The PSE Model-Based Innovation Prize 2019

Runners-up

Demand response-oriented dynamic modeling and operational optimization of membrane-based chlor-alkali plants by Joannah I. Otashu*, Michael Baldea of McKetta Department of Chemical Engineering, The University of Texas at Austin.

Published in Computers & Chemical Engineering Journal, Elsevier.

Abstract

Power-intensive processes can potentially provide significant demand response (DR) services. Modeling such processes for demand response is not trivial as models must depict plant transient properties under highly dynamic operation while remaining computationally efficient. We develop a demand response-oriented model for an important power-intensive process i.e., chlor-alkali production using membrane cells, and demonstrate the provision of fast demand response by an industrial-size plant. Through an extensive simulation and optimization case study, we show that the fast modulation of the cell power demand is possible without adverse impact on cell concentration and temperature. Additionally, the cell temperature dynamics are found to restrict the demand response capacity of the plant and must to be explicitly accounted for to support dynamic cell operation in DR scenarios. Substantial load curtailment during peak electricity price periods can be achieved and the energy cost to the electrolysis plant can be reduced.

* Submitting author

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