Building energy efficiency improvement using multi-objective optimization for heating and cooling VRF thermostat setpoints

¹ LMAID laboratory, Rabat National School of Mines, 10070 Rabat, Morocco.
² Green Energy Park (IRESEN, UM6P), 43150 Benguerir, Morocco.
³ Faculty of Science and Technology, Abdelmalek Essaadi University, B.P. 416 Tangier, Tétouan, Morocco.
⁴ Laboratory (LaMEE), Faculty of Sciences Semlalia, Cadi Ayyad University, 40000 Marrakesh, Morocco.
⁵ Univ Lyon, ENTPE, Ecole Centrale de Lyon, CNRS, LTDS, UMR 5513, 69518 Vaulx-en-Velin Cedex, France.
⁶ Institute of Energy Systems Technology, Offenburg University of Applied Sciences, Offenburg, Germany.

^* Corresponding author: niima.essakali@enim.ac.ma / es-sakali@greenenergypark.ma

Abstract

The variable refrigerant flow system is one of the best heating, ventilation, and air conditioning systems (HVAC) thanks to its ability to provide thermal comfort inside buildings. But, at the same time, these systems are considered one of the most energy-consuming systems in the building sector. Thus, it is crucial to well size the system according to the building’s cooling and heating needs and the indoor temperature fluctuations. Although many researchers have studied the optimization of the building energy performance considering heating or cooling needs, using air handling units, radiant floor heating, and direct expansion valves, few studies have considered the use of multi-objective optimization using only the thermostat setpoints of VRF systems for both cooling and heating needs. Thus, the main aim of this study is to conduct a sensitivity analysis and a multi-objective optimization strategy for a residential building containing a variable refrigerant flow system, to evaluate the effect of the building performance on energy consumption and improve the building energy efficiency. The numerical model was based on the EnergyPlus, jEPlus, and jEPlus+EA simulation engines. The approach used in this paper has allowed us to reach significant quantitative energy saving by varying the cooling and heating setpoints and scheduling scenarios. It should be stressed that this approach could be applied to several HVAC systems to reduce energy-building consumption.