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Application of a Novel Jaya Algorithm Based on Chaotic Sequence and Opposition-based Learning in the Multi-objective Optimal Operation of Cascade Hydropower Stations System

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Abstract

The traditional operation of the cascade hydropower stations system (CHPS) mainly focus on the maximization of power generation benefits, but ignores the interference of CHPS operation to the river ecosystem, therefore, carrying out the multi-objective optimal operation (MOOP) of CHPS considering ecological demands is crucial. In this paper, a MOOP model considering the ecological objective is established. To effectively solve the MOOP problems, a novel multi-objective Jaya algorithm (MOCOM-Jaya) is proposed, where the quality of the initial population is enhanced based on the chaotic sequence, the later disturbance term and Gaussian mutation are incorporated to improve the local search ability, the elite opposition-based learning is adopted to broaden the optimization space. The proposed algorithm is applied to the study of MOOP of CHPS in the Wujiang river, and the results show that compared with MOPSO and NSGA-II, MOCOM-Jaya can gain the solution set with better convergence and distribution for the MOOP. The competition relationship between the power generation objective (PGO) and the ecological objective (ECO) is revealed based on the partial replacement ratio method. The results show that the competitiveness of PGO and ECO experienced a trade lead with the increase of power generation. The mean competitiveness ratios of PGO to ECO (\(\overline {CP{R_{P - E}}} \) ) in three typical years (dry, normal, wet) are 3.22, 3.17 and 3.15, indicating that the PGO is dominant in the competition with the ECO as a whole.

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Availability of Data and Material

Streamflow data and parameters data of hydropower stations are obtained from Changjiang Water Resources Commission of the Ministry of Water Resources.

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Acknowledgements

The research was funded by the National Key Research & Development Project of China(2016YFC0402209)

Funding

The research was funded by the National Key Research & Development Project of China(Grant number: 2016YFC0402209).

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Authors and Affiliations

  1. College of Hydrology and Water Resources, Hohai University, Nanjing, 210098, China

    Yiming Wei & Zengchuan Dong

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  1. Yiming Wei
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  2. Zengchuan Dong
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Yiming Wei. Zengchuan Dong helped perform the analysis with constructive discussions. Zengchuan Dong is the recipient of the funding. The first draft of the manuscript was written by Yiming Wei and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Zengchuan Dong.

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Wei, Y., Dong, Z. Application of a Novel Jaya Algorithm Based on Chaotic Sequence and Opposition-based Learning in the Multi-objective Optimal Operation of Cascade Hydropower Stations System. Water Resour Manage 35, 1397–1413 (2021). https://doi.org/10.1007/s11269-020-02731-0

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  • DOI: https://doi.org/10.1007/s11269-020-02731-0

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