Model predictive control for an industrial coal pulveriser
by Vini Dadiala; Jignesh Patel; Jayesh Barve
International Journal of Modelling, Identification and Control (IJMIC), Vol. 36, No. 4, 2020

Abstract: The coal-pulveriser/coal-mill is an important subsystem upstream of boilers in coal-based thermal power plants. The efficient boiler operations demand optimum combustion-air to coal-fuel ratio (AFR). In fact, portion of (preheated) combustion-air called primary-air, passes through coal-mill and carries pulverised coal to the boiler. The safe, efficient coal-mill operation is important and requires - safe temperature control of primary air-coal mixture inside/outlet of mill; optimum primary air-to-fuel ratio (pAFR); and swift tracking of coal-flowrate setpoints to cater for variable power-load demands. In this paper, a multivariable Model Predictive Control (MPC) scheme is proposed for specific industrial coal-mill. Also, simulation study is performed using validated industrial coal-mill model, and performance of MPC is compared with two other control schemes - industrial 2PI, and prior published 3PI with selective control. The MPC outperforms the other two control schemes and provides better control performance; well-respects coal-mill operational constraints; and improves pAFR.

Online publication date: Thu, 09-Sep-2021

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