• 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