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SCIENCE CHINA Information Sciences, Volume 62, Issue 7: 070210(2019) https://doi.org/10.1007/s11432-018-9715-2

Dynamic economic emission dispatch based on multi-objectivepigeon-inspired optimization with double disturbance

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  • ReceivedAug 15, 2018
  • AcceptedNov 30, 2018
  • PublishedMay 9, 2019

Abstract

There is no abstract available for this article.


Acknowledgment

This work was supported by National Natural Science Foundation of China (Grant Nos. 61673404, 61873292), Key Scientific Research Projects in Colleges and Universities of Henan Province (Grant Nos. 19A120014, 17A470006), and Innovative Talents Project of Henan (Grant No. 16HASTIT033).


Supplement

Appendixes A–D.


References

[1] Xia X, Elaiw A M. Optimal dynamic economic dispatch of generation: A review. Electric Power Syst Res, 2010, 80: 975-986 CrossRef Google Scholar

[2] Yorino N, Hafiz H M, Sasaki Y. High-Speed Real-Time Dynamic Economic Load Dispatch. IEEE Trans Power Syst, 2012, 27: 621-630 CrossRef ADS Google Scholar

[3] Roy P K, Bhui S. A multi-objective hybrid evolutionary algorithm for dynamic economic emission load dispatch. Int Trans Electr Energ Syst, 2016, 26: 49-78 CrossRef Google Scholar

[4] Zhu Z, Wang J, Baloch M H. Dynamic economic emission dispatch using modified NSGA-II. Int Trans Electr Energ Syst, 2016, 26: 2684-2698 CrossRef Google Scholar

[5] Basu M. Dynamic Economic Emission Dispatch Using Evolutionary Programming and Fuzzy Satisfying Method. Int J Emerging Electric Power Syst, 2007, 8: 1-15 CrossRef Google Scholar

[6] Qu B Y, Zhu Y S, Jiao Y C. A survey on multi-objective evolutionary algorithms for the solution of the environmental/economic dispatch problems. Swarm Evolary Computation, 2018, 38: 1-11 CrossRef Google Scholar

[7] Duan H B, Qiao P X. Pigeon-inspired optimization:A new swarm intelligence optimizer for air robot pathplanning. Int J Intell Comput Cybern, 2014, 7: 2--21. Google Scholar

[8] Lei X, Ding Y, Wu F X. Detecting protein complexes from DPINs by density based clustering with Pigeon-Inspired Optimization Algorithm. Sci China Inf Sci, 2016, 59: 070103 CrossRef Google Scholar

[9] Qiu H X, Duan H B. Multi-objective pigeon-inspired optimization for brushless direct current motor parameter design. Sci China Technol Sci, 2015, 58: 1915-1923 CrossRef Google Scholar

  • Table 1   Results obtained by IMPIO-DD and MPIO for all the three cases
    Case1Case2Case3
    MethodObjectiveCost (Emission (lb)Cost (Emission (lb)Cost(Emission (lb)
    Best cost255496.9328110550114.0744119780140.4679
    IMPIO-DDBest emission268395.697612372068.431313724092.2827
    Best compromise258805.972011671082.1513128580101.3510
    Best cost260276.220811622088.1546127300113.2912
    MPIO Best emission 260366.210811744083.4975127850111.0852
    Best compromise 260306.217011660086.5584127550112.1846

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