DocumentCode :
2310736
Title :
On-line optimization and monitoring of power plant performance through machine learning techniques
Author :
Swidenbank, E. ; Garcia, JA ; Flynn, D. ; Rapun, JL
Author_Institution :
Queen´´s Univ., Belfast, UK
Volume :
1
fYear :
1998
fDate :
1-4 Sep 1998
Firstpage :
257
Abstract :
This paper describes TOPGEN, a collaborative project for the demonstration of research results in the field of advanced control and optimization of a power plant. The project is partially funded by the European ESPRIT programme. In TOPGEN, several related technologies are being jointly tested on a 200 MW generating unit of Ballylumford Power Station, Northern Ireland. The objective is to provide operational and engineering recommendations for plant adjustments, in order to achieve performance improvements, during steady-state and fault-free conditions, given a set of exploitation constraints. Thus, the expected result is a software system, fully installed at Ballylumford Power Plant, which will improve the performance of the plant, reducing the amount of fuel necessary to obtain the electrical power required. This system will work online, continuously receiving data from the process
Keywords :
power station control; 200 MW; Ballylumford Power Station; ESPRIT programme; Northern Ireland; TOPGEN; UK; collaborative project; exploitation constraints; fault-free conditions; generating unit; machine learning techniques; online monitoring; online optimization; plant adjustments; power plant performance; steady-state conditions;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Control '98. UKACC International Conference on (Conf. Publ. No. 455)
Conference_Location :
Swansea
ISSN :
0537-9989
Print_ISBN :
0-85296-708-X
Type :
conf
DOI :
10.1049/cp:19980237
Filename :
727918
Link To Document :
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