Multiobjective Scheduling Method for Short-Term Peak Shaving Operation of Cascade Hydro Plants
Publication: Journal of Water Resources Planning and Management
Volume 146, Issue 9
Abstract
With structural changes in power consumption, peak load demands and peak-valley differences are growing, which motivates peak shaving operations of hydropower systems. A multiobjective mixed-integer nonlinear programming model is presented for short-term hydropower generation scheduling that aims to regulate peak loads and enhance power efficiency. The combined feasible operation zones and the aggregate generation function of each plant are embedded in this model to deal with the operation constraints of units. A set of Pareto solutions of this model is generated by an improved normalized constraint method that narrows the optimization range to ensure the practicality and compact distribution of solutions, each of which represents an aggregated scheduling of cascaded hydropower plants. Then, a mixed integer nonlinear programming formulation is developed to solve the unit commitment problem for each solution, and a fuzzy-based membership value assignment method is employed to extract a best compromise solution for final implementation. A case study of the hydropower plants of the Beipanjiang cascade in China is used to test the proposed approach, verifying its success in generating a practical operating schedule while providing abundant information to decision makers for decision support.
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Data Availability Statement
Some data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request, including the proposed multiobjective MINLP model, the UC model, and the LINGO codes used in solving the subproblems of INNC method and the UC model.
Acknowledgments
The work described in this paper was supported by the National Nature Science Foundation of China (No. 91547201), and the National Natural Science Foundation of China (No. U1765103).
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Published In
Journal of Water Resources Planning and Management
Volume 146 • Issue 9 • September 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Mar 13, 2019
Accepted: Apr 1, 2020
Published online: Jun 18, 2020
Published in print: Sep 1, 2020
Discussion open until: Nov 18, 2020
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