Integrated approach for dynamic economic/emission dispatch problem: multi-objective moth flame optimizer with transmission loss prediction using cascaded forward neural network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Electrical and Electronic Engineering
Link
https://link.springer.com/content/pdf/10.1007/s00202-023-02117-6.pdf
Reference89 articles.
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2. Abualigah L, Yousri D, Abd Elaziz M et al (2021) Aquila optimizer: a novel meta-heuristic optimization algorithm. Comput Ind Eng 157:107250. https://doi.org/10.1016/j.cie.2021.107250
3. Aghaei J, Niknam T, Azizipanah-Abarghooee R, Arroyo JM (2013) Scenario based dynamic economic emission dispatch considering load and wind power uncertainties. Electr Power Energy Syst 47:351–367. https://doi.org/10.1016/j.ijepes.2012.10.069
4. Alham MH, Elshahed M, Ibrahim DK, Abo El Zahab EED (2016) A dynamic economic emission dispatch considering wind power uncertainty incorporating energy storage system and demand side management. Renew Energy 96:800–811. https://doi.org/10.1016/J.RENENE.2016.05.012
5. Basu M (2008) Dynamic economic emission dispatch using nondominated sorting genetic algorithm-II. Int J Electr Power Energy Syst 30:140–149. https://doi.org/10.1016/j.ijepes.2007.06.009
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