A Modified Artificial Bee Colony for the Non-Smooth Dynamic Economic/Environmental Dispatch

Authors

  • Ι. Marouani National School of Engineering of Sfax (ENIS), University of Sfax, Tunisia
  • A. Boudjemline College of Engineering, University of Hail, Saudi Arabia
  • T. Guesmi College of Engineering, University of Hail, Saudi Arabia | University of Sfax, ENIS, Tunisia
  • H. H. Abdallah Electrical Engineering Department, University of Sfax, Tunisia
Volume: 8 | Issue: 5 | Pages: 3321-3328 | October 2018 | https://doi.org/10.48084/etasr.2098

Abstract

This paper presents an improved artificial bee colony (ABC) technique for solving the dynamic economic emission dispatch (DEED) problem. Ramp rate limits, valve-point loading effects and prohibited operating zones (POZs) have been considered. The proposed technique integrates the grenade explosion method and Cauchy operator in the original ABC algorithm, to avoid random search mechanism. However, the DEED is a multi-objective optimization problem with two conflicting criteria which need to be minimized simultaneously. Thus, it is recommended to provide the best solution for the decision-makers. Shannon’s entropy-based method is used for the first time within the context of the on-line planning of generator outputs to extract the best compromise solution among the Pareto set. The robustness of the proposed technique is verified on six-unit and ten-unit system tests. Results proved that the proposed algorithm gives better optimum solutions in comparison with more than ten metaheuristic techniques.

Keywords:

evolutionary computation, power generation dispatch, optimal scheduling, decision making, cost function

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References

P. K. Roy, S. A. Bhui, “Multi-objective hybrid evolutionary algorithm for dynamic economic emission load dispatch”, International Transactions on Electrical Energy Systems, Vol. 26, No. 1, pp. 49-78, 2016 DOI: https://doi.org/10.1002/etep.2066

R. Muthuswamy, M. Krishnan, K. Subramanian, B. Subramanian, “Environmental and economic power dispatch of thermal generators using modified NSGA-II algorithm”, International Transactions on Electrical Energy Systems, Vol. 25, No. 8, pp. 1552-1569, 2014 DOI: https://doi.org/10.1002/etep.1918

K. Tlijani, T. Guesmi, H. Hadj Abdallah, “Dynamic coupled Active–Reactive Dispatch Including SVC Devices with Limited Switching Operations”, Arabian Journal for Science and Engineering, Vol. 42, No. 7, pp. 2651-2661, 2017 DOI: https://doi.org/10.1007/s13369-016-2286-0

X. Jiang, J. Zhou, H. Wang, Y. Zhang, “Dynamic environmental economic dispatch using multiobjective differential evolution algorithm with expanded double selection and adaptive random restart”, International Journal of Electrical Power & Energy Systems, Vol. 49, pp. 399-407, 2013 DOI: https://doi.org/10.1016/j.ijepes.2013.01.009

K. Vaisakh, P. Praveena, K. Naga Sujatha, “Solution of dynamic economic emission dispatch problem by hybrid bacterial foraging algorithm”, International Journal of Computer Science and Electronics Engineering, Vol. 2, No. 1, pp. 58-64, 2014

Z. Zhu, J. Wang, M. H. Baloch, “Dynamic economic emission dispatch using modified NSGA-II”, International Transactions on Electrical Energy Systems, Vol. 26, No. 12, pp. 2684-2698, 2016 DOI: https://doi.org/10.1002/etep.2228

M. K. Sharma, P. Phonrattanasak, N. Leeprechanon, “Improved bees algorithm for dynamic economic dispatch considering prohibited operating zones”, IEEE-Innovative Smart Grid Technologies-Asia (ISGT ASIA), Bangkok, Thailand, November 3-6, 2015 DOI: https://doi.org/10.1109/ISGT-Asia.2015.7386972

M. I. Behnam, R. Abbas, S. Alireza, “Nonconvex dynamic economic power dispatch problems solution using hybrid immune-genetic algorithm”, IEEE Systems Journal, Vol. 7, No. 4, pp. 777-785, 2013 DOI: https://doi.org/10.1109/JSYST.2013.2258747

T. Sen, H. D. Mathur, “A new approach to solve economic dispatch problem using a hybrid ACO–ABC–HS optimization algorithm”, International Journal of Electrical Power & Energy Systems, Vol. 78, pp. 735-744, 2016 DOI: https://doi.org/10.1016/j.ijepes.2015.11.121

Z. Liang, J. D. Glover, “A zoom feature for a dynamic programming solution to economic dispatch including transmission losses”, IEEE Transactions on Power Systems, Vol. 7, No. 2, pp. 544-550, 1992 DOI: https://doi.org/10.1109/59.141757

