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Title: An intellignet controller for optimized sootblowing

Abstract

Efficiency losses of over 200 Btu/KWH have been attributed to sub-optimal control of sootblowers in coal-fired boilers, frequently accounting for over 80% of the controllable losses. For a 500 MW power plant, this translates into yearly costs of over $1 M. The primary impediment to sootblowing optimization to date has been the difficulty associated with modeling the relationship between sootblowing, and boiler efficiency. New advances in neural network technology now provide an attractive approach to address this issue. This paper presents results to date of a project currently under way at DHR Technologies, Inc. (DHR), George Washington University (GWU), and Baltimore Gas and Electric Company (BGE), with funding provided by the Department of Energy (DOE), to develop an Intelligent Controller for Optimized Sootblowing (ICOS). The ICOS system combines a neural network-based process model with an optimization algorithm to provide automated, optimized control of steam or compressed air sootblowers for fossil utility boilers. In Phase I of the project, the proposed optimization approach was tested and validated using data from BGE`s Brandon Shores Station. Phase I quantified the expected savings of the controller and verified the effectiveness of the proposed technical approach. In Phase II, the control algorithm will be incorporatedmore » into DHR`s TOPAZ{trademark} optimization system and interfaced with Brandon Shore`s Diamond Power sootblowing controller, and will be demonstrated and tested for closed-loop, optimal sootblowing control. The savings achieved through use of the ICOS controller during testing will also be quantified.« less

Authors:
; ;  [1]
  1. and others
Publication Date:
Research Org.:
Electric Power Research Inst. (EPRI), Palo Alto, CA (United States); Encor-America, Inc., Mountain View, CA (United States)
OSTI Identifier:
269614
Report Number(s):
EPRI-TR-106529; CONF-960524-
TRN: 96:003583-0027
Resource Type:
Technical Report
Resource Relation:
Conference: Heat-rate improvement conference, Dallas, TX (United States), 22-24 May 1996; Other Information: PBD: May 1996; Related Information: Is Part Of Proceedings: 1996 heat rate improvement conference; Diaz-Tous, I.A. [ed.] [Encor-America, Inc., Mountain View, CA (United States)]; PB: 568 p.
Country of Publication:
United States
Language:
English
Subject:
20 FOSSIL-FUELED POWER PLANTS; BOILERS; CLEANING; FOSSIL-FUEL POWER PLANTS; ON-LINE CONTROL SYSTEMS; THERMAL EFFICIENCY; SOOT; NEURAL NETWORKS; ALGORITHMS; DIAGRAMS

Citation Formats

Baldridge, D, Bangham, M, and Gratcheva, K. An intellignet controller for optimized sootblowing. United States: N. p., 1996. Web.
Baldridge, D, Bangham, M, & Gratcheva, K. An intellignet controller for optimized sootblowing. United States.
Baldridge, D, Bangham, M, and Gratcheva, K. 1996. "An intellignet controller for optimized sootblowing". United States.
@article{osti_269614,
title = {An intellignet controller for optimized sootblowing},
author = {Baldridge, D and Bangham, M and Gratcheva, K},
abstractNote = {Efficiency losses of over 200 Btu/KWH have been attributed to sub-optimal control of sootblowers in coal-fired boilers, frequently accounting for over 80% of the controllable losses. For a 500 MW power plant, this translates into yearly costs of over $1 M. The primary impediment to sootblowing optimization to date has been the difficulty associated with modeling the relationship between sootblowing, and boiler efficiency. New advances in neural network technology now provide an attractive approach to address this issue. This paper presents results to date of a project currently under way at DHR Technologies, Inc. (DHR), George Washington University (GWU), and Baltimore Gas and Electric Company (BGE), with funding provided by the Department of Energy (DOE), to develop an Intelligent Controller for Optimized Sootblowing (ICOS). The ICOS system combines a neural network-based process model with an optimization algorithm to provide automated, optimized control of steam or compressed air sootblowers for fossil utility boilers. In Phase I of the project, the proposed optimization approach was tested and validated using data from BGE`s Brandon Shores Station. Phase I quantified the expected savings of the controller and verified the effectiveness of the proposed technical approach. In Phase II, the control algorithm will be incorporated into DHR`s TOPAZ{trademark} optimization system and interfaced with Brandon Shore`s Diamond Power sootblowing controller, and will be demonstrated and tested for closed-loop, optimal sootblowing control. The savings achieved through use of the ICOS controller during testing will also be quantified.},
doi = {},
url = {https://www.osti.gov/biblio/269614}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed May 01 00:00:00 EDT 1996},
month = {Wed May 01 00:00:00 EDT 1996}
}

Technical Report:
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