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Ameliorated artificial hummingbird algorithm for coordinated wind-solar-thermal generation scheduling problem in multiobjective framework

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  • Kansal, Veenus
  • Dhillon, J.S.

Abstract

This paper proposed an optimization technique, namely ameliorated artificial hummingbird algorithm (AAHA), that blends artificial hummingbird algorithm (AHA) with simplex search strategy (SSS) to solve the coordinated wind-solar-thermal generation scheduling problem. The AAHA simulates the foraging behaviour of hummingbirds for food, including guided, territorial, and migration foraging. Guided foraging helps in the higher exploration in the initial stages, and territorial foraging performs the exploitation in its neighbourhood. Migration foraging explores the search space. The SSS enhances the weak territorial and migration foraging of AHA by improving the exploitation mechanism. The proposed method is simple and has less dependency on parameters to adjust. The solar and wind units are committed to ascertaining their share for uninterrupted supply. The price penalty method is applied to unify the emission of gaseous pollutants due to thermal generation with operating costs. To reduce the use of coal, renewable energy sources have been considered in this problem which results in reducing the pollutants’ emissions and saving in fuel costs. To solve the dynamic multivariable constrained optimization problem, the forward approach has been implemented. The performance of the proposed algorithm is tested on different electric test systems, and a statistical test justifies the results.

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  • Kansal, Veenus & Dhillon, J.S., 2022. "Ameliorated artificial hummingbird algorithm for coordinated wind-solar-thermal generation scheduling problem in multiobjective framework," Applied Energy, Elsevier, vol. 326(C).
    • Handle: RePEc:eee:appene:v:326:y:2022:i:c:s0306261922012880
    DOI: 10.1016/j.apenergy.2022.120031
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    References listed on IDEAS

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    1. Xu, Jiuping & Wang, Fengjuan & Lv, Chengwei & Huang, Qian & Xie, Heping, 2018. "Economic-environmental equilibrium based optimal scheduling strategy towards wind-solar-thermal power generation system under limited resources," Applied Energy, Elsevier, vol. 231(C), pages 355-371.
    2. Oracio I. Barbosa-Ayala & Jhon A. Montañez-Barrera & Cesar E. Damian-Ascencio & Adriana Saldaña-Robles & J. Arturo Alfaro-Ayala & Jose Alfredo Padilla-Medina & Sergio Cano-Andrade, 2020. "Solution to the Economic Emission Dispatch Problem Using Numerical Polynomial Homotopy Continuation," Energies, MDPI, vol. 13(17), pages 1-15, August.
    3. Xiong, Guojiang & Shi, Dongyuan, 2018. "Hybrid biogeography-based optimization with brain storm optimization for non-convex dynamic economic dispatch with valve-point effects," Energy, Elsevier, vol. 157(C), pages 424-435.
    4. Yin, Linfei & Sun, Zhixiang, 2021. "Multi-layer distributed multi-objective consensus algorithm for multi-objective economic dispatch of large-scale multi-area interconnected power systems," Applied Energy, Elsevier, vol. 300(C).
    5. Liu, Zhi-Feng & Li, Ling-Ling & Liu, Yu-Wei & Liu, Jia-Qi & Li, Heng-Yi & Shen, Qiang, 2021. "Dynamic economic emission dispatch considering renewable energy generation: A novel multi-objective optimization approach," Energy, Elsevier, vol. 235(C).
    6. Qiao, Baihao & Liu, Jing, 2020. "Multi-objective dynamic economic emission dispatch based on electric vehicles and wind power integrated system using differential evolution algorithm," Renewable Energy, Elsevier, vol. 154(C), pages 316-336.
    7. Alsumait, J.S. & Sykulski, J.K. & Al-Othman, A.K., 2010. "A hybrid GA-PS-SQP method to solve power system valve-point economic dispatch problems," Applied Energy, Elsevier, vol. 87(5), pages 1773-1781, May.
    8. Alham, M.H. & Elshahed, M. & Ibrahim, Doaa Khalil & Abo El Zahab, Essam El Din, 2016. "A dynamic economic emission dispatch considering wind power uncertainty incorporating energy storage system and demand side management," Renewable Energy, Elsevier, vol. 96(PA), pages 800-811.
    9. Al-Bahrani, Loau Tawfak & Horan, Ben & Seyedmahmoudian, Mehdi & Stojcevski, Alex, 2020. "Dynamic economic emission dispatch with load dema nd management for the load demand of electric vehicles during crest shaving and valley filling in smart cities environment," Energy, Elsevier, vol. 195(C).
    10. Kheshti, Mostafa & Ding, Lei & Ma, Shicong & Zhao, Bing, 2018. "Double weighted particle swarm optimization to non-convex wind penetrated emission/economic dispatch and multiple fuel option systems," Renewable Energy, Elsevier, vol. 125(C), pages 1021-1037.
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    1. Zhang, Yagang & Wang, Hui & Wang, Jingchao & Cheng, Xiaodan & Wang, Tong & Zhao, Zheng, 2024. "Ensemble optimization approach based on hybrid mode decomposition and intelligent technology for wind power prediction system," Energy, Elsevier, vol. 292(C).

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