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TRANSCRIPT
Jacqueline Hsu
CITRIS Sustainability Internship
12 April 2013
Measuring Plug Loads at LBNL
Initially, John Elliot and I talked about potential projects, including one that involved
creating and implementing an equipment lending library, but we have decided to work on a plug
load project. This plug load project is aiming to measure the energy usage of plug loads in LBNL
buildings that are not on their main laboratory campus. As these buildings will soon merge with
the main campus and the Richmond Bay campus, we want to see how we can reduce plug load
energy usage during the move. Thus, this week I did research based on case studies on plug load
reduction and how to implement a project similar to this.
In a typical California office building, lights consumer 40 percent of the total energy
usage, HVAC consumes 25 percent and plug loads consumer 15 percent, but as laboratories use
three to eight times more energy than a typical office building, plug loads constitute a far larger
portion of the energy consumption. Furthermore, proportions for the energy usage change in a
high performance and efficient building, where unregulated plug loads can become more than
50% of the total energy consumption. Plug load monitoring is the best way to determine the plug
loads that are redundant and unnecessary in both office spaces and laboratory spaces.
One case study that I looked into is the NASA pilot study program at the NASA Ames
campus. This pilot program took place during the spring and summer of 2011. The study used
plug load management systems by Enmetric Systems that allows for metering and control of
individual electric plug loads. From this study, they found that each workstation consumed an
average of 27 kWh every week with no controls in place, but computers made up 82 percent of
that energy usage. The average desktop computer consumes an average of 2.7 kWh, while
laptops consumed 0.36 kWh, thus showing that a switch from desktop computers to laptop
computers could demonstrate large energy savings. Additionally, they recommended using
tactics such as promoting energy efficient behavior changes, installing energy efficient
appliances and equipment, implementing and institutionalizing energy policies, and employing
plug load controls to help lower the overall energy usage.
A second case study that I researched is the California Energy Commission Office Plug
Load Field Monitoring Report. During this study they found that office equipment and other plug
loads constitute for more than 20 percent of the energy usage in California offices. The study
look place in 47 offices with plug load meter installations in 25 offices with the use of the Watts
Up Pro ES meters to monitor the plug load usages. Their results showed that computers and
monitors accounted for 66 percent of the total plug load energy usage, office electronics
including printers and fax, made up 16 percent of the plug load energy usage, and miscellaneous
items such as task lighting and coffee makers made up 18 percent of the plug load energy usage.
As repeated in this case study, computers tend to be the largest energy user in office settings, so
this is something that LBNL can look into when monitoring the plug load energy usage in their
offices. Additionally, the study also mentioned that a lot of the plug load energy usage came
from the electronics being on during nights and weekends, which is something that can be
improved through occupancy sensors and installation of timers. They recommend offering
aggressive education about the energy use of office electronics, promoting power management
features of office electronics, purchasing only energy efficient appliances, implementing smart
strips and automatic controls, and retrofitting the office if needed.
With these two case studies, I found that the most common way of monitoring the plug
load energy usage is by using a metering system for a short period of time. First, it is important
to create a plug load inventory and meet with a facilities building manager to answer any
questions they may have about the study, as well as get answers about the staff practices and
behavior in the office or laboratory space. During this process of inventorying, it is important to
note the device name, location, type of power supply, and whether the device is unplugged or
inaccessible for metering. Second, the metering team must choose a random sample of the
inventoried electronics to meter. As it is not easy to inventory a high number of electronics,
especially if it was on a building wide scale, choosing a random sample from each floor would
supply the best plug load energy usage estimate. If choosing the electronics by hand, it is
important to note that devices that have a high energy use or little is known about the energy use
should be considered first for metering. During this time, it must be determined how many
meters will be allocated to each site and to keep track of which meter is tracking which device.
Then, the meters are installed for a minimum of 1 week and then removed after that period. The
data from the metering system will show the peak energy use times, standby times, and whether
or not the electronic is left on after work hours.
While my research thus far only shows the plug load usage in California offices, it has
been difficult to find plug load research for laboratories. I believe that this is mainly due to the
type of equipment being used in laboratories and the difficultly in installing a metering system
for a laboratory building. This next week I will continue my initial plug load research and find
resources that can specifically help LBNL develop an implementation plan to conduct a plug
load monitoring project, as well as find data on laboratory equipment energy usage.
