Optimal Operation of Multi-reservoir Systems Considering Time-lags of Flood Routing

Wang Zhang, Pan Liu (), Xizhen Chen, Li Wang, Xueshan Ai, Maoyuan Feng, Dedi Liu and Yuanyuan Liu
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Wang Zhang: Wuhan University
Pan Liu: Wuhan University
Xizhen Chen: Wuhan University
Li Wang: Guangxi Water and Power Design Institute
Xueshan Ai: Wuhan University
Maoyuan Feng: Wuhan University
Dedi Liu: Wuhan University
Yuanyuan Liu: Wuhan University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2016, vol. 30, issue 2, No 5, 523-540

Abstract: Abstract Operations of multi-reservoir systems are nonlinear and high-dimensional problems, which are difficult to find the optimal or near-optimal solution owing to the heavy computation burden. This study focuses on flood control operation of multi-reservoir systems considering time-lags caused by Muskingum flood routing of river channels. An optimal model is established to jointly minimize the flood peak on the downstream flood control station for the multi-reservoir systems. A hybrid algorithm, Progressive Optimality Algorithm and Successive Approximation (POA-SA), is improved to solve the multi-reservoir operation model by modifying the POA. The POA-SA uses the DPSA to reduce the spatial dimensionality due to the multiple reservoirs, and adopts an improved POA to alleviate the temporal dimensionality caused by the time-lags of the Muskingum flood routing. Linear programming is then implemented to verify the solution of the POA-SA method with a linear approximation of the discharge capacity curve. The multi-reservoir systems of China’s Xijiang River is selected for a case study. Results show that the flood peak of Wuzhou station can be averagely decreased by 6730 m3/s (12.8 %) for the 100-year return period floods, indicating that the proposed method is efficient to operate the multi-reservoir systems and resolve the time-lags issues.

Keywords: Multi-reservoir systems; Optimization; Muskingum; Progressive optimality algorithm; Successive approximation; Linear programming (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s11269-015-1175-8

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