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Multi-objective hydropower station operation using an improved cuckoo search algorithm

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  • Meng, Xuejiao
  • Chang, Jianxia
  • Wang, Xuebin
  • Wang, Yimin

Abstract

Efficient utilization of water resources in hydropower station operation is an important part of mitigating water and energy scarcity. Exploring efficient multi-objective optimization algorithms and studying the trade-off between water and energy have become the primary goal of multi-objective hydropower station optimal operation (MOHSOO). In this paper, a new improved multi-objective cuckoo search (IMOCS) algorithm is proposed to overcome the shortcomings of MOCS. Specifically, a population initialization strategy based on constraint transformation and the individual constraints and group constraints technique (ICGC) and a dynamic adaptive probability (DAP) are used to improve the search efficiency and the quality of solutions, respectively. A flock search strategy (FSS) is proposed to greatly speed up the convergence and improve the quality of the non-dominated solutions. In addition, the MOCS and NSGA-II are presented as a comparison to test the performance of IMOCS as well as three hybrids of MOCS combined with these strategies. An MOHSOO model of Xiaolangdi and Xixiayuan cascade hydropower stations in the lower Yellow River is built to verify the effectiveness of these algorithms together with five benchmark problems. The results show that IMOCS performs better than other algorithms in convergence speed, convergence property, and diversity of solutions. For the Xiaolangdi hydropower station, there is a strong competitive relationship between power generation and water supply from September to next February, which severely restricts the power generation of the hydropower station.

Suggested Citation

  • Meng, Xuejiao & Chang, Jianxia & Wang, Xuebin & Wang, Yimin, 2019. "Multi-objective hydropower station operation using an improved cuckoo search algorithm," Energy, Elsevier, vol. 168(C), pages 425-439.
    • Handle: RePEc:eee:energy:v:168:y:2019:i:c:p:425-439
    DOI: 10.1016/j.energy.2018.11.096
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    1. Shang, Yizi & Lu, Shibao & Ye, Yuntao & Liu, Ronghua & Shang, Ling & Liu, Chunna & Meng, Xianyong & Li, Xiaofei & Fan, Qixiang, 2018. "China’ energy-water nexus: Hydropower generation potential of joint operation of the Three Gorges and Qingjiang cascade reservoirs," Energy, Elsevier, vol. 142(C), pages 14-32.
    2. 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.
    3. Li, Nan & Chen, Wenying, 2019. "Energy-water nexus in China's energy bases: From the Paris agreement to the Well Below 2 Degrees target," Energy, Elsevier, vol. 166(C), pages 277-286.
    4. Duan, Cuncun & Chen, Bin, 2017. "Energy–water nexus of international energy trade of China," Applied Energy, Elsevier, vol. 194(C), pages 725-734.
    5. Jiang, Zhiqiang & Ji, Changming & Qin, Hui & Feng, Zhongkai, 2018. "Multi-stage progressive optimality algorithm and its application in energy storage operation chart optimization of cascade reservoirs," Energy, Elsevier, vol. 148(C), pages 309-323.
    6. Ibanez, Eduardo & Magee, Timothy & Clement, Mitch & Brinkman, Gregory & Milligan, Michael & Zagona, Edith, 2014. "Enhancing hydropower modeling in variable generation integration studies," Energy, Elsevier, vol. 74(C), pages 518-528.
    7. Tang, Jia & Wang, Dan & Wang, Xuyang & Jia, Hongjie & Wang, Chengshan & Huang, Renle & Yang, Zhanyong & Fan, Menghua, 2017. "Study on day-ahead optimal economic operation of active distribution networks based on Kriging model assisted particle swarm optimization with constraint handling techniques," Applied Energy, Elsevier, vol. 204(C), pages 143-162.
    8. Ju, Liwei & Tan, Zhongfu & Yuan, Jinyun & Tan, Qingkun & Li, Huanhuan & Dong, Fugui, 2016. "A bi-level stochastic scheduling optimization model for a virtual power plant connected to a wind–photovoltaic–energy storage system considering the uncertainty and demand response," Applied Energy, Elsevier, vol. 171(C), pages 184-199.
    9. Chang, XiaoLin & Liu, Xinghong & Zhou, Wei, 2010. "Hydropower in China at present and its further development," Energy, Elsevier, vol. 35(11), pages 4400-4406.
    10. Basu, M. & Chowdhury, A., 2013. "Cuckoo search algorithm for economic dispatch," Energy, Elsevier, vol. 60(C), pages 99-108.
    11. Bo Ming & Jian-xia Chang & Qiang Huang & Yi-min Wang & Sheng-zhi Huang, 2015. "Optimal Operation of Multi-Reservoir System Based-On Cuckoo Search Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5671-5687, December.
    12. Wang, Xuebin & Chang, Jianxia & Meng, Xuejiao & Wang, Yimin, 2018. "Short-term hydro-thermal-wind-photovoltaic complementary operation of interconnected power systems," Applied Energy, Elsevier, vol. 229(C), pages 945-962.
    13. Glotić, Arnel & Glotić, Adnan & Kitak, Peter & Pihler, Jože & Tičar, Igor, 2014. "Optimization of hydro energy storage plants by using differential evolution algorithm," Energy, Elsevier, vol. 77(C), pages 97-107.
    Full references (including those not matched with items on IDEAS)

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