Electrical energy consumption and utilization time analysis of hospital departments and large scale medical equipment

Abstract Predicting the loads of electrical devices is an important part of modeling the energy flows in buildings. In non-residential buildings these loads can have a significant impact on heating and cooling requirements. In the case of hospitals this holds true particularly for areas directly connected to diagnostics and medical treatment. Even though the amount of information concerning these loads has increased in recent years, detailed information based on measured data remains scarce. Thus, within this paper over 20,000 h of measured data for operating theaters, intensive care units, examination and treatment rooms as well as large scale medical equipment are analyzed and evaluated. The used methodology allows for the determination of area-specific operating hours and a prediction of time-dependent electrical loads in different hospital departments. It was found that a differentiation of weekdays and weekend days is not appropriate for intensive care units, while the examined operating suites show surprisingly strong similarities with regular “office hours” within the assessed hospital. The presented values extend findings from other recent studies in this field and give a more detailed separation of individual contributions from lighting and different classes of medical equipment.

[1]  A. Carrico,et al.  Motivating energy conservation in the workplace: An evaluation of the use of group-level feedback and peer education , 2011 .

[2]  Dejan Mumovic,et al.  Original Article/ResearchA comparative study of benchmarking approaches for non-domestic buildings: Part 1 – Top-down approach , 2013 .

[3]  William Chung,et al.  Review of building energy-use performance benchmarking methodologies , 2011 .

[4]  Martin Kaltschmitt,et al.  Electricity consumption of medical plug loads in hospital laboratories: Identification, evaluation, prediction and verification , 2015 .

[5]  J. D. Chen,et al.  ENERY COST AND CONSUMPTION IN A LARGE ACUTE HOSPITAL , 2004 .

[6]  Piljae Im,et al.  Comparison of building energy use data between the United States and China , 2014, Energy and Buildings.

[7]  Sandhya Patidar,et al.  Understanding the energy consumption and occupancy of a multi-purpose academic building , 2015 .

[8]  P. Torcellini,et al.  Large Hospital 50% Energy Savings: Technical Support Document , 2010 .

[9]  Jared A. Linebach,et al.  Nonparametric Statistics for Applied Research , 2013 .

[10]  Nelson Fumo,et al.  A review on the basics of building energy estimation , 2014 .

[11]  Francisco Jesús Martínez-Murcia,et al.  Computer Aided Diagnosis tool for Alzheimer's Disease based on Mann-Whitney-Wilcoxon U-Test , 2012, Expert Syst. Appl..

[12]  Lee Siew Eang,et al.  Benchmarking energy use and greenhouse gas emissions in Singapore's hotel industry , 2010 .

[13]  T. Agami Reddy,et al.  Applied Data Analysis and Modeling for Energy Engineers and Scientists , 2011 .

[14]  Deuk-Woo Kim,et al.  Difficulties and limitations in performance simulation of a double skin faade with EnergyPlus , 2011 .

[15]  Jyotirmay Mathur,et al.  Potential of energy savings through implementation of Energy Conservation Building Code in Jaipur city, India , 2013 .

[16]  Patxi Hernandez,et al.  Energy demands and potential savings in European office buildings: Case studies based on EnergyPlus simulations , 2013 .

[17]  Tarald Rohde,et al.  Equipment and Energy Usage in a Large Teaching Hospital in Norway. , 2015, Journal of healthcare engineering.

[18]  Dirk Saelens,et al.  Assessment of approaches for modeling louver shading devices in building energy simulation programs , 2013 .

[19]  Luis Pérez-Lombard,et al.  A review on buildings energy consumption information , 2008 .

[20]  M. Hasanuzzaman,et al.  An end-use energy analysis in a Malaysian public hospital , 2010 .

[21]  A. Wright,et al.  Benchmarking acute hospitals: Composite electricity targets based on departmental consumption intensities? , 2016 .

[22]  Qiang Zhang,et al.  Model-based benchmarking with application to laboratory buildings , 2002 .

[23]  Mo Chung,et al.  Comparison of building energy demand for hotels, hospitals, and offices in Korea , 2015 .

[24]  Laurie Thorp,et al.  Energy conservation attitudes, knowledge, and behaviors in science laboratories , 2012 .

[25]  Frédéric Magoulès,et al.  A review on the prediction of building energy consumption , 2012 .

[26]  S. Chirarattananon,et al.  Development of Energy Conservation Programs for Commercial Buildings based on Assessed Energy Saving Potentials , 2011 .

[27]  Ruchi Choudhary,et al.  Energy analysis of the non-domestic building stock of Greater London , 2012 .

[28]  Herman P. Wijnand,et al.  Mann-Whitney/Wilcoxon's nonparametric cumulative probability distribution , 2000, Comput. Methods Programs Biomed..

[29]  Tony Roskilly,et al.  This Work Is Licensed under a Creative Commons Attribution 4.0 International License Royapoor M, Roskilly T. Building Model Calibration Using Energy and Environmental Data. Energy and Buildings Building Model Calibration Using Energy and Environmental Data Keywords: Model Calibration Measured Energy , 2022 .