Abstract
The article studies the experience of automation of heating, ventilation, and air conditioning (HVAC) systems of buildings with regard to the technical capacities of the Internet of Things (IoT). Using the data from IoT devices maintains the set quality parameters throughout the entire operation period, which is achieved with the compensatory and predictive control algorithms. The objective of the research is to increase the HVAC control efficiency in smart buildings using the control system with the adaptation circuit, which proactively compensates any disturbances. The proper operation of the circuit requires accumulation of information of the venue during the operation period, which is used for building the transfer functions of the HVAC of the building. Continuous adaptation of the control system model to reality is a way to continuously optimize the adjustments of the regulation algorithm, ensuring effective operation of the local temperature regulation circuits. The capacities of the IoT controller-based control system and the generation of a compensatory-predictive control signal with the placement of the control algorithm in a “cloud” on a server are demonstrated with the indoor temperature control model. The simulation models of the indoor temperature changing processes are studied: the indoor temperature changing process model without a control system; model with a PI-regulator and disturbance compensation; the disturbance compensation model for the IoT controller-based control system. The structural and parametric identification of the model is carried out with the active experiment method #CSOC1120.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
White paper: “Green Intelligent buildings”. Mapping of companies and activities in the US within “smart” buildings. Innovation Centre Denmark “Silicon Valley”, Palo Alto, CA, USA (2014)
Wonga, J.K.W., Li, H., Wang, S.W.: Intelligent building research: a review. Autom. Constr. 14(1), 143–159 (2005)
Zhang, J., Seet, B.-C., Lie, T.T.: Building information modelling for smart built environments. Buildings 5(1), 100–115 (2015)
Hong, T., Feng, W., Lu, A., Xia, J., Yang, L., Shen, Q., Im, P., Bhandari, M.: Building Energy Monitoring and Analysis. Lawrence Berkeley National Laboratory, Berkeley (2013)
Kudzh, S.A., Tsvetkov, V.Y.: Netcentered control and cyper-physical systems. Educ. Res. Technol. 2(19), 86–91 (2017)
Tsvetkov, V.Y.: Distributed smart control. State Counsel. 1, 16–22 (2017)
Zhu, C., Leung, V.C.M., Shu, L., Ngai, E.C.-H.: Green Internet of Things for smart world. IEEE Access 3, 2151–2162 (2015)
Lü, X., Lu, T., Kibert, C.J., Viljanen, M.: A novel dynamic modeling approach for predicting building energy performance. Appl. Energy 114(C), 91–103 (2014)
Zhang, J., Seet, B.-C., Lie, T.T.: Building information modelling for smart built environments. Buildings 5(1), 100–115 (2015)
Strizhak, P.A., Morozov, M.N.: Mathematical modelling of building heating regime considering the solar radiation heat input. Tomsk Polytech. Univ. News Georesour. Eng. 326(8), 36–46 (2015)
Stepanov, V.M., Sergeeva, T.E.: Analysis of the buildings’ heat-mass-exchange process mathematic models for the development of an electromechanic system control inputs. Tula State Univ. News Tech. Sci. 12(2), 158–164 (2015)
Panferov, V.I., Anisimova, EYu., Nagornaya, A.N.: To the theory of mathematical modelling of the heating circuit of the buildings. South Ural State Univ. Newsl. 14, 128–131 (2006)
Faizrakhmanov, R.A., Frank, T., Kychkin, A.V., Fedorov, A.B.: Sustainable energy consumption control using the MY-JEVIS energy management data system. Russ. Electr. Eng. 82(11), 607–611 (2011)
Chivilikhin, D., Shalyto, A., Vyatkin, V.: Inferring automata logic from manual control scenarios: implementation in function blocks. In: Proceedings of the 13th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA 2015), Helsinki, Finland, pp. 307–312. IEEE (2015)
Kychkin, A.V.: Synthesizing a system for remote energy monitoring in manufacturing. Metallurgist 59(9–10), 752–760 (2016)
Lyakhomskii, A.V., Perfil’eva, E.N., Perfil’eva, E.N., Kychkin, A.V., Genrikh, N.A.: Software-hardware system of remote monitoring and analysis of the energy data. Russ. Electr. Eng. 86, 314–319 (2015)
Braga, L.C., Braga, A.R., Braga, C.M.A.: On the characterization and monitoring of building energy demand using statistical process control methodologies. Energy Build. 65, 205–219 (2013)
Kychkin, A.V., Mikriukov, G.P.: Applied data analysis in energy monitoring system. Probl. Energet. Reg. 2(31), 84–92 (2016)
Gubbi, J., et al.: Internet of Things (IoT): a vision, architectural elements, and future directions. Future Gener. Comput. Syst. 29(7), 1645–1660 (2013)
Kelly, S.D.T., Suryadevara, N.K., Mukhopadhyay, S.C.: Towards the implementation of IoT for environmental condition monitoring in homes. IEEE Sens. J. 13(10), 3846–3853 (2013)
Tao, F., et al.: IoT-based intelligent perception and access of manufacturing resource toward cloud manufacturing. IEEE Trans. Industr. Inf. 10(2), 1547–1557 (2014)
Menezes, A.C., Cripps, A., Bouchlaghem, D., Buswell, R.: Predicted vs. actual energy performance of non-domestic buildings: using post-occupancy evaluation data to reduce the performance gap. Appl. Energy 97, 355–364 (2012)
Mahdavi, A., Schuss, M., Suter, G., Metzger, A.S., Camara, S., Dervishi, S.: Recent advances in simulation-powered building systems control. In: Proceedings of the 7th International IBPSA Conference (Building Simulation 2009), Glasgow, UK, 27–30 July 2009, pp. 267–268 (2009)
Guan, L.: Preparation of future weather data to study the impact of climate change on buildings. Build. Environ. 44(4), 793–800 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Kychkin, A.V., Deryabin, A.I., Vikentyeva, O.L., Shestakova, L.V. (2020). Adaptive IoT-Based HVAC Control System for Smart Buildings. In: Silhavy, R. (eds) Applied Informatics and Cybernetics in Intelligent Systems. CSOC 2020. Advances in Intelligent Systems and Computing, vol 1226. Springer, Cham. https://doi.org/10.1007/978-3-030-51974-2_46
Download citation
DOI: https://doi.org/10.1007/978-3-030-51974-2_46
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-51973-5
Online ISBN: 978-3-030-51974-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)