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What Are the Best Practices to Reduce Plug Loads?
Reducing plug loads may look like low-lying fruit in energy management but there are many possible strategies to consider. Researchers have found that the cost/benefit outcomes depend on a number of factors, including building type, occupancy, occupied hours, tenancy and employee density.
Reducing plug and process loads saves energy.
Success and the cost/benefit outcome both depend on a number of factors,
including building type, occupancy, occupied hours, tenancy and employee density.
An experiment at a multitenant office building in Washington, D.C., investigated two very different approaches on different floors. The research at the Millennium Building was conducted by the Institute for Market Transformation (IMT), a DC-based nonprofit promoting energy efficiency, and the Waypoint Building Group, a software and analytics provider for commercial real estate.
The landlord of the building, D.C. metro-based Tower Companies, not only wanted to discover effective practices but also the cost and ease of implementing them.
APS vs. Education Approaches
Three full-floor tenants in existing spaces participated in the study over a roughly three-month period (105 days). The first used a program of education and messaging designed to encourage behavior change among occupants. The second tenant implemented advanced power strips (APS) that power down equipment when not in use. The third was a control group whose members were unaware of the experiment.
Each tenant occupied approximately 19,000 square feet in the building. All groups had their entire plug load metered for the study, including refrigerators, server rooms and common printers as well as devices connected to power strips (computers, monitors, desk lamps, etc.). The submeters were wireless IoT devices that minimized disruption.
The tenant using APS achieved an average 9% reduction in plug loads. Most of the savings occurred during non-working hours (nights, holidays, weekends) when the APS powered down equipment based on a preset schedule or inactivity.
Loads decreased by an average of 29% on workday evenings and 17% over weekends. The implementation cost was $6,000 for 46 employees on its floor, although the researchers note that utility incentives could lower this price.
The 9% savings from the APS was much less than the 48% recorded with similar devices in a GSA study. However, the GSA measured only the power delivered by the APS while the study at the Millennium also recorded plug loads that were not from the APS (refrigerators, servers, etc.).
The education/messaging approach was less expensive to implement – $2,000 for a full-floor tenant with 45 employees. The messaging included a kick-off meeting, lunch and learn, emails, signage and pledges managed by a “plug load champion.” However, no energy was saved in this instance – in fact, power demand increased 1%.
After the first round of messaging, the investigators found a noticeable improvement of 8% over weekends, presumably due to occupants remembering to turn down their equipment. But the impact was short term, with final results mirroring those of the control group.
The researchers believe that the small increase may be due to random variation and noted that the messaging technique used for this particular tenant, a law firm, may not have been as effective as others that could have been devised.
Stanford Researchers Inventory Plug Loads Across Campus
A more extensive study of plug loads covered 220 owner-occupied buildings on the campus of Stanford University. The buildings were varied in terms of type, from labs and offices to dorms and recreational facilities. Nevertheless, computing equipment (personal computers, monitors, servers) was the most common equipment category creating plug loads across all building types.
The category accounted for an estimated 36% of the campus plug loads. Within that category, servers account for 60% of the energy.
The researchers note that many servers were found in IT closets with inefficient cooling, which increases the energy demand to keep the servers operational. A low utilization rate may also drive server power demand. A study by the National Renewable Energy Laboratory found a utilization rate of less than 5% for servers in an office building.
Another source of energy demand at Stanford was space heaters. The researchers inventoried 955 space heaters (one heater for every 17 occupants) estimated to consume more than 500,000 kWh per year.
Overall, plug loads were estimated at 32% of total energy consumption in the Stanford building portfolio. And servers and space heaters are opportunities to reduce demand.
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