Hydropower Scheduling with State-Dependent Discharge Constraints: An SDDP Approach
Publication: Journal of Water Resources Planning and Management
Volume 148, Issue 11
Abstract
Environmental constraints in hydropower systems serve to ensure sustainable use of water resources. Through accurate treatment in hydropower scheduling, one seeks to respect such constraints in the planning phase while optimizing the utilization of hydropower. However, many environmental constraints introduce state-dependencies and even nonconvexities to the scheduling problem, making them challenging to represent in stochastic hydropower scheduling models. This paper describes how the state-dependent maximum discharge constraint, which is widely enforced in the Norwegian hydropower system, can be embedded within the stochastic dual dynamic programming (SDDP) algorithm for hydropower scheduling without compromising computational time. In this work, a combination of constraint relaxation and time-dependent auxiliary lower reservoir volume bounds is applied, and the modeling is verified through computational experiments on two different systems. The results demonstrate that the addition of an auxiliary lower bound on reservoir volume has significant potential for improved system operation, and that a bound based on the minimum accumulated inflow in the constraint period is the most efficient.
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Data Availability Statement
All data and code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was funded by The Research Council of Norway through Project No. 257588.
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Journal of Water Resources Planning and Management
Volume 148 • Issue 11 • November 2022
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This work is made available under the terms of the Creative Commons Attribution 4.0 International license, https://creativecommons.org/licenses/by/4.0/.
History
Received: Oct 21, 2021
Accepted: Jun 28, 2022
Published online: Sep 14, 2022
Published in print: Nov 1, 2022
Discussion open until: Feb 14, 2023
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