Optimizing Desalination Operations for Energy Flexibility

Akshay Rao, Adam Atia, Bernard Knueven, Meagan Mauter

Research output: Contribution to journalArticlepeer-review

Abstract

Despite the value of energy optimization in desalination processes, modeling dynamic operations for monthly billing periods has remained a computational challenge. This work proposes a framework for energy flexibility optimization, which includes new modeling features for independent operation of parallel skids, start-up delays associated with chemical stabilization, the consideration of industrial energy tariff structures, and inclusion of hourly electrical carbon intensities. This is done using a modular and computationally efficient formulation that guarantees a globally optimal solution with standard optimization solvers. The approach is demonstrated in two distinct case studies: a seawater desalination plant in Santa Barbara, CA, and an indirect potable reuse facility in San Jose, CA. Trends predicted from the model are validated against operational facility measurements from a demand response shutdown event. Preliminary results show that optimizing energy flexibility can result in 18.51% monthly cost savings over energy efficiency-optimized operation. The value extracted from a facility-wide shutdown during peak electricity price hours is hampered by start-up delays in post-treatment chemical stabilization. In cases in which a facility does not have much excess capacity, using a flow equalization tank or operating over a wide recovery range may be cost-effective.
Original languageAmerican English
Pages (from-to)15696-15704
Number of pages9
JournalACS Sustainable Chemistry and Engineering
Volume12
Issue number42
DOIs
StatePublished - 2024

NREL Publication Number

  • NREL/JA-2C00-90919

Keywords

  • convex optimization
  • desalination
  • energy flexibility
  • mixed-integer programming

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