Optimization Framework to Assess the Demand Response Capacity of a Water Distribution System
Publication: Journal of Water Resources Planning and Management
Volume 146, Issue 8
Abstract
As large electricity consumers, water distribution system (WDS) pumping stations have the potential to become meaningful participants in demand response (DR) programs. The authors propose an optimization framework for assessing the DR capacity of a WDS and identifying the optimal bidding strategy for maximizing WDS revenue in the DR spot market. The proposed mixed integer linear programming (MILP) model overcomes computational constraints of previous DR optimization models by adopting a preprocessing procedure to minimize the number of binary variables and implementing a convex relaxation technique to linearize the hydraulic equations. The proposed MILP model also explicitly accounts for varying levels of risk tolerance of WDS operators by varying the recovery period over which pumping returns to business-as-usual operation. The optimization framework is implemented on a skeletonized 48-node WDS model that includes 7 pumps, 6 tanks, and 39 pipes. Using a simulated DR event and water consumption profile, the authors derive the optimal DR supply curves (i.e., compensation price versus load curtailment quantity) and revenue potential of the WDS under six scenarios for DR participation.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available from the corresponding author by request.
Acknowledgments
This work has been supported by the National Renewable Energy Laboratory, discretionary funds of M. Mauter at Stanford and CMU, and the Center for Climate and Energy Decision Making through a cooperative agreement between CMU and NSF (SES-0949710).
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Published In
Journal of Water Resources Planning and Management
Volume 146 • Issue 8 • August 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: May 9, 2019
Accepted: Feb 24, 2020
Published online: May 29, 2020
Published in print: Aug 1, 2020
Discussion open until: Oct 29, 2020
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