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Optimal Operation of Interprovincial Hydropower System Including Xiluodu and Local Plants in Multiple Recipient Regions

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  • Jianjian Shen

    (Institute of Hydropower and Hydroinformatics, Dalian University of Technology, Dalian, Liaoning 116024, China)

  • Xiufei Zhang

    (Institute of Hydropower and Hydroinformatics, Dalian University of Technology, Dalian, Liaoning 116024, China)

  • Jian Wang

    (Institute of Hydropower and Hydroinformatics, Dalian University of Technology, Dalian, Liaoning 116024, China)

  • Rui Cao

    (Institute of Hydropower and Hydroinformatics, Dalian University of Technology, Dalian, Liaoning 116024, China)

  • Sen Wang

    (Key laboratory of the Pearl River Estuarine Dynamics and Associated Process Regulation, Ministry of Water Resources, Guangzhou 510611, China)

  • Jun Zhang

    (State Grid Zhejiang Electric Power Company, Hangzhou, Zhejiang 310000, China)

Abstract

This paper focuses on the monthly operations of an interprovincial hydropower system (IHS) connected by ultrahigh voltage direct current lines. The IHS consists of the Xiluodu Hydropower Project, which ranks second in China, and local plants in multiple recipient regions. It simultaneously provides electricity for Zhejiang and Guangdong provinces and thus meets their complex operation requirements. This paper develops a multi-objective optimization model of maximizing the minimum of total hydropower generation for each provincial power grid while considering network security constraints, electricity contracts, and plant constraints. The purpose is to enhance the minimum power in dry season by using the differences in hydrology and regulating storage of multiple rivers. The TOPSIS method is utilized to handle this multi-objective optimization, where the complex minimax objective function is transformed into a group of easily solved linear formulations. Nonlinearities of the hydropower system are approximatively described as polynomial formulations. The model was used to solve the problem using mixed integer nonlinear programming that is based on the branch-and-bound technique. The proposed method was applied to the monthly generation scheduling of the IHS. Compared to the conventional method, both the total electricity for Guangdong Power Grid and Zhejiang Power Grid during dry season increased by 6% and 4%, respectively. The minimum monthly power also showed a significant increase of 40% and 31%. It was demonstrated that the hydrological differences between Xiluodu Plant and local hydropower plants in receiving power grids can be fully used to improve monthly hydropower generation.

Suggested Citation

  • Jianjian Shen & Xiufei Zhang & Jian Wang & Rui Cao & Sen Wang & Jun Zhang, 2019. "Optimal Operation of Interprovincial Hydropower System Including Xiluodu and Local Plants in Multiple Recipient Regions," Energies, MDPI, vol. 12(1), pages 1-19, January.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:1:p:144-:d:194380
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    Cited by:

    1. Sung-Min Cho & Jin-Su Kim & Jae-Chul Kim, 2019. "Optimal Operation Parameter Estimation of Energy Storage for Frequency Regulation," Energies, MDPI, vol. 12(9), pages 1-21, May.
    2. Lingquan Dai & Huichao Dai & Haibo Liu & Yu Wang & Jiali Guo & Zhuosen Cai & Chenxi Mi, 2020. "Development of an Optimal Model for the Xiluodu-Xiangjiaba Cascade Reservoir System Considering the Downstream Environmental Flow," Sustainability, MDPI, vol. 12(3), pages 1-18, January.
    3. Rui Cao & Jianjian Shen & Chuntian Cheng & Jian Wang, 2020. "Optimization Model for the Long-Term Operation of an Interprovincial Hydropower Plant Incorporating Peak Shaving Demands," Energies, MDPI, vol. 13(18), pages 1-21, September.
    4. Philip Mayer & Christopher Stephen Ball & Stefan Vögele & Wilhelm Kuckshinrichs & Dirk Rübbelke, 2019. "Analyzing Brexit: Implications for the Electricity System of Great Britain," Energies, MDPI, vol. 12(17), pages 1-27, August.
    5. Shen, Jianjian & Cheng, Chuntian & Wang, Sen & Yuan, Xiaoye & Sun, Lifei & Zhang, Jun, 2020. "Multiobjective optimal operations for an interprovincial hydropower system considering peak-shaving demands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    6. Iram Parvez & Jianjian Shen & Ishitaq Hassan & Nannan Zhang, 2021. "Generation of Hydro Energy by Using Data Mining Algorithm for Cascaded Hydropower Plant," Energies, MDPI, vol. 14(2), pages 1-28, January.

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