Optimizing Hydropower Reservoirs Operation via an Orthogonal Progressive Optimality Algorithm
Publication: Journal of Water Resources Planning and Management
Volume 144, Issue 3
Abstract
The progressive optimality algorithm (POA) is commonly used to identify optimal hydropower operation schedules in China. However, POA may not converge within a reasonable time for large and complex problems because its computational burden grows exponentially with the expansion of system scale. In order to effectively alleviate the dimensionality problem of POA, an improved POA variant called orthogonal progressive optimality algorithm (OPOA) is introduced in this paper. In the OPOA, an orthogonal experimental design is used to replace the exhaustive combinatorial evaluation at each POA two-stage subproblem. The theoretical analysis shows that POA and OPOA have exponential and approximately polynomial growth in computational complexity, respectively. The proposed method is applied to a large-scale multireservoir system located on the Wu River in China. The results indicate that, compared with POA, OPOA can remarkably enhance the computing efficiency in different cases, showing its practicability and feasibility for multireservoir system operation.
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Acknowledgments
The authors would like to thank editors and reviewers for their valuable comments and suggestions. This paper is supported by Natural Science Foundation of China (51709119, 91547201 and 51210014) and the Fundamental Research Funds for the Central Universities (HUST: 2017KFYXJJ193).
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Published In
Journal of Water Resources Planning and Management
Volume 144 • Issue 3 • March 2018
Copyright
©2018 American Society of Civil Engineers.
History
Received: Feb 7, 2017
Accepted: Aug 4, 2017
Published online: Jan 4, 2018
Published in print: Mar 1, 2018
Discussion open until: Jun 4, 2018
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