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Predictive control of thermal Power Plants
Author(s) -
Aurora C.,
Magni L.,
Scattolini R.,
Colombo P.,
Pretolani F.,
Villa G.
Publication year - 2004
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.890
Subject(s) - flexibility (engineering) , model predictive control , thermal power station , computer science , documentation , control (management) , competition (biology) , power (physics) , control engineering , reliability engineering , engineering , operating system , electrical engineering , ecology , statistics , physics , mathematics , quantum mechanics , artificial intelligence , biology
This work presents the results of a project aimed at verifying the applicability of industrial model predictive control (MPC) to thermal Power Plants. The research is motivated by the need to improve the efficiency of power plants so as to cope with the high levels of competition induced by the deregulation of the energy market. A detailed plant simulator, already used for operators training and controllers tuning, is coupled to an industrial software package implementing the dynamic matrix control algorithm. The achieved results witness the great potentialities of MPC, with respect to classical decentralized schemes, in terms of economical savings, reduction of pollutants, improved flexibility, easier tuning and better documentation. Copyright © 2004 John Wiley & Sons, Ltd.