Many advanced systems and data analysis methods are introduced into building science to realize the building automation and smart buildings. They are highly dependent on the information and data obtained from building sensor networks. In this technical flow, it is considerably important to understand the impacts of sensor errors on building energy systems, including Heating, Ventilation, Air-conditioning, and Refrigeration (HVACR), and mechanisms behind that in developing the reliable sensing environments and applying sensing technologies. Especially, temperature sensor errors have the great impacts on the system control and the application performance connected with the building systems; However, it is more challenging to calibrate the erroneous temperature sensors using a recent novel sensor calibration method (virtual in-situ sensor calibration). Nevertheless, few studies have concentrated on the impacts of temperature sensor errors through HVACR systems and they still lack the quantitative results and the understanding of how the temperature errors affect building energy performance and thermal comfort in the previous studies. Thus, this study investigates and characterizes the various impacts of temperature errors in HVACR using building energy simulation with the individual and combined error cases. The analysis includes the changes in the energy consumptions, system operation, system performance, and occupant unmet set-point hours by error location and error size.