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Hybrid HS–random search algorithm considering ensemble and pitch violation for unit commitment problem

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Abstract

Harmony search (HS) is a population-based metaheuristics search algorithm inspired from the musical process of searching for a perfect state of harmony. The pitch of each musical instrument determines the aesthetic quality, just as the fitness function value determines the quality of decision variables. In the musical improvisation process, all players sound pitches within possible range together to make one harmony. If all the pitches make a good harmony, each player stores in his memory that experience and the possibility of making a good harmony is increased next time. Even though HS has the ability to escape from local minima, it does not require differential gradients and initial value setting for the variables, is free from divergence and has strong ability to explore the regions of solution space in a reasonable time. However, it has lower exploitation ability in later period and it easily trapped into local optima and converges very slowly. To improve the exploitation ability of HS algorithm in later stage and provide global optimal solution, a novel and hybrid version of harmony search combined with random search algorithm is presented in the proposed research to solve single-area unit commitment problem of electric power system. The proposed algorithm is tested for standard IEEE systems consisting of 4, 10, 20 and 40 generating units. The effectiveness of proposed hybrid algorithm is compared with other well-known evolutionary, heuristics and metaheuristics search algorithms, and it has been found that performance of proposed algorithm is much better than of classical harmony search algorithm and improved harmony search algorithm as well as recently developed algorithms. Sensitivity analysis on proposed algorithm shows that low value of pitch adjustment rate results in better cost, and parametric test on proposed algorithm shows the rejection of the null hypothesis at the alpha significance level.

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Acknowledgments

The corresponding author wish to thank DAV University, Jalandhar, and I.K. Gujral Punjab Technical University, Jalandhar (Punjab), for providing advanced research facilities during research work.

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  1. Research Scholar, Department of Electrical Engineering, I.K. Gujral Punjab Technical University, Kapurthala, Punjab, India

    Vikram Kumar Kamboj

  2. Department of Electrical Engineering, Giani Zail Singh Campus College of Engineering & Technology, Bathinda, Punjab, India

    S. K. Bath

  3. Department of Electrical and Instrumentation Engineering, Sant Longowal Institute of Engineering and Technology, Longowal, Punjab, India

    J. S. Dhillon

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  1. Vikram Kumar Kamboj
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Correspondence to Vikram Kumar Kamboj.

Appendix

Appendix

See Tables 19, 20, 21, 22 and Figs. 11, 12.

Table 19 Test data for 4-unit system [73]
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Table 20 Load demand for 4-unit test system
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Table 21 Test data for 10-unit system [73]
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Table 22 Load demand pattern for 24 h for 10-unit system
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Fig. 12
figure 12

Pseudo-code for various repairing of UCP constraints

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Kamboj, V.K., Bath, S.K. & Dhillon, J.S. Hybrid HS–random search algorithm considering ensemble and pitch violation for unit commitment problem. Neural Comput & Applic 28, 1123–1148 (2017). https://doi.org/10.1007/s00521-015-2114-6

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