Using occupant interaction with advanced lighting systems to understand opportunities for energy optimization: Control data from a hospital NICU
Introduction
A recent report published by the U.S. Department of Energy [2] predicts that between 2017 and 2035 the possible total cumulative energy savings from light-emitting diode (LED) lighting systems is 78 quadrillion BTUs. This is comparable to the annual energy consumption of 773 million U.S. households and equates to approximately $890 billion. These savings assume that adoption of advanced and connected lighting systems continues to increase through at least 2035, with connected lighting accounting for 12% in 2035, while the report also acknowledges the uncertainty of lighting controls assumptions. An advanced lighting system is considered to incorporate lighting controls with LED luminaires, and may also include additional features such as tunable lighting (variable spectrum and intensity), as well as occupancy sensors.
As noted by Gunay et al. [4], occupant behavior accounts for considerable uncertainty in building energy use and understanding occupant behavior helps address this uncertainty. Occupants adapt a space to suit their needs, often with minimal consideration of energy-conserving measures. This is commonly true in healthcare applications, where the top priority is patient care. Additionally, in hospital patient rooms the space is typically unfamiliar for the patients and families. The length of stay is relatively short compared to other spaces such as residential homes and offices, where individuals also often can control the environment.
Although there is much in the built environment literature about adaptive thermal comfort [7], and ASHRAE has a thermal comfort model [1], there is no such occupant comfort model in lighting. Additionally, these heating, ventilation, and air conditioning (HVAC) comfort models assume a certain number of occupants will be left dissatisfied, while the hope with advanced lighting systems is that occupants are able to adjust the lighting for their individual visual needs and preferences.
There have been several review studies related to electric lighting controls [3], [5], but these studies occurred before the widespread market adoption of LEDs that are easier to control than incumbent lighting technology. Guo et al. [5] acknowledged their work was a prelude to sensor networks as part of building management, also noting that “higher savings might be possible, but only after professional tuning [light level] and commissioning, which rarely occurs.” Commissioning continues to be a critical step in achieving the energy and occupant benefits of advanced lighting systems that are often claimed, yet is still too often overlooked. Tunable lighting systems with individual luminaires that can be adjusted to vary intensity and spectrum require additional time because the intensity and spectrum of each luminaire needs to be verified. If the tunable lighting is programmed to change throughout the day, then this verification is required for each programmed scene.
With the increasing availability of data, there is more opportunity to use that data for commissioning, while also providing insights into occupant behavior and preference that can further system optimization after occupancy and inform design practice. Safranek and Irvin [8] monitored occupant interaction with a lighting control system installed as a pilot in three elementary school classrooms, documenting over 6 weeks the frequency that specific buttons were selected on lighting control stations. The collected data showed that the teachers regularly utilized the full functionality of the system through preset and custom control of lighting color and intensity. Observed control patterns and preferences were unique to each teacher, remaining consistent over the monitoring period. The data revealed opportunities for further system optimization, making the preferred light settings more accessible by potentially reprogramming the control keypads or providing additional training for the teachers. To the authors’ knowledge, there are no comparable long-term studies of documented occupant interaction with lighting control systems in other facility types, including patient rooms.
This paper focuses on the use of lighting system control data to understand how occupants are using a new tunable lighting system installed at the University of Kentucky (UK) in their neonatal intensive care unit (NICU). The decision to analyze the control data from the UK NICU occurred after system installation and commissioning. It did not require any additional equipment or any special lighting system design considerations. The analysis of this control data provides a unique look at how occupants are actually using the tunable lighting system to meet their daily needs, how these decisions affect energy use, and what opportunities exist for optimizing the lighting system to improve energy savings. The patient room is of increasing focus for tunable lighting systems because of the potential to support health outcomes; however, the installation of these advanced lighting systems also provides an opportunity to explore additional benefits, including the role of data in energy efficiency optimization.
Section snippets
Background
In April 2018, the UK moved their NICU to the new Betti Ruth Robinson Taylor NICU at Kentucky Children’s Hospital, in an updated portion of the Albert B. Chandler Hospital. The UK NICU is the only level-four NICU in Kentucky, providing the highest level of care and regularly operating near capacity during the monitoring period of this study. The new NICU has 68 patient rooms distributed among six hallways. Most of the patient rooms have one bed, except for two rooms for twins. The nurses in the
Lighting control system and building automation system integration
The LCS managed all aspects of the linear luminaire and downlights within a patient room including manual and automatic inputs as well as commanding the intensity levels. The linear luminaire, downlights and control stations were all connected to the LCS processor, which commanded and tracked the lighting modes.
The building automation system (BAS) was connected directly to the LCS processor using the BACnet protocol, a commonly used standardized communication protocol for building automation
Cycled-lighting program and manual modes
A sample of the recorded data is presented in Fig. 3, showing the lighting modes used in the five rooms across the same seven 24-hour days, along with an example of what the lighting system would record if there were no adjustments made to the CLP. Each row contains 288 data points creating a continuous line, and the color of each row corresponds to the lighting mode recorded during the 5-minute interval. Details for the different lighting modes are listed in Table 1.
Comparing the hypothetical
Analysis and discussion
The lighting system control data provide a better understanding of occupant response to and interaction with the tunable lighting system. During the 25-week (175-day) monitoring period, the patient rooms were in the CLP mode 47% of the time, while the remaining 53% of the time was spent in the Manual modes, including Exam, Custom, or Off. The design and operation intent was never that the occupants would use only the CLP mode; however, it is surprising that the CLP mode was operating for less
Conclusion
Lighting system control data from five patient rooms in a NICU were recorded during a 25-week (175 day) monitoring period and analyzed to better understand how the occupants, including staff and patients’ families, responded to an automatic lighting system with manual overrides. The occupants used the lighting system throughout the 24-hour day, deviating considerably from the automatic CLP mode.
Beyond the CLP modes, the Exam, Custom, and Manual Off modes were used regularly, and in some cases
Declaration of Competing Interest
Craig Casey is employed at Lutron Electronics Co., Inc. which is the lighting control manufacturer included in this article.
Acknowledgment
The authors acknowledge Lauri Tredinnick of Pivotal Lighting and Bobbie Tincher with the University of Kentucky for their assistance with this research.
Funding
This work was supported by the U.S. Department of Energy’s Lighting R&D Program, part of the Building Technologies Office within the Office of Energy Efficiency and Renewable Energy (EERE).
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