Abstract
For a reliable assessment of energy consumption by the air conditioning system, data on the frequency of occurrence of combinations of temperature and enthalpy of outside air in the construction area is needed. The purpose of this article is to consider the influence of the detail of the probabilistic-statistical climate model on the results of calculating the consumption of heat, cold, and electricity by a direct-flow air conditioning system with a controlled cooling process serving office premises in Hanoi (Vietnam). To achieve this goal, the results of energy consumption calculations are considered in two versions: details of the climate model: the repeatability of combinations of climate parameters in option 1 is given for cells with a step of 2 °C, relative humidity of 5%, and in option 2 for cells with a step of 1 °C, relative humidity of 2.5%. The calculation results indicate a significant increase in the accuracy of calculations with a smaller step of the climate model.
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
Chua, K.J., Chou, S.K., Yang, W.M., Yan, J.: Achieving better energy-efficient air conditioning – a review of technologies and strategies. Appl. Energy 104, 87–104 (2013)
Oldewurtel, F., Sturzenegger, D., Morari, M.: Importance of occupancy information for building climate control. Appl. Energy 101, 521–532 (2012)
Afram, А., Janabi-Sharifi, F.: Review of modeling methods for HVAC systems. Appl. Therm. Eng. 67(1–2), 507–519 (2014)
Samarin, O.D., Lushin, K.I., Kirushok, D.A.: Energy-saving air handling circuit with indirect evaporative cooling in plate heat exchangers. Hous. Build. 1–2, 43–45 (2018). (in Russian)
Malyavina, Е.G., Kryuchkova, О.Y.: Analysis of annual power consumption by central air conditioning systems using the climatic data stochastic statistics model. In: Environmental engineering. 8-th International Conference, Vilnius, Lithuania, vol. 19–20, рp. 776–780 (2011)
Pshenichnikov, V.M.: Building heat and energy consumption management based on mathematical modeling. HVAC 8, 48–53 (2018). (in Russian)
Kostin, V.I., Rakova, E.А.: Constructive schemes of control systems of a microclimate of premises with the constant temperature of internal air. News High. Educ. Inst. Constr. 4, 59–66 (2018). (in Russian)
Kostin, V.I., Russkikh, E.Yu.: Calculation of expenses of cold on air conditioning systems of industrial buildings. HVAC 5, 18–21 (2012). (in Russian)
Arbatsky, A.A., Afonina, G.N.: Calculation of annual energy use by refrigeration centers. HVAC 6, 10–13 (2017). (in Russian)
TCVN 5687.2010: Ventilation, air conditioning - Design Standards Vietnam, Hanoi (2010) (in Vietnamese)
Chấn, T.N.: Air Conditioning. Building Publishing, Hanoi (2002). (in Vietnamese)
Van Lương, P.: Energy saving solution for a large air conditioning system. Vietnamese Association of Civil Environment, Hanoi (2015). (in Vietnamese)
Afram, А., Janabi-Sharifi, F.: Theory and applications of HVAC control systems – a review of model predictive control (MPC). Build. Environ. 72, 343–355 (2014)
Oldewurtel, F., Jones, C.N., Parisio, A., Morari, M.: Stochastic model predictive control for building climate control. IEEE Trans. Control Syst. Technol. 22(3), 1198–1205 (2013)
Malyavina, Е.G., Kryuchkova, О.Y., Kozlov, V.V.: Comparison of climate models for calculating energy consumption central air conditioning systems. Hous. Build. 6, 24–26 (2014). (in Russian)
Belova, E.M.: Central air conditioning systems in buildings. Euroclimate, Moscow (2006). (in Russian)
Malyavina, Е.G., Malikova, О.Y. Comparison of the completeness of the climate probability-statistic model and the reference year model. In: IOP Conference Series: Materials Science and Engineering, Moscow, vol. 365 (2018). https://doi.org/10.1088/1757-899X/365/2/022009
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
Malyavina, E., Malikova, O., Pham, V.L. (2020). Probabilistic-Statistical Model of Climate in Estimation of Energy Consumption by Air Conditioning Systems. In: Murgul, V., Pasetti, M. (eds) International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2018. EMMFT-2018 2018. Advances in Intelligent Systems and Computing, vol 982. Springer, Cham. https://doi.org/10.1007/978-3-030-19756-8_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-19756-8_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-19755-1
Online ISBN: 978-3-030-19756-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)