Verification of Energy Efficiency as a Function of the Control Mode of a Residential Heating System, Modelled in a MATLAB SIMULINK Environment
DOI:
https://doi.org/10.33038/jcegi.4850Keywords:
simulation, heat control, energy saving, optimizationAbstract
Efficient control of the heating system in residential buildings is of outstanding importance for energy efficiency, comfort, and emissions reduction. The use of mathematical modelling and simulation allows for the investigation and optimization of various heating control modes. During the study, we developed mathematical models to describe different control modes of the heating system in residential buildings. The most commonly used modes were constant setpoint control, variable setpoint control, weather-compensation control, and PID control. Among these, we compared the constant setpoint On/Off thermostat control with the variable setpoint control based on normal and reduced temperature time programs.
Based on the models, we analysed the effectiveness and energy-saving potential of these two different control modes. The simulations were conducted using meteorological measurement data. The results showed that the variable setpoint control leads to 8,4% energy saving with minimal or negligible decrease in comfort, thus ensuring lower emissions.
It can be concluded that through mathematical modelling and simulation, it is possible to conduct detailed examinations and comparisons of the heating system control modes in residential buildings. Based on the findings, designers and engineers can develop more efficient and sustainable heating solutions for residential buildings.
References
AKAN, A.P. – AKAN, A.E. (2021): Modeling on CO2 emissions via optimum insulation thickenss of residential buildings. Clean Technologies and Environmental Policy, 24, 949–967. https://doi.org/10.1007/s10098-021-02233-6
ALI, M. (2020): The PID comparsion simulation with SOSMF control and efficient indoor thermal comfort control in HVAC System. Student Conference on Research and Development/IEEE. elérhető: https://www.researchgate.net/publication/338386124 letöltés: 2023.07.25.
BALALI, Y. – CHONG, A. – BUSCH, A. – O’KEEFE, S.G. (2023): Energy modelling and control of building heating and cooling systems with data-driven and hybrid models-A review. Renewable and Sustainable Energy Reviews, 183. https://doi.org/10.1016/j.rser.2023.113496
BORODINECS, A. – ZEMITIS, J. – PALCIKOVSKIS, A. – ARDAVS, A. – LAVENDELIS E. (2023): Review of modern demand control solutions and technologies for HVAC operation. E3S Web of Conferences, 396, 02020. https://doi.org/10.1051/e3sconf/202339602020
FELIMBAN, A. – KNAACK, U. – KONSTANTINOU, T. (2023): Evaluating Savings Potentials Using Energy Retrofitting Measures for a Residential Building in Jeddah, KSA. Buildings, 13(7) 1645. https://doi.org/10.3390/buildings13071645
FUAD, A.A. – KHAN, S.U. – MYNUDDIN, M. (2023): Fuzzy Logic Control Method of HVAC Equipment for Optimization of Occupants’ Thermal Comfort in Apartment. Noble International Journal of Scientific Research, 7(1), 08–18. elérhető: www.napublisher.org letöltés: 2023.04.11.
GHABOUR, R. – JOSIMOVIC, L. – KORZENSZKY, P. (2021): Two Analytical Methods for Optimising Solar Process Heat System Used in a Pasteurising Plant. Applied Engineering Letters, 6(4), 166–174. https://doi.org/10.18485/aeletters.2021.6.4.4
GHABOUR, R. – KORZENSZKY, P. (2020): Mathematical modelling and experimentation of soy wax PCM solar tank using response surface method. Analecta Technica Szegedinensia, 14(2), 35–42. https://doi.org/10.14232/analecta.2020.2.35-42
GHABOUR, R. – KORZENSZKY, P. (2021): Effect of in series and in parallel flow heater configuration of solar heat system for industrial processes. Science, Technology and Innovation, 14(3-4), 18–26. https://doi.org/10.55225/sti.315
GHABOUR, R. – KORZENSZKY, P. (2022): Linear Model of DHW System Using Response Surface Method Approach. Technicki Vjesnik, 29(1), 66–72. https://doi.org/10.17559/TV-20201128095138
GHABOUR, R. – KORZENSZKY, P. (2023): Dynamic Modelling and Experimental Analysis of Tankless Solar Heat Process System for Preheating Water in the Food Industry. Acta Polytechnica Hungarica, 20(4), 65–83. https://doi.org/10.12700/APH.20.4.2023.4.4
HERMANUCZ, P. – BENÉCS, J. – BARÓTFI, I. (2022): Levegő hőforrású hőszivattyú leolvasztási ciklusának energetikai vizsgálata. Magyar Épületgépészet, 71(1–2), 7–12.
INTERNATIONAL ENERGY AGENCY (2018): A hat legnagyobb CO2 kibocsátó végfelhasználás Magyarországon 2017-ben elérhető: https://www.iea.org/ letöltés: 2023. 05.15.
KHAIRI, M. – JAAPAR, A. – YAHYA, Z. (2017): The application, benefits and challanges of retrofitting the existing buildings. Materials Science and Engineering 271, 012030. https://doi.org/10.1088/1757-899X/271/1/012030
MOON, H. – HYUN, C. – HONG, T. (2014): Prediction Model of CO2 Emission for Residential Buildings in South Korea. Journal of Management in Engineering, 30(3), 04014001 https://doi.org/10.1061/(ASCE)ME.1943-5479.0000228
MAWSON, V.J. – HUGHES, B.R. (2021): Coupling simulation with artificial neural networks for the optimisation of HVAC controls in manufacturing environments. Optimization and Engineering, 22, 103–119. https://doi.org/10.1007/s11081-020-09567-y
PALLONETTO, F. – ROSA, M.D. – FINN, D.P. (2020): Environmental and economic benefits of building retrofit measures for the residential sector by utilising sensor data and advanced calibrated models. Advanced in Building Energy Research, 16(1), 89–117. https://doi.org/10.1080/17512549.2020.1801504
PÁGER, S. – FÖLDI, L. – GÉCZI, G. (2022): Creation and validation of simplified mathematical model for residential building energy analysis in matlab environment. Mechanical Engineering Letters, 22, 26–42. elérhető: https://uni-mate.hu/documents/315606/3131614/MEL_2022_vol22.pdf
RICHTER, P. – ABIDA, A. (2022): HVAC control in buildings using neural network. Journal of Building Engineering, 65, 105558. https://doi.org/10.1016/j.jobe.2022.105558
Downloads
Published
Issue
Section
License
Copyright (c) 2023 Journal of Central European Green Innovation
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.