Jacqueline Hsu
CITRIS Sustainability Internship
19 April 2013
Plug Load Meters and Solutions
After researching and reading through several case studies of offices doing plug load
audits and installing monitoring meters, this week I have completed research on existing plug
load meter technology. As mentioned in the meeting, network meters allow for a simpler way to
gather and aggregate all of the data in a building and a more advanced form of technology that
will be easier to implement than manual plug load meters, such as kill-a-watt meters. The plug
load meter technology systems that I researched include Enmetric Systems and Autani Systems.
First, from a NASA Pilot Study for a plug load management system, they used the
Enmetric Enterprise Plug Load Management System, which is a plug load management system
that consists of two separate consoles, the PowerPort and the Bridge. This plug load management
system allows for metering and control of individual electrical plug loads. The Power Port is an
advanced power strip with four channels that are individually metered and controlled and this
console transmits the data once per second to a separate console, the Bridge. The data is stored in
a cloud-based data service once per minute with the minimum, mean and maximum power draw
over each one-minute interval recorded. Currently, Enmetric Enterprises system comes with
software that allows users to measure and control the plug load energy usage and quickly
identifies unnecessary energy usage and automatically shut them off. The software also allows
users to generate detailed reports on the plug load energy consumption and the energy demand at
certain times of the day. The software features allow for the benefit of measuring and tracking
the progress of reaching specific energy goals. Additionally, it helps save time by logging all of
the data for baseline measurements and treatment measurements. Unfortunately, I could not find
a price for the system online, but their targeted customers include large enterprises, small and
medium sized businesses, government facilities, and educational facilities. Due to the lack of
specific pricing, I am assuming that they charge based on the quantity and type of consumer.
A second plug load meter system that I researched is the PLUS system by Autani. On
their website, Autani noted that when equipment is in standby mode, the energy used accounts
for up to 10 percent of all electricity usage in commercial and educational facilities. While I have
never seen this particular statistic before, it is interesting that when electronics are in standby
mode, a ton of energy is still being used. The Autani System offers different types of plug load
meters that all contribute to plug load management. For instance, the Autani 6 Pack Load
Controller is a wirelessly managed load controller that provides both direct and independent
control of six different plug loads. This is commonly used for controlling plug loads in an office
space, site lighting, signage, or appliances. The features of this controller include independent
control of six switched loads according to schedule, occupancy and day lighting. Another Autani
Systems plug load management product is the DISTRO Wirelessly Managed Power Strip. This
advanced power strip allows for wireless control of the power strip, which will help reduce
energy usage from standby mode loads and unattended devices. Additionally, the PLUS
computer software that comes with the different system products allows for remote and local
access to web-based metering, monitoring, reporting and management of the power strips. This
software helps keep track of the energy usage data for each individual plugged-in electronic.
Lastly, I wanted to find a large network based monitoring system for plug loads, but I
found that in most cases, facilities used smart meters and advanced power strips to monitor plug
load energy usage. Additionally, there is growing popularity for software systems that
accompany these advanced power strips and meters in order to track and log the energy data in a
web-based data system. A lot of the companies and case studies I researched mentioned that they
installed different types of equipment to meter different appliances. For instance, when
controlling plug load usage from computers, it is recommended to install a power management
system specifically for IT, in which case, Lawrence Berkeley Laboratory has already installed
the Tivoli BigFix Endpoint Manager. As for individual small plug loads, most case studies
recommended the use of smart meters and smart strips. While I do not know if this is the best
way to monitor plug load usage, it seems as if it is a common method used in office spaces.
The main distinction is that the office setting and laboratory setting are very different.
The lab would need to install the wirelessly controlled smart strips and have someone who sets
the timers and schedules for each one, without interrupting anyone’s work schedule and work
environment. This seems as if it could be complicated, as many laboratory workers may not have
set hours for each day. Additionally, it was difficult to estimate the cost of installing smart
meters and advanced power strips due to the lack of direct pricing information from the
companies. It seems as if many of them work with large corporations, thus do not offer an every
day consumer based pricing method. I will continue doing research on what other laboratories
have done to manage plug load usage and see if there are better monitoring systems and meters
out there for LBNL.
Jacqueline Hsu
CITRIS Sustainability Internship
26 April 2013
Case Studies from Sutardja Dai Hall and Lawrence Berkeley Lab
After speaking with John Elliot last Friday, we have decided to continue our research by
reading past case studies related to plug load usage monitoring and tracking on the UC Berkeley
campus. Thus, this week I focused on the project completed by both Jason Trager and Jorge
Ortiz in Sutardja Dai Hall and the plug load energy survey completed in Building 90 of LBNL.
