Optimization Framework to Assess the Demand Response Capacity of a Water Distribution System

Yang Liu, Clayton Barrows, Jordan Macknick, Meagan Mauter

Research output: Contribution to journalArticlepeer-review

19 Scopus Citations

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.

Original languageAmerican English
Article numberArticle No. 04020063
Number of pages13
JournalJournal of Water Resources Planning and Management
Volume146
Issue number8
DOIs
StatePublished - 1 Aug 2020

Bibliographical note

Publisher Copyright:
© 2020 American Society of Civil Engineers.

NREL Publication Number

  • NREL/JA-6A20-76008

Keywords

  • demand response capacity
  • modeling
  • optimization framework
  • water distribution

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