Technical Papers
Apr 29, 2019

Efficient Tabu Search Procedure for Short-Term Planning of Large-Scale Hydropower Systems

Publication: Journal of Water Resources Planning and Management
Volume 145, Issue 7

Abstract

Short-term hydrogeneration scheduling aims at minimizing water consumption for the next 7–15 days on an hourly basis, while satisfying the electrical load as well as many operational, regulatory, and safety requirements. In an ever-changing environment, planners need to make decisions quickly and often adapt their schedules to new conditions. They need a tool that is fast, reactive, and flexible. This paper presents a new solution approach that provides, within a few minutes of computation, near-optimal solutions to hard problems, in which one seeks to determine the number of committed generating units and turbined and spilled flows on an hourly basis for a planning horizon of 10 days. Our solution approach is based on tabu search with new neighborhoods, allowing simultaneous modifications for several plants and time periods. It can handle multiobjective problems, as well as nonlinear and nonconvex constraints. A decomposition mechanism allows parallelism and search acceleration for long horizons and large production systems. Computational experiments on real instances from Hydro-Québec show that even with the most naïve initial solution, our approach finds solutions almost as good as mixed integer linear programming solutions up to 235 times faster than conventional solvers and with less modeling limitations. Starting from a previous planning solution yields even better results.

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Acknowledgments

This work was supported by NSERC/Hydro-Québec Industrial Research Chair on the Stochastic Optimization of Electricity Generation, Hydro-Québec Production, and Mitacs through the Mitacs Accelerate program. We also wish to thank the anonymous referees who reviewed this paper for their insightful comments.

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Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 145Issue 7July 2019

History

Received: Mar 29, 2018
Accepted: Oct 22, 2018
Published online: Apr 29, 2019
Published in print: Jul 1, 2019
Discussion open until: Sep 29, 2019

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Authors

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Ph.D. Candidate, Dept. of Mathematics and Industrial Engineering, Polytechnique Montréal, Montreal, QC, Canada H3T 1J4 (corresponding author). ORCID: https://orcid.org/0000-0002-4441-1667. Email: [email protected]
Michel Gendreau
Professor, Dept. of Mathematics and Industrial Engineering, Polytechnique Montréal, Montreal, QC, Canada H2Z 1A4.
Marko Blais
Engineer, Hydro-Québec Production, Blvd. René-Lévesque, Montreal, QC, Canada H2Z 1A4.
Grégory Emiel
Optimization Analyst, Hydro-Québec Production, Blvd. René-Lévesque, Montreal, QC, Canada H3T 1J4.

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