Case Studies
Jun 21, 2016

Centralized versus Distributed Cooperative Operating Rules for Multiple Cascaded Hydropower Reservoirs

Publication: Journal of Water Resources Planning and Management
Volume 142, Issue 11

Abstract

Multiple cascaded hydropower reservoir systems serving the same area need to cooperate to increase overall benefits and reliability. To meet system demand while balancing among cascaded systems, both centralized and distributed five segment energy available based operating rules, making power decisions for subsystems and the whole system, are proposed for cooperation across multiple cascaded hydropower reservoirs. Unlike existing methods, the cooperative operating rules are optimized to the global objective of maximizing the minimum system power production, with constraints on local cascade minimum energy generation to confine the possible local profit earnings or losses because of cooperation, making the operating rules more acceptable for cooperative operations among local cascade system agents. The operating rule optimization models are solved using a genetic algorithm. A case study for three cascaded systems in southwest China shows that distributed and centralized cooperative operating rules can increase minimum total power by more than 3,600 MW and 4,700 MW, respectively, in the dry season with little energy changes in each cascaded system, taking advantages of reservoir storages and different timing of inflows. The centralized rule is superior to the distributed rule for increasing minimum power, although the distributed rule is more effective to control the energy for each cascaded system. The distributed and centralized rules adapt to higher subsystem energy constraints and higher interbasin compensation demands.

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Acknowledgments

The research work described in this paper is supported by the National Nature Science Foundation of China (91547201, 51210014).

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Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 142Issue 11November 2016

History

Received: Aug 5, 2015
Accepted: Mar 23, 2016
Published online: Jun 21, 2016
Published in print: Nov 1, 2016
Discussion open until: Nov 21, 2016

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Authors

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Assistant Professor, Dept. of Institute of Hydropower and Hydroinformatics, Dalian Univ. of Technology, Dalian 116024, China; Visiting Scholar, Center for Watershed Sciences, Univ. of California, Davis, CA 95616. E-mail: [email protected]
Chuntian Cheng [email protected]
Professor, Dept. of Institute of Hydropower and Hydroinformatics, Dalian Univ. of Technology, Dalian 116024, China (corresponding author). E-mail: [email protected]
Ph.D. Student, Dept. of Institute of Hydropower and Hydroinformatics, Dalian Univ. of Technology, Dalian 116024, China. E-mail: [email protected]
Jay R. Lund, Dist.M.ASCE [email protected]
Professor, Dept. of Civil and Environmental Engineering, Univ. of California, Davis, CA 95616. E-mail: [email protected]

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