MATHEMATICAL MODELING AND CONTROL SYSTEM OF NEARLY ZERO ENERGY BUILDING
Ildar A. Sultanguzin
sultanguzinia@mpei.ruNational Research University “MPEI”, Department of Industrial Thermal Engineering Systems (Russian Federation)
Hannes Toepfer
Technische Universität Ilmenau, Institute for Information Technology (Germany)
Ivan D. Kalyakin
National Research University “MPEI”, Department of Industrial Thermal Engineering Systems (Russian Federation)
Alexandr V. Govorin
National Research University “MPEI”, Department of Industrial Thermal Engineering Systems (Russian Federation)
Ekaterina V. Zhigulina
National Research University “MPEI”, Department of Industrial Thermal Engineering Systems (Russian Federation)
Sergey Yu. Kurzanov
National Research University “MPEI”, Department of Industrial Thermal Engineering Systems (Russian Federation)
Yury V. Yavorovsky
National Research University “MPEI”, Department of Industrial Thermal Engineering Systems (Russian Federation)
Abstract
The article examines three different kinds of mathematical model of nearly zero energy building. The first model enables to optimize the structure and the definition of key parameters of energy efficient building. The second model is necessary for passive house designing with renewable energy sources. The third model should be used for monitoring and control of energy supply system of nearly zero energy building through year every hour of winter and summer.
Keywords:
control system, mathematical model, monitoring, passive house, zero energy buildingReferences
Bacher P., Madsen H., Nielsen H.A., Perers B.: Short-term heat load forecasting for single family houses. Energy and Buildings 38/2006, 63–71.
Google Scholar
Bacher P., Madsen H., Nielsen H.A.: Online short-term solar power forecasting. Solar Energy 83/2009, 1772–1783.
Google Scholar
Cemesova A. et al.: PassivBIM: Enhancing interoperability between BIM and low energy design software. Automation in Construction 57/2015, 17–32.
Google Scholar
Fabrizio E. et al.: A model to design and optimize multi-energy systems in buildings at the design concept stage. Renewable Energy 35/2010, 644–655.
Google Scholar
Fan Ch. et al.: Temporal knowledge discovery in big BAS data for building energy management. Energy and Buildings 109/2015, 75–89.
Google Scholar
Feist V.: Die Hauptlagen nach der Projektierung der passiven Häuser. Konti Print, Moscow 2015.
Google Scholar
Halvgaard R. et al.: Model predictive control for a smart solar tank based on weather and consumption forecasts. Energy Procedia 30/2012, 270–278.
Google Scholar
Michailidis I.T. et al.: Proactive control for solar energy exploitation: A german high-inertia building case study. Applied Energy 155/2015, 409–420.
Google Scholar
Oti A.H. et al.: A framework for the utilization of Building Management System data in building information models for building design and operation. Automation in Construction 72/2016, 195–210.
Google Scholar
Sultanguzin I., Kalyakin I., Govorin A., et.al.: Optimization of the energy efficient active house. 3 Ingenieurtag 2016. Neseff-Netzwerktreffen 2016. Tagungsband. Branden-burgische Technische Universität. Cottbus-Senftenberg. 14-15 November 2016, 8–12.
Google Scholar
Sultanguzin I.A., Isaev M.V., Kurzanov S.Yu.: Optimizing the production of coke, coal chemicals, and steel on the basis of environmental and energy criteria. Metallurgist 54/2011, 600–607.
Google Scholar
Toepfer H., Goetze M., Chervakova E., Hutschenreuther T.: On the Use of Wireless Sensors Within a Traffic Monitoring System. Proceedings of the International Academic Forum AMO–SPITSE–NESEFF. Smolensk Publishing “Universum”, Moscow–Smolensk 2016.
Google Scholar
Torunski E. et al.: A review of smart environments for energy savings. Procedia Computer Science 10/2012, 205–214.
Google Scholar
Wang Y., Kuckelkorn J., Liu Y.: State of art review on methodologies for control strategies in low energy buildings in the period from 2006 to 2016. Energy & Buildings 147/2017, 27–40.
Google Scholar
Zhou K. et al.: Big data driven smart energy management: From big data to big insights. Renewable and Sustainable Energy Reviews 56/2016, 215–225.
Google Scholar
Authors
Ildar A. Sultanguzinsultanguzinia@mpei.ru
National Research University “MPEI”, Department of Industrial Thermal Engineering Systems Russian Federation
Authors
Hannes ToepferTechnische Universität Ilmenau, Institute for Information Technology Germany
Authors
Ivan D. KalyakinNational Research University “MPEI”, Department of Industrial Thermal Engineering Systems Russian Federation
Authors
Alexandr V. GovorinNational Research University “MPEI”, Department of Industrial Thermal Engineering Systems Russian Federation
Authors
Ekaterina V. ZhigulinaNational Research University “MPEI”, Department of Industrial Thermal Engineering Systems Russian Federation
Authors
Sergey Yu. KurzanovNational Research University “MPEI”, Department of Industrial Thermal Engineering Systems Russian Federation
Authors
Yury V. YavorovskyNational Research University “MPEI”, Department of Industrial Thermal Engineering Systems Russian Federation
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