Abstract
This paper presents a novel, effective method to handle critical sensor faults affecting a control system devised to operate a biomass boiler. In particular, the proposed method consists of integrating a data reconciliation algorithm in a model predictive control loop, so as to annihilate the effects of faults occurring in the sensor of the flue gas oxygen concentration, by feeding the controller with the reconciled measurements. Indeed, the oxygen content in flue gas is a key variable in control of biomass boilers due its close connections with both combustion efficiency and polluting emissions. The main benefit of including the data reconciliation algorithm in the loop, as a fault tolerant component, with respect to applying standard fault tolerant methods, is that controller reconfiguration is not required anymore, since the original controller operates on the restored, reliable data. The integrated data reconciliation–model predictive control (MPC) strategy has been validated by running simulations on a specific type of biomass boiler—the KPA Unicon BioGrate boiler.
Highlights
Renewable energy production is acknowledged worldwide as a key factor for sustainable growth.As for the energy sources used to replace the fossil fuel sources in power and heat production, local fuel supplies such as biomass fuel, which includes wood chips, bark, and sawdust, have relevant advantages for on-site industries and municipalities, such as, primarily, secure availability and price stability [1]
The model predictive control (MPC) strategy presented in this work is based on a more detailed model of the BioGrate boiler, which includes the dynamics of the oxygen content in the flue gas
This case study describes the effectiveness of the integrated data reconciliation-model predictive control (DR-MPC) system during an additive intermittent fault that occurs in the flue gas oxygen content sensor from 501 s to 5400 s
Summary
Renewable energy production is acknowledged worldwide as a key factor for sustainable growth. As to the effectiveness of the proposed data-reconciliation based fault-tolerant control scheme, this has been shown by integrating data reconciliation with an improved version of the model predictive control (MPC) strategy earlier developed in [2] for a specific type of biomass boiler—the KPA Unicon. The MPC strategy presented in this work is based on a more detailed model of the BioGrate boiler, which includes the dynamics of the oxygen content in the flue gas. The performance of the overall fault tolerant control system has been evaluated by running simulations on recorded data concerning the measurement of the oxygen content in the flue gas of an actual process under faulty conditions. Process and Control Description of the BioPower Combined Heat and Power Process
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
