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Titolo:
A novel performance monitoring strategy for economical thermal power plantoperation
Autore:
Prasad, G; Swidenbank, E; Hogg, BW;
Indirizzi:
Queens Univ Belfast, Dept Elect & Elect Engn, Belfast BT9 5AH, Antrim, North Ireland Queens Univ Belfast Belfast Antrim North Ireland BT9 5AH m, North Ireland
Titolo Testata:
IEEE TRANSACTIONS ON ENERGY CONVERSION
fascicolo: 3, volume: 14, anno: 1999,
pagine: 802 - 809
SICI:
0885-8969(199909)14:3<802:ANPMSF>2.0.ZU;2-B
Fonte:
ISI
Lingua:
ENG
Soggetto:
SYSTEM;
Keywords:
performance monitoring; efficiency models; thermal power plant; neural networks;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
10
Recensione:
Indirizzi per estratti:
Indirizzo: Prasad, G Queens Univ Belfast, Dept Elect & Elect Engn, Ashby Bldg, Belfast BT9 5AH,Antrim, North Ireland Queens Univ Belfast Ashby Bldg Belfast Antrim North Ireland BT9 5AH
Citazione:
G. Prasad et al., "A novel performance monitoring strategy for economical thermal power plantoperation", IEEE EN CON, 14(3), 1999, pp. 802-809

Abstract

A need-based integrated performance monitoring strategy is proposed to economize the operation of a thermal power plant, exploiting the immensely powerful resources of newly retrofitted modern Distributed Control System (DCS). After reviewing the performance monitoring practice of a typical 200 MW oil/gas fired thermal power plant at Ballylumford, N. Ireland, the paper analyses its shortcomings and then suggests remedial measures through the proposed strategy. A simulation of this plant has been used for investigation purposes. The twin key aspects of performance monitoring, i.e, monitoring of performance indices and controllable parameters, are addressed in more effective and novel ways. The achievable best efficiency values of plant components, needed for comparative performance evaluation, are shown to be morereliably and accurately obtainable through neural network performance models. A method based on histogram plots is shown to be highly effective in monitoring the performance of plant controllers in reducing the variability of plant variables and then modifying the set-points to improve the thermal performance of the plant.

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Documento generato il 04/04/20 alle ore 02:45:41