Advanced Lighting Control Systems: Bench Testing

Category: 
Commercial Office
Project Number: 
ET14SDG1061
Start Year: 
2014
End Year: 
2015
Markets Segments: 
Commercial
Commercial Office
Commercial, Small
Educational Facilities
Government - Institutional Facilities
Hospitality
Retail
Supermarket
Project Type: 
Hardware
Methodology
Product Evaluation
Scoping Study
Type of Technology: 
Building Controls
Lighting, Commercial
Organization: 
San Diego Gas and Electric (SDG&E - a Sempra utility)
Project Status: 
Completed
Savings Type: 
Work

Advanced lighting control systems provide networked control and monitoring capabilities of connected luminaires via onboard metering and system reporting features. These advanced features allow system owners to dynamically balance visual comfort and lighting energy use. CLTC, in collaboration with SDG&E, developed a technology validation program to determine the accuracy and reliability of onboard metering and system reporting features of advanced lighting control systems. Project outcomes are intended to assist SDG&E and other utilities with future incentive program development activities focused on this product category.

PROJECT OUTCOMES

The project team conducted a market assessment, defined a system testing methodology, and tested three commercially available advanced lighting control systems in accordance with the methodology to validate its procedures and identify areas in need of refinement. The three systems are referred to as ALCS 1, ALCS 2, and ALCS 3 throughout this report. ALCS 1 employs ‘real power’ methods to measure both the current and voltage. However, ALCS 1 resulted in significant error in measurements as compared to the reference analyzer measurements. Two potential sources for this error are 1) are the sampling rate of the current and voltage waveforms not being quick enough to capture the “spikey” waveform of the load used, and/or 2) lack of sufficient bandwidth to capture the “spikey” waveform by the onboard current transducer. ALCS 2 employs ‘apparent power’ methods which determines energy use by multiplying the measured root‐mean squared (RMS) current by the assumed RMS voltage. ALCS 2 resulted in power measurements with greater than 50% error. The apparent power method is more accurate in cases when the power factor is 1. The non‐linear loads selected for this evaluation do not have a power factor of 1 resulting in this approach having a significant amount of error. ALCS 3 employs ‘real power’ methods to measure both the current and voltage. ALCS 3 resulted in power measurements with errors within 2.1% when comparing ALCS power measurements to reference analyzer measurements. ALCS 3 reports one minute power measurements at a five minute resolution. Modeled power measurement sampling rates were also evaluated to determine their effect on reported energy use. Simulated shorter sampling rates resulted in more accurate energy use. Five minute time delays on the simulated occupancy sensor combined with one minute sampling rates resulted in the most accurate energy use reported by the modeled ALCS system. To ensure accuracies within 1% of reference analyzer energy use for the occupancy pattern used in the simulation, the sampling of ALCS power measurement must occur more frequently than once per minute. An alternative approach to ensure sufficient sampling over time is on‐demand sampling, where power measurement occurs at light level changes.

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