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Dynamic economic emission dispatch considering renewable energy generation: A novel multi-objective optimization approach

Author

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  • Liu, Zhi-Feng
  • Li, Ling-Ling
  • Liu, Yu-Wei
  • Liu, Jia-Qi
  • Li, Heng-Yi
  • Shen, Qiang

Abstract

This study contributes to construct the mathematical model of hybrid dynamic economic emission dispatch (HDEED) considering renewable energy generation and propose a novel solving approach based on enhanced moth-flame optimization algorithm. Renewable energy power generation technology has an important impact on reducing pollutant emissions and promoting sustainable development. Therefore, this study aims to investigate the HDEED problem in consideration of renewable energy generation and improve the economic and environmental benefits of the power system. First, a moth-flame optimization algorithm based on position disturbance updating strategy (MFO_PDU) was proposed aiming at the non-convex, non-linear and high-dimensional characteristics of HDEED problem. Second, the mathematical model of HDEED on the basis of Wind-Solar-Thermal integrated energy was constructed, while taking into account the valve point effect, equality constraints and inequality constraints. Finally, three cases including test systems of different scales were formulated and employed to verify the proposed approach, and the compromise solution was determined through membership function. The results revealed that the fuel cost obtained by the MFO_PDU algorithm was 11.31%, 4.01% and 5.27% smaller than those of HHO, TSA and MFO algorithms for small-scale test system. Accordingly, the research outcomes contribute in reducing the fuel cost and pollutant emissions of power generation system, and further improving the utilization and penetration rate of renewable energy.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:energy:v:235:y:2021:i:c:s0360544221016558
    DOI: 10.1016/j.energy.2021.121407
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    as
    1. Shen, Xin & Zou, Dexuan & Duan, Na & Zhang, Qiang, 2019. "An efficient fitness-based differential evolution algorithm and a constraint handling technique for dynamic economic emission dispatch," Energy, Elsevier, vol. 186(C).
    2. Chen, Min-Rong & Zeng, Guo-Qiang & Lu, Kang-Di, 2019. "Constrained multi-objective population extremal optimization based economic-emission dispatch incorporating renewable energy resources," Renewable Energy, Elsevier, vol. 143(C), pages 277-294.
    3. 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.
    4. 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.
    5. Xiang, Yue & Wu, Gang & Shen, Xiaodong & Ma, Yuhang & Gou, Jing & Xu, Weiting & Liu, Junyong, 2021. "Low-carbon economic dispatch of electricity-gas systems," Energy, Elsevier, vol. 226(C).
    6. Hlalele, Thabo G. & Zhang, Jiangfeng & Naidoo, Raj M. & Bansal, Ramesh C., 2021. "Multi-objective economic dispatch with residential demand response programme under renewable obligation," Energy, Elsevier, vol. 218(C).
    7. 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.
    8. 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.
    9. Zheng, Lingwei & Zhou, Xingqiu & Qiu, Qi & Yang, Lan, 2020. "Day-ahead optimal dispatch of an integrated energy system considering time-frequency characteristics of renewable energy source output," Energy, Elsevier, vol. 209(C).
    10. 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.
    11. Li, Xiaozhu & Wang, Weiqing & Wang, Haiyun & Wu, Jiahui & Fan, Xiaochao & Xu, Qidan, 2020. "Dynamic environmental economic dispatch of hybrid renewable energy systems based on tradable green certificates," Energy, Elsevier, vol. 193(C).
    12. 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).
    13. 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.
    Full references (including those not matched with items on IDEAS)

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