menoufia University, Egypt
A.A Mousa Department of Basic Engineering Science, Faculty of Engineering, Shebin El-Kom, Menoufia University, Egypt & Department of Mathematics and Statistics, Faculty of sciences, Taif University, Saudi Arabia
M Farag Department of Basic Engineering Science, Faculty of Engineering, Shebin El-Kom, Menoufia University, Egypt

DOI:

https://doi.org/10.18488/journal.76.2017.41.11.29

Abstract

Nonlinear single-unit commitment problem (NSUCP) is a NP-hard nonlinear mixed-integer optimization problem, encountered as one of the toughest problems in power systems. This paper presents a new algorithm for solving NSUCP using genetic algorithm (GA) based clustering technique. The proposed algorithm integrates the main features of binary-real coded GA and K-means clustering technique. Clustering technique divides population into a specific number of subpopulations. In this way, different operators of GA can be used instead of using one operator to the whole population to avoid the local minima and introduce diversity. The effectiveness of the proposed algorithm is validated by comparison with other well-known techniques. By comparison with the previously reported results, it is found that the performance of the proposed algorithm quite satisfactory.