M. C. W. Gar, J. G. Aganagic, B. Tony Meding Jose, S. Reeves, “Experience with mixed integer linear programming based approach on short term hydrothermal scheduling”, IEEE Transactions on Power Systems, Vol. 16, No. 4, pp. 743-749, 2001 DOI: https://doi.org/10.1109/59.962421

M. Basu, “Dynamic economic emission dispatch using nondominated sorting genetic algorithm-II”, International Journal of Electrical Power & Energy Systems, Vol. 30, pp. 140-149, 2008 DOI: https://doi.org/10.1016/j.ijepes.2007.06.009

J. B. Park, K. S. Lee, J. R. Shin, K. Y. Lee, “A particle swarm optimization for economic dispatch with nonsmooth cost functions”, IEEE Transactions on Power Systems, Vol. 20, No. 1, pp. 34-42, 2005 DOI: https://doi.org/10.1109/TPWRS.2004.831275

I. Ziane, F. Benhamida, A. Graa, “Simulated annealing algorithm for combined economic and emission power dispatch using max/max price penalty factor”, Neural Computing and Applications, Vol. 28 (Suppl. 1), pp. 197-205, 2017 DOI: https://doi.org/10.1007/s00521-016-2335-3

W. M. Lin, F. S. Cheng, M. T. Tsay, “An improved Tabu search for economic dispatch with multiple minima”, IEEE Transactions on Power Systems, Vol. 17, No. 1, pp. 108-112, 2002 DOI: https://doi.org/10.1109/59.982200

J. G. Zheng, C. Q. Zhang, Y. Q. Zhou, “Artificial bee colony algorithm combined with grenade explosion method and Cauchy operator for global optimization”, Mathematical Problems in Engineering, Vol. 2015, Article ID 739437, 2015 DOI: https://doi.org/10.1155/2015/739437

D. Karaboga, An idea based on honey bee swarm for numerical optimization, Tech Rep TR06, Erciyes University, Engineering Faculty, Computer Engineering Department, Turkey, 2005

C. Zhang, J. Zheng, Y. Zhou, “Two modified artificial bee colony algorithms inspired by grenade explosion method”, Neurocomputing, Vol. 151, No. 3, pp. 1198-1207, 2015 DOI: https://doi.org/10.1016/j.neucom.2014.04.082

A. Ahrari, A. A. Atai, “Grenade explosion method-A novel tool for optimization of multimodal functions”, Applied Soft Computing, Vol. 10, pp. 1132-1140, 2010 DOI: https://doi.org/10.1016/j.asoc.2009.11.032

R. Venkata Rao, “A material selection model using graph theory and matrix approach”, Material Science Engineering: A, Vol. 431, No. 1-2, pp. 248-255, 2006 DOI: https://doi.org/10.1016/j.msea.2006.06.006

M. Soleimani-Damaneh, M. Zarepisheh, “Shannon’s entropy for combining the efficiency results of different DEA models: Method and application”, Expert Systems with Applications, Vol. 36, pp. 5146-5150, 2009 DOI: https://doi.org/10.1016/j.eswa.2008.06.031

A. Hafezalkotob, A. Hafezalkotob, “Extended MULTIMOORA method based on Shannon entropy weight for materials selection”, Journal of Industrial Engineering International, Vol. 12, No. 1, pp. 1-13, 2016 DOI: https://doi.org/10.1007/s40092-015-0123-9

N. Pandit, A. Tripathi, S. Tapaswi, M. Pandit, “An improved bacterial foraging algorithm for combined static/dynamic”, Applied Soft Computing, Vol. 12, No. 11, pp. 3500-3513, 2012 DOI: https://doi.org/10.1016/j.asoc.2012.06.011

A. Hafezalkotob, A. Hafezalkotob, “Fuzzy entropy-weighted MULTIMOORA method for materials selection”, Journal of Intelligent & Fuzzy Systems, Vol. 31, No. 3, pp. 1211-1226, 2016 DOI: https://doi.org/10.3233/IFS-162186

Y. A. Gherbi, H. Bouzeboudja, F. Z. Gherbi, “The combined economic environmental dispatch using new hybrid metaheuristic”, Energy, Vol. 115, Part 1, pp. 486-477, 2016 DOI: https://doi.org/10.1016/j.energy.2016.08.079

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How to Cite

[1]
Marouani Ι., Boudjemline, A., Guesmi, T. and Abdallah, H.H. 2018. A Modified Artificial Bee Colony for the Non-Smooth Dynamic Economic/Environmental Dispatch. Engineering, Technology & Applied Science Research. 8, 5 (Oct. 2018), 3321–3328. DOI:https://doi.org/10.48084/etasr.2098.

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