Towards data-driven NARX ANN simulation for optimal control of the flue gas desulphurization for coal power plants
Authors:
- Dominika Cywicka,
- Agnieszka Jakóbik
Abstract
This paper presents the ANN-based algorithm for data-driven optimal control of desulfurization of the flue gases from Coal Power Plants. We have proposed the NARX recurrent neural network with experimentally selected feedback connection length as the black box model for the first stage of the control process. Then simple brute force algorithm was used to find the optimal level of the reagent added into the system to keep the SOX concentration outlet below the assumed level. This procedure was designed for a known level of SOX concentration inlet. The proposed approach was tested on real data collected from the selected Coal Power Plant in Poland. The simulation that was made confirms that such an approach is effective for coal power plants to increase their energy efficiency and meet the appropriate environmental standards.
- Record ID
- CUTce7a105b80c34afba2af694f23eacd19
- Publication categories
- ; ;
- Author
- Pages
- 562-567
- Other elements of collation
- schem.; tab.; wykr.; Bibliografia (na s.) - 566-567; Bibliografia (liczba pozycji) - 17; Oznaczenie streszczenia - Abstr.
- Substantive notes
- Wydaw. wg cop.
- Miejsce wyd. wg siedziby wydaw.
- Punktacja MNiSW/MEiN (rozdział) - 5
- Book
- Vicario Enrico, Enrico Vicario Bandinelli Romeo, Romeo Bandinelli Fani Virginia Virginia Fani [et al.] (eds.): ECMS 2023 : proceedings of the 37th ECMS International Conference on Modelling and Simulation, June 20th – June 23rd, 2023 Florence, Italy, European Conference for Modelling and Simulation, no. Vol. 37, Iss. 1, 2023, Caserta, ECMS, ISBN 978-3-937436-80-7 (Print)
- Keywords in English
- SOX absorption, data-driven modeling, and simulation, semi-dry gas desulfurization, optimal control, artificial neural network
- URL
- https://www.scs-europe.net/dlib/dl-index.htm Opening in a new tab
- Language
- eng (en) English
- License
- Score (nominal)
- 5
- Score source
- publisherList
- Score
- Additional fields
- Indeksowana w: CORE
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUTce7a105b80c34afba2af694f23eacd19/
- URN
urn:pkr-prod:CUTce7a105b80c34afba2af694f23eacd19
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.