Milan Zlatkovikj
School of Business, Society and Engineering, Malardalen University, Vasteras, Sweden
Valentina Zaccaria
School of Business, Society and Engineering, Malardalen University, Vasteras, Sweden
Ioanna Aslanidou
School of Business, Society and Engineering, Malardalen University, Vasteras, Sweden
Konstantinos Kyprianidis
School of Business, Society and Engineering, Malardalen University, Vasteras, Sweden
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https://doi.org/10.3384/ecp20176107Published in: Proceedings of The 61st SIMS Conference on Simulation and Modelling SIMS 2020, September 22-24, Virtual Conference, Finland
Linköping Electronic Conference Proceedings 176:15, p. 107-115
Published: 2021-03-03
ISBN: 978-91-7929-731-2
ISSN: 1650-3686 (print), 1650-3740 (online)
Biomass fired boilers usage is increasing due to supportive policies and economic trends. Fluidized bed technology is identified as proper solution for lower quality fuels such as biomass. Moisture and heating value can vary significantly in biomass fuels. Without real-time information on their variation, they are a disturbance to the system. These disturbances affect the system steady state and decrease operational efficiency. Proper characterization of the disturbance enables the use of feed-forward control. Feed-forward makes use of the knowledge about the updated condition of the fuel and can act towards reducing the impact of the fuel on offsetting the system. Feed-forward model predictive control is proposed as new control strategy. Comparison is made between the existing control strategy and the new proposed solution. Control performance is evaluated on three process outputs, in three different scenarios. Adding feed-forward signal for fuel moisture improves control performance in both controllers, while ultimately feed-forward model predictive control shows the best performance in most comparison metrics.
biomass fuel, fuel moisture, model predictive control, feed-forward, plant control