Short-Term Operation Optimization of Cascade Hydropower Reservoirs with Linear Functional Analysis

  • Yanke ZhangEmail author
  • Jinjun You
  • Changming Ji
  • Jiajie Wu
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 849)


In the operation optimization of cascade hydropower reservoirs, upstream reservoir outflow is usually taken as downstream reservoir inflow, which influences generation scheme accuracy when flow time-lag cannot be neglected. In this study, based on linear space mapping and bounded linear functional theory, the relationship between upstream reservoir outflow and downstream reservoir inflow is quantized. Their corresponding map functions and functional operators are proposed considering river channel storage capacity. Additionally, a short-term generation optimization model of cascade hydropower reservoirs considering flow time-lag is established, with no impact on the objective function and water balance. Furthermore, to verify the feasibility and effectiveness of the model, it is applied to the short-term generation optimization of Jinping-Guandi cascade hydropower reservoirs in Yalong River. Results tally more with the actual operation process compared with the original scheme. This work can increase generation scheduling accuracy and provide reference for short-term operation of cascade hydropower reservoirs.


Flow time-lag Cascade hydropower reservoirs Short-term optimization model Linear functional analysis 



This study was financially supported by the 13th Five-Year National Key Program of China (2016YFC0402208, 2016YFC0402200), the Open Research Fund of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin(China Institute of Water Resources and Hydropower Research) (IWHR-SKL-201420, 2016TS04), the National Science Foundation(51709105, 51279062), the Major Consulting Strategic Project of Engineering Institute (2016-ZD-08-05), the National Key R&D Program of China(2017YFC0405906) and the Fundamental Research Funds for the Central Universities (2016MS51, JB2015169, 2014XS51). The authors are grateful to the anonymous reviewers for their comments and valuable suggestions.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Yanke Zhang
    • 1
    Email author
  • Jinjun You
    • 2
  • Changming Ji
    • 1
  • Jiajie Wu
    • 1
  1. 1.School of Renewable EnergyNorth China Electric Power UniversityBeijingChina
  2. 2.China Institute of Water Resources and Hydropower ResearchBeijingChina

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