CONTROL OF ENERGY EFFICIENCY IN INDUSTRY AND HOUSING AND COMMUNAL SERVICES
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UDC 62-52/551.4, 628.87
DOI: 10.14529/ctcr150305
Building Thermal Performance Feed-Forward Control
V.V. Abdullin, South Ural State University, Chelyabinsk, Russian Federation, vildan@ait.susu.ac.ru
Abstract
This paper proposes an implementation of method of heating feed-forward control system for multi-storey buildings. The proposed structure incorporates baseline control loop that controls heating power depending on the key perturbing factor – outdoor air temperature and adjusting control loop implementing feed-forward control based on indoor air temperature inverse dynamics model. The suggested model structure enables real-time assessment of the impact of unmeasurable perturbing factors on indoor air temperature, along with distinguishing between fast and slow processes occurring within the system. To measure current indoor air temperature values, the authors used a distributed field-level sensor network. The estimation of generalized temperature perturbation was performed using predicting ability of exponential smoothing. The paper also contains the actual results obtained by deployment of the suggested heating control system in the university academic building. The results obtained demonstrate the reducing of overall energy consumption by building heating system, at the same time increasing the comfort level of the building.
Keywords
building thermal performance, feed-forward control, inverse dynamics model, heating of buildings, automated heat station
References
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6. Abdullin V.V., Shnayder D.A., Basalaev A.A. Building Heating Feed-Forward Control Based on Indoor Air Temperature Inverse Dynamics Model. Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering and Computer Science 2014, WCECS 2014, 22–24 October, 2014, San Francisco, CA, USA, pp. 886–892.
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8. Abdullin V.V., Shnayder D.A., Kazarinov L.S. Identification of Multistorey Building’s Thermal Performance Based on Exponential Filtering. Transactions on Engineering Technologies. – Springer Netherlands, 2014. pp. 501–512. DOI: 10.1007/978-94-017-8832-8_36
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2. Salmerón J.M., Álvarez S., Molina J.L., Ruiz A., Sánchez F.J. Tightening the Energy Consumptions of Buildings Depending on their Typology and on Climate Severity Indexes. Energy and Buildings, 2013, vol. 58, pp. 372–377. DOI: 10.1016/j.enbuild.2012.09.039
3. Salsbury T., Mhaskar P., Qin S.J. Predictive Control Methods to Improve Energy Efficiency and Reduce Demand in Buildings. Computers and Chemical Engineering, 2013, vol. 51, pp. 77–85. DOI: 10.1016/j.compchemeng.2012.08.003
4. Shaikh P.H., Nor N.M., Nallagownden P., Elamvazuthi I., Ibrahim T. A Review on Optimized Control Systems for Building Energy and Comfort Management of Smart Sustainable Buildings. Renewable and Sustainable Energy Reviews, 2014, vol. 34, pp. 409–429. DOI: 10.1016/j.rser.2014.03.027
5. Oldewurtel F., Parisio A., Jones C., Morari M., Gyalistras D., Gwerder M., et al. Energy Efficient Building Climate Control Using Stochastic Model Predictive Control and Weather Predictions. Proceedings of American Control Conference 2010, ACC 2010, 30 June–2 July, 2010, Baltimore, MD, USA, pp. 5100–5105. DOI: 10.1109/ACC.2010.5530680
6. Abdullin V.V., Shnayder D.A., Basalaev A.A. Building Heating Feed-Forward Control Based on Indoor Air Temperature Inverse Dynamics Model. Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering and Computer Science 2014, WCECS 2014, 22–24 October, 2014, San Francisco, CA, USA, pp. 886–892.
7. Abdullin V.V., Shnayder D.A., Kazarinov L.S. Method of Building Thermal Performance Identification Based on Exponential Filtration. Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2013, WCE 2013, 3–5 July, 2013, London, U.K., pp. 2226–2230.
8. Abdullin V.V., Shnayder D.A., Kazarinov L.S. Identification of Multistorey Building’s Thermal Performance Based on Exponential Filtering. Transactions on Engineering Technologies. – Springer Netherlands, 2014. pp. 501–512. DOI: 10.1007/978-94-017-8832-8_36
9. Sokolov E.Ya. Teplofikatsiya i teplovye seti (Central Heating and Heating Networks). Moscow, MEI, 2001. (in Russ.)
10. Gorelik S.I., Kazarinov L.S. (Prediction of Random Oscillatory Processes on the Basis of the Exponential Smoothing Method). Automation and Remote Control, 1994, 55:10, pp. 1413–1419. (in Russ.)
11. Shnayder D.A., Shishkin M.V. (Adaptive Controller for Building Heating Systems Applying Artificial Neural Network). Automatics and Control in Technical Systems, Edited Book. Chelyabinsk, South Ural State University press, 2000, pp. 131–134. (in Russ.)
12. Shnayder D.A., Abdullin V.V. A WSN-based System for Heat Allocating in Multiflat Buildings. 2013 36th International Conference on Telecommunications and Signal Processing Proceedings, TSP 2013, 2–4 July, 2013, Rome, Italy, Article number 6613915, pp. 181–185. DOI: 10.1109/TSP.2013.6613915
Source
Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control, Radio Electronics, 2015, vol. 15, no. 3, pp. 33-39. (in Russ.) (Management of Engineering Systems)