Title: A data-driven linear formulation of the optimal demand response scheduling problem for an industrial air separation unit

Journal Article · · Chemical Engineering Science
 [1];  [2];  [3];  [3];  [3];  [2]
  1. University of Texas, Austin, TX (United States); OSTI
  2. University of Texas, Austin, TX (United States)
  3. Smart Operations, Center of Excellence (COE), Tonawanda, NY (United States)
+ Show Author Affiliations

Demand response (DR) has become a key element in balancing the power grid as the contribution of time-varying renewable power generation increases. Chemical plants are appealing candidates for DR programs as they offer large, concentrated and flexible loads. DR participation calls for frequent production rate changes over time scales that overlap with the dominant dynamics of the plant. Production scheduling should therefore consider the process dynamics explicitly. Here we present a data-driven approach for modelling the scheduling-relevant dynamics based on historical closed-loop operating data using autoregressive with extra inputs (ARX) models. We introduce a new, linear scheduling problem formulation based on the ARX representation, and demonstrate its implementation on an industrial air separation unit.

Research Organization:
Krell Institute, Ames, IA (United States); University of California, Los Angeles, CA (United States); University of Texas, Austin, TX (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Grant/Contract Number:
EE0007613; FG02-97ER25308
OSTI ID:
1976947
Journal Information:
Chemical Engineering Science, Journal Name: Chemical Engineering Science Journal Issue: C Vol. 252; ISSN 0009-2509
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

References (23)

Enterprise-wide optimization: A new frontier in process systems engineering journal January 2005
Air separation with cryogenic energy storage: Optimal scheduling considering electric energy and reserve markets journal February 2015
Dynamic modeling and collocation-based model reduction of cryogenic air separation units journal January 2016
Demand response scheduling under uncertainty: Chance‐constrained framework and application to an air separation unit journal July 2020
Reduced dynamic modeling approach for rectification columns based on compartmentalization and artificial neural networks journal February 2019
A flexible air separation process: 2. Optimal operation using economic model predictive control journal July 2019
An MILP framework for optimizing demand response operation of air separation units journal July 2018
Integration of production planning and scheduling: Overview, challenges and opportunities journal December 2009
Optimal multi-scale capacity planning for power-intensive continuous processes under time-sensitive electricity prices and demand uncertainty. Part I: Modeling journal June 2014
Integrated production scheduling and process control: A systematic review journal December 2014
A time scale-bridging approach for integrating production scheduling and process control journal August 2015
A discrete-time scheduling model for continuous power-intensive process networks with various power contracts journal January 2016
An efficient MILP framework for integrating nonlinear process dynamics and control in optimal production scheduling calculations journal February 2018
A simulation-based optimization framework for integrating scheduling and model predictive control, and its application to air separation units journal May 2018
Optimal demand response scheduling of an industrial air separation unit using data-driven dynamic models journal July 2019
Development of a digital twin for a flexible air separation unit using a pressure-driven simulation approach journal August 2021
An empirical study of moving horizon closed-loop demand response scheduling journal August 2020
Optimal scheduling of multiple sets of air separation units with frequent load-change operation journal January 2017
Optimal Process Operations in Fast-Changing Electricity Markets: Framework for Scheduling with Low-Order Dynamic Models and an Air Separation Application journal April 2016
Energy-Efficient Production Scheduling of a Cryogenic Air Separation Plant journal April 2017
Novel Formulation for Optimal Schedule with Demand Side Management in Multiproduct Air Separation Processes journal January 2019
110th Anniversary: Using Data to Bridge the Time and Length Scales of Process Systems journal August 2019
The Bang-Bang Principle for Linear Control Systems
  • Sonneborn, L. M.; Van Vleck, F. S.
  • Journal of the Society for Industrial and Applied Mathematics Series A Control, Vol. 2, Issue 2 https://doi.org/10.1137/0302013
journal January 1964

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42 ENGINEERING
ARX
ASU
air separation units
autoregressive with extra inputs
demand response
models
production scheduling
scale bridging models