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Title: Dynamic model-based sensor network design algorithm for system efficiency maximization

Here, a dynamic model-based sensor network design (DMSND) algorithm has been developed for maximizing system efficiency for an estimator-based control system. The algorithm synthesizes the optimal sensor network in the face of disturbances or set point changes. Computational expense of the large-scale combinatorial optimization problem is significantly reduced by parallel computing and by using combination of three novel strategies: multi-rate sampling frequency, model order reduction, and use of an incumbent solution that enables early termination of evaluation of infeasible sensor sets. The developed algorithm is applied to an acid gas removal unit as part of an integrated gasification combined cycle power plant with carbon capture. Even though there are more than thousand process states and more than hundred candidate sensor locations, the optimal sensor network design problem for maximizing process efficiency could be solved within couple of hours for a given budget.
Authors:
 [1] ;  [1] ;  [1] ;  [2]
  1. West Virginia Univ., Morgantown, WV (United States)
  2. West Virginia Univ., Morgantown, WV (United States); National Energy Technology Lab. (NETL), Morgantown, WV (United States)
Publication Date:
Type:
Accepted Manuscript
Journal Name:
Computers and Chemical Engineering
Additional Journal Information:
Journal Volume: 89; Journal Issue: C; Journal ID: ISSN 0098-1354
Publisher:
Elsevier
Research Org:
National Energy Technology Lab. (NETL), Morgantown, WV (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
47 OTHER INSTRUMENTATION; Dynamic model-based sensor network design; Efficiency maximization; Multi-rate sampling; Incumbent solution; Parallel computing; Acid gas removal unit
OSTI Identifier:
1477854

Paul, Prokash, Bhattacharyya, Debangsu, Turton, Richard, and Zitney, Stephen E. Dynamic model-based sensor network design algorithm for system efficiency maximization. United States: N. p., Web. doi:10.1016/j.compchemeng.2016.01.018.
Paul, Prokash, Bhattacharyya, Debangsu, Turton, Richard, & Zitney, Stephen E. Dynamic model-based sensor network design algorithm for system efficiency maximization. United States. doi:10.1016/j.compchemeng.2016.01.018.
Paul, Prokash, Bhattacharyya, Debangsu, Turton, Richard, and Zitney, Stephen E. 2016. "Dynamic model-based sensor network design algorithm for system efficiency maximization". United States. doi:10.1016/j.compchemeng.2016.01.018. https://www.osti.gov/servlets/purl/1477854.
@article{osti_1477854,
title = {Dynamic model-based sensor network design algorithm for system efficiency maximization},
author = {Paul, Prokash and Bhattacharyya, Debangsu and Turton, Richard and Zitney, Stephen E.},
abstractNote = {Here, a dynamic model-based sensor network design (DMSND) algorithm has been developed for maximizing system efficiency for an estimator-based control system. The algorithm synthesizes the optimal sensor network in the face of disturbances or set point changes. Computational expense of the large-scale combinatorial optimization problem is significantly reduced by parallel computing and by using combination of three novel strategies: multi-rate sampling frequency, model order reduction, and use of an incumbent solution that enables early termination of evaluation of infeasible sensor sets. The developed algorithm is applied to an acid gas removal unit as part of an integrated gasification combined cycle power plant with carbon capture. Even though there are more than thousand process states and more than hundred candidate sensor locations, the optimal sensor network design problem for maximizing process efficiency could be solved within couple of hours for a given budget.},
doi = {10.1016/j.compchemeng.2016.01.018},
journal = {Computers and Chemical Engineering},
number = C,
volume = 89,
place = {United States},
year = {2016},
month = {3}
}