Plant-Wide Physical Model-Based Control for a Thermal Power Plant

G Prasad, GW Irwin, E Swidenbank, BW Hogg

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

This paper reports the development of a constrained, non-linear physical model-based, predictive control (NPMPC) strategy for improved plant-wide control of a thermal power plant. The proposed strategy makes use of successive linearisation and extended Kalman filtering (EKF) to obtain a linear state-space model. The linear model and a quadratic programming routine are then used to design a constrained long-range predictive control routine. The proposed approach places major emphasis on better disturbance modeling based on a physical plant model. The paper discusses how this approach results into selection of a specific set of model parameters for on-line estimation to account for time-varying system characteristics resulting from major system disturbances and ageing. A plant model with 14 non-linear ODEs, simulating the dominant characteristics of a 200 MW oil-fired power plant at Ballylumford, N. Ireland, has been used to test the control strategy. The simulation results demonstrate that the constrained NPMPC controller provides significantly faster disturbance rejection with realistic rates of changes in manipulated variables during large system disturbances and extremely high rate of load changes. Results also demonstrate that the constrained algorithm provides a fault-tolerant capability to the controller, while satisfying the system constraints for economical plant operation.
LanguageEnglish
Title of host publicationUnknown Host Publication
Pages4631-4636
Number of pages6
DOIs
Publication statusPublished - Dec 1999
Event38th IEEE Conference on Decision and Control (CDC), December 7-10, Phoenix, Arizona, USA - Phoenix, Arizona, USA
Duration: 1 Dec 1999 → …

Conference

Conference38th IEEE Conference on Decision and Control (CDC), December 7-10, Phoenix, Arizona, USA
Period1/12/99 → …

Fingerprint

Power plants
Controllers
Disturbance rejection
Time varying systems
Quadratic programming
Hot Temperature
Linearization
Aging of materials

Cite this

Prasad, G., Irwin, GW., Swidenbank, E., & Hogg, BW. (1999). Plant-Wide Physical Model-Based Control for a Thermal Power Plant. In Unknown Host Publication (pp. 4631-4636) https://doi.org/10.1109/CDC.1999.833273
Prasad, G ; Irwin, GW ; Swidenbank, E ; Hogg, BW. / Plant-Wide Physical Model-Based Control for a Thermal Power Plant. Unknown Host Publication. 1999. pp. 4631-4636
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Prasad, G, Irwin, GW, Swidenbank, E & Hogg, BW 1999, Plant-Wide Physical Model-Based Control for a Thermal Power Plant. in Unknown Host Publication. pp. 4631-4636, 38th IEEE Conference on Decision and Control (CDC), December 7-10, Phoenix, Arizona, USA, 1/12/99. https://doi.org/10.1109/CDC.1999.833273

Plant-Wide Physical Model-Based Control for a Thermal Power Plant. / Prasad, G; Irwin, GW; Swidenbank, E; Hogg, BW.

Unknown Host Publication. 1999. p. 4631-4636.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - This paper reports the development of a constrained, non-linear physical model-based, predictive control (NPMPC) strategy for improved plant-wide control of a thermal power plant. The proposed strategy makes use of successive linearisation and extended Kalman filtering (EKF) to obtain a linear state-space model. The linear model and a quadratic programming routine are then used to design a constrained long-range predictive control routine. The proposed approach places major emphasis on better disturbance modeling based on a physical plant model. The paper discusses how this approach results into selection of a specific set of model parameters for on-line estimation to account for time-varying system characteristics resulting from major system disturbances and ageing. A plant model with 14 non-linear ODEs, simulating the dominant characteristics of a 200 MW oil-fired power plant at Ballylumford, N. Ireland, has been used to test the control strategy. The simulation results demonstrate that the constrained NPMPC controller provides significantly faster disturbance rejection with realistic rates of changes in manipulated variables during large system disturbances and extremely high rate of load changes. Results also demonstrate that the constrained algorithm provides a fault-tolerant capability to the controller, while satisfying the system constraints for economical plant operation.

AB - This paper reports the development of a constrained, non-linear physical model-based, predictive control (NPMPC) strategy for improved plant-wide control of a thermal power plant. The proposed strategy makes use of successive linearisation and extended Kalman filtering (EKF) to obtain a linear state-space model. The linear model and a quadratic programming routine are then used to design a constrained long-range predictive control routine. The proposed approach places major emphasis on better disturbance modeling based on a physical plant model. The paper discusses how this approach results into selection of a specific set of model parameters for on-line estimation to account for time-varying system characteristics resulting from major system disturbances and ageing. A plant model with 14 non-linear ODEs, simulating the dominant characteristics of a 200 MW oil-fired power plant at Ballylumford, N. Ireland, has been used to test the control strategy. The simulation results demonstrate that the constrained NPMPC controller provides significantly faster disturbance rejection with realistic rates of changes in manipulated variables during large system disturbances and extremely high rate of load changes. Results also demonstrate that the constrained algorithm provides a fault-tolerant capability to the controller, while satisfying the system constraints for economical plant operation.

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Prasad G, Irwin GW, Swidenbank E, Hogg BW. Plant-Wide Physical Model-Based Control for a Thermal Power Plant. In Unknown Host Publication. 1999. p. 4631-4636 https://doi.org/10.1109/CDC.1999.833273