Energy Equipment and Systems

Energy Equipment and Systems

Indoor temperature and energy optimization using Energyplus and Taguchi method: A case study

Document Type : Research Paper

Authors
Mina Alafzadeh 1
Mitra Moubed 2
Samyar Haghighat 3
1 Department of Mechanical Engineering, Faculty of Engineering, Ardakan University, Ardakan, Iran
2 Department of Industrial Engineering, Faculty of Engineering, Ardakan University, Ardakan, Iran
3 TACwin Company, Tehran, Iran
10.22059/ees.2023.548622.1384
Abstract
Cooling system is in charge of a high percent of total energy consumption in buildings. Different cooling systems and devices have different effects on the cooling load and energy consumption. The main objective of this paper is to study the effects of floor and ceiling temperature in comparison with other parameters including location of air diffusers and application of insulation and sealant. On the other hand, hospitals are huge buildings with high energy requirements and systems compared to other buildings such as universities, schools and offices. In this paper the impacts of these different cooling parameters on the temperature and cooling load in a room of a hospital are studied using Design of Experiments (DOE) and the Taguchi method. The experiments are simulated in Energy Plus to achieve the comfort temperature in one hospital’s room in Iran during six months of spring and summer. Using different cooling systems such as chilled floor (during night to decrease the peak load during day) and ceiling in combination with air handling unit can provide people satisfaction while optimizing energy consumption. The results show that the location of inlet and outlet diffusers has the most effect while the chilled floor (when the other systems are off) has the less impact on reaching comfort temperature. The ranking of parameters and their interactions has been discussed through the paper.
Keywords
Taguchi Method
Cooling Load
Air Diffusers
Insulation
Sealant

Subjects

[1] Synnefa, A., M. Santamouris, and H. Akbari, Estimating the effect of using cool coatings on energy loads and thermal comfort in residential buildings in various climatic conditions. Energy and Buildings, 2007. 39(11): p. 1167-1174.
[2] Mui, K.W., et al., A hybrid simulation model to predict the cooling energy consumption for residential housing in Hong Kong. Energies, 2021. 14(16): p. 4850.
[3] Evins, R., et al., A case study exploring regulated energy use in domestic buildings using design-of-experiments and multi-objective optimisation. Building and Environment, 2012. 54: p. 126-136.
[4] Zhu, J., et al., Optimization method for building envelope design to minimize carbon emissions of building operational energy consumption using orthogonal experimental design (OED). Habitat International, 2013. 37: p. 148-154.
[5] Zahraee, S.M., et al., Application of design experiments to evaluate the effectiveness of climate factors on energy saving in green residential buildings. Jurnal Teknologi, 2014. 69(5).
[6] Wahid, F. and D.H. Kim, An Efficient Approach for Energy Consumption Optimization and Management in Residential Building Using Artificial Bee Colony and Fuzzy Logic. Mathematical Problems in Engineering, 2016. 2016(1): p. 9104735.
[7] Kim, W., Y. Jeon, and Y. Kim, Simulation-based optimization of an integrated daylighting and HVAC system using the design of experiments method. Applied energy, 2016. 162: p. 666-674.
[8] Pezeshki, Z., A. Soleimani, and A. Darabi, Taguchi method to determine the best location for cooling and heating appliances. Proceedings of the Institution of Civil Engineers - Energy, 2020. 173(1): p. 13-44.
[9] Ogunleye, O., R.M. Singh, and F. Cecinato, Assessing the thermal efficiency of energy tunnels using numerical methods and Taguchi statistical approach. Applied Thermal Engineering, 2021. 185: p. 116377.
[10] Abdullah, H.K. and H.Z. Alibaba, A Performance-Based Window Design and Evaluation Model for Naturally Ventilated Offices. Buildings, 2022. 12(8): p. 1141.
[11] Costa, N. and P. Fontes, Energy-Efficiency Assessment and Improvement—Experiments and Analysis Methods. Sustainability, 2020. 12(18): p. 7603.
[12] Fraley, S.A., et al. 14.1: Design of Experiments via Taguchi Methods-Orthogonal Arrays.
[13] Davis, R. and P. John, Application of Taguchi-Based Design of Experiments for Industrial Chemical Processes. 2018.