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The combined economic environmental dispatch using new hybrid metaheuristic

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  • Gherbi, Yamina Ahlem
  • Bouzeboudja, Hamid
  • Gherbi, Fatima Zohra

Abstract

The combined economic/environmental dispatch treats the economic and environmental impact as competing objectives. This requires effective optimization algorithms to achieve a solution. The firefly algorithm and bat algorithm are the latest methods; they have already proven their effectiveness in several research areas.

Suggested Citation

  • Gherbi, Yamina Ahlem & Bouzeboudja, Hamid & Gherbi, Fatima Zohra, 2016. "The combined economic environmental dispatch using new hybrid metaheuristic," Energy, Elsevier, vol. 115(P1), pages 468-477.
    • Handle: RePEc:eee:energy:v:115:y:2016:i:p1:p:468-477
    DOI: 10.1016/j.energy.2016.08.079
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    References listed on IDEAS

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    1. Basu, M., 2014. "Fuel constrained economic emission dispatch using nondominated sorting genetic algorithm-II," Energy, Elsevier, vol. 78(C), pages 649-664.
    2. Bahmani-Firouzi, Bahman & Farjah, Ebrahim & Azizipanah-Abarghooee, Rasoul, 2013. "An efficient scenario-based and fuzzy self-adaptive learning particle swarm optimization approach for dynamic economic emission dispatch considering load and wind power uncertainties," Energy, Elsevier, vol. 50(C), pages 232-244.
    3. Younes, Mimoun & Khodja, Fouad & Kherfane, Riad Lakhdar, 2014. "Multi-objective economic emission dispatch solution using hybrid FFA (firefly algorithm) and considering wind power penetration," Energy, Elsevier, vol. 67(C), pages 595-606.
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    Citations

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    Cited by:

    1. Al-Bahrani, Loau Tawfak & Chandra Patra, Jagdish, 2018. "Multi-gradient PSO algorithm for optimization of multimodal, discontinuous and non-convex fuel cost function of thermal generating units under various power constraints in smart power grid," Energy, Elsevier, vol. 147(C), pages 1070-1091.
    2. Xin-gang, Zhao & Ze-qi, Zhang & Yi-min, Xie & Jin, Meng, 2020. "Economic-environmental dispatch of microgrid based on improved quantum particle swarm optimization," Energy, Elsevier, vol. 195(C).
    3. Kheshti, Mostafa & Kang, Xiaoning & Bie, Zhaohong & Jiao, Zaibin & Wang, Xiuli, 2017. "An effective Lightning Flash Algorithm solution to large scale non-convex economic dispatch with valve-point and multiple fuel options on generation units," Energy, Elsevier, vol. 129(C), pages 1-15.
    4. Abdulaziz Almalaq & Tawfik Guesmi & Saleh Albadran, 2023. "A Hybrid Chaotic-Based Multiobjective Differential Evolution Technique for Economic Emission Dispatch Problem," Energies, MDPI, vol. 16(12), pages 1-34, June.
    5. Wang, Guibin & Zha, Yongxing & Wu, Ting & Qiu, Jing & Peng, Jian-chun & Xu, Gang, 2020. "Cross entropy optimization based on decomposition for multi-objective economic emission dispatch considering renewable energy generation uncertainties," Energy, Elsevier, vol. 193(C).
    6. Yu, Xiaobing & Duan, Yuchen & Luo, Wenguan, 2022. "A knee-guided algorithm to solve multi-objective economic emission dispatch problem," Energy, Elsevier, vol. 259(C).
    7. Shin, Hansol & Kim, Tae Hyun & Kim, Hyoungtae & Lee, Sungwoo & Kim, Wook, 2019. "Environmental shutdown of coal-fired generators for greenhouse gas reduction: A case study of South Korea," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    8. Zhang, Xian & Wang, Huaizhi & Peng, Jian-chun & Liu, Yitao & Wang, Guibin & Jiang, Hui, 2018. "GPNBI inspired MOSDE for electric power dispatch considering wind energy penetration," Energy, Elsevier, vol. 144(C), pages 404-419.
    9. Liu, Jingsen & Mao, Yinan & Liu, Xiaozhen & Li, Yu, 2020. "A dynamic adaptive firefly algorithm with globally orientation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 174(C), pages 76-101.
    10. Hossein Nourianfar & Hamdi Abdi, 2022. "Environmental/Economic Dispatch Using a New Hybridizing Algorithm Integrated with an Effective Constraint Handling Technique," Sustainability, MDPI, vol. 14(6), pages 1-26, March.

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