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

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

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.

Suggested Citation

  • M.A El-Shorbagy & A.A Mousa & M Farag, 2017. "Solving Nonlinear Single-Unit Commitment Problem by Genetic Algorithm Based Clustering Technique," Review of Computer Engineering Research, Conscientia Beam, vol. 4(1), pages 11-29.
    • Handle: RePEc:pkp:rocere:v:4:y:2017:i:1:p:11-29:id:1451
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    1. M. A. El-Shorbagy & A. A. Mousa & M. A. Farag, 2019. "An intelligent computing technique based on a dynamic-size subpopulations for unit commitment problem," OPSEARCH, Springer;Operational Research Society of India, vol. 56(3), pages 911-944, September.

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