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A modified gravitational search algorithm based on a non-dominated sorting genetic approach for hydro-thermal-wind economic emission dispatching

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  • Chen, Fang
  • Zhou, Jianzhong
  • Wang, Chao
  • Li, Chunlong
  • Lu, Peng

Abstract

Wind power is a type of clean and renewable energy, and reasonable utilization of wind power is beneficial to environmental protection and economic development. Therefore, a short-term hydro-thermal-wind economic emission dispatching (SHTW-EED) problem is presented in this paper. The proposed problem aims to distribute the load among hydro, thermal and wind power units to simultaneously minimize economic cost and pollutant emission. To solve the SHTW-EED problem with complex constraints, a modified gravitational search algorithm based on the non-dominated sorting genetic algorithm-III (MGSA-NSGA-III) is proposed. In the proposed MGSA-NSGA-III, a non-dominated sorting approach, reference-point based selection mechanism and chaotic mutation strategy are applied to improve the evolutionary process of the original gravitational search algorithm (GSA) and maintain the distribution diversity of Pareto optimal solutions. Moreover, a parallel computing strategy is introduced to improve the computational efficiency. Finally, the proposed MGSA-NSGA-III is applied to a typical hydro-thermal-wind system to verify its feasibility and effectiveness. The simulation results indicate that the proposed algorithm can obtain low economic cost and small pollutant emission when dealing with the SHTW-EED problem.

Suggested Citation

  • Chen, Fang & Zhou, Jianzhong & Wang, Chao & Li, Chunlong & Lu, Peng, 2017. "A modified gravitational search algorithm based on a non-dominated sorting genetic approach for hydro-thermal-wind economic emission dispatching," Energy, Elsevier, vol. 121(C), pages 276-291.
    • Handle: RePEc:eee:energy:v:121:y:2017:i:c:p:276-291
    DOI: 10.1016/j.energy.2017.01.010
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    2. Massrur, Hamid Reza & Niknam, Taher & Aghaei, Jamshid & Shafie-khah, Miadreza & Catalão, João P.S., 2018. "A stochastic mid-term scheduling for integrated wind-thermal systems using self-adaptive optimization approach: A comparative study," Energy, Elsevier, vol. 155(C), pages 552-564.
    3. Ji, Bin & Zhang, Binqiao & Yu, Samson S. & Zhang, Dezhi & Yuan, Xiaohui, 2021. "An enhanced Borg algorithmic framework for solving the hydro-thermal-wind Co-scheduling problem," Energy, Elsevier, vol. 218(C).
    4. Zhou, Yanlai & Guo, Shenglian & Chang, Fi-John & Liu, Pan & Chen, Alexander B., 2018. "Methodology that improves water utilization and hydropower generation without increasing flood risk in mega cascade reservoirs," Energy, Elsevier, vol. 143(C), pages 785-796.
    5. Rahmani, Shima & Amjady, Nima, 2017. "A new optimal power flow approach for wind energy integrated power systems," Energy, Elsevier, vol. 134(C), pages 349-359.
    6. Li, Chaoshun & Wang, Wenxiao & Chen, Deshu, 2019. "Multi-objective complementary scheduling of hydro-thermal-RE power system via a multi-objective hybrid grey wolf optimizer," Energy, Elsevier, vol. 171(C), pages 241-255.
    7. Yi Yu & Yonggang Wu & Binqi Hu & Xinglong Liu, 2018. "An enhanced artificial bee colony algorithm (EABC) for solving dispatching of hydro-thermal system (DHTS) problem," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-19, January.
    8. Wang, Fengjuan & Xie, Yachen & Xu, Jiuping, 2019. "Reliable-economical equilibrium based short-term scheduling towards hybrid hydro-photovoltaic generation systems: Case study from China," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    9. McLarty, Dustin & Panossian, Nadia & Jabbari, Faryar & Traverso, Alberto, 2019. "Dynamic economic dispatch using complementary quadratic programming," Energy, Elsevier, vol. 166(C), pages 755-764.
    10. 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.
    11. Zhongkai Feng & Wenjing Niu & Sen Wang & Chuntian Cheng & Zhenguo Song, 2019. "Mixed Integer Linear Programming Model for Peak Operation of Gas-Fired Generating Units with Disjoint-Prohibited Operating Zones," Energies, MDPI, vol. 12(11), pages 1-17, June.

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