First, the plug load survey in Sutardja Dai Hall incorporated the use of a smart phone
based auditing application. QR codes were assigned to each electronic device and tracked with
the smart phone application. By using this type of database, it was easy to organize the electronic
devices by location, type, and energy usage. Luckily, I have gotten access to the smart phone
application and will delve further into how to use the application for the potential plug load
survey to be completed in the summer.
After reading over the project paper, I noticed that a previous study they had noted had
used the Watts-Up plug-load meter, which has no networking capabilities and costs around two
hundred dollars, but is user friendly and commonly used by auditing teams. As an alternative for
the Watts-Up meter, they used a plug-load meter called ACme, which is said to have cost around
twenty dollars per meter. When speaking with Jorge about these meters, he mentioned that the
team had made these meters themselves and they highly recommend them as they have wireless
networking capabilities.
As for the actual survey implementation, I have summarized the process into the
following steps:
1. Conduct a walk-through of the building and compile a list of electronic devices and categorize
them by assigning each type of device a short name (i.e. Phone = PHN). During this step, it is
necessary to either find the manufacturer’s specifications for the device’s average energy usage
or take a baseline of the energy usage using the plug-load meters. Another helpful resource is
floor plans for the building, so that it is easy to keep track of where each device is in the
building.
2. Deploy the plug-load meters to specified areas, if not metering the entire building. When
doing this, be sure to use the QR codes and the smart phone based auditing application to track
which meter is installed to which electronic device. This will make sure that the data logged is
accurate and organized.
3. Analyze the collected data based on timeline and specific details relating to the project.
Provide recommendations based on findings.
As for the results of the case study, the team found that the majority of the plug load energy
usage came from resistive loads, which includes space heaters and coffee machines. The second
largest energy user was computing equipment, such as monitors and desktop machines.
A best practice from this particular case study is the use of the mobile phone application.
By using the application, the team members were able to collect deployment information in an
easy and timely manner. Additionally, it keeps the data logged through a cloud-based network
and prevents loss of information and data. Also, the use of QR codes allows for an easy and cost
effective way to track each individual electronic device, although it may seem tedious to sticker
each individual device, but it ultimately necessary for the success of the data tracking for plug
load energy usage.
A second case study that I looked into was the plug load survey completed in Building 90
of LBNL. The survey completed in Building 90 consisted mainly of an office section of the
building and thus, does not offer any insight into the plug load energy usage of a laboratory
space. During this project, they also deployed ACme plug load meters to track the energy usage
of individual electronic devices and installed 455 ACme meters for over six months to get long-
term data. They also used a cloud-based network to make the process of tracking energy usage
easier. For this study, the results showed that plug load energy usage accounted for forty percent
of the building’s electricity and fifty percent of that was being used by computing equipment,
while the other ten percent was displays, miscellaneous heating and air conditioning appliances,
network equipment and task lighting. As for their recommendations, they found that using
computer power management could save up to twelve percent of the building’s total energy
usage and using timer controlled power strips could save six percent of the total energy usage.
One thing that I am keeping in mind for the computing equipment energy usage is that LBNL
has recently deployed the use of the BigFix Endpoint Manager software, which is a power
management software that is supposed to help eliminate plug load energy usage from desktop
and laptop machines. Although not every computer has the software installed, I believe that the
use of power management will help lower their plug load energy usage significantly as shown in
this particular LBNL study.
Jacqueline Hsu
CITRIS Sustainability Internship
3 May 2013
LBNL SEAMS and Lab21 Plug Load Study
A new group at Lawrence Berkeley Lab called SEAMS, Scientific Equipment Asset
Management System, has been attempting to catalog all plug loads at four off-campus LBNL
building locations. They have kindly shared their data with me, and this week I analyzed
SEAMS surveying strategy, as well as conducted additional research on energy efficiency in
laboratories based on Labs21 papers and information.
SEAMS was recently created with the goal of providing a collection and tracking system
for all scientific equipment at Lawrence Berkeley Lab across groups, departments and divisions.
The project is separated into two different phases. For phase one, SEAMS has completed data
collection for one off-campus LBNL building (APBDU) and are currently working on collecting
data for three other off-campus LBNL buildings including JBEI, JGI, and LSD. The format for
their project is an online database website and search engine. The website is currently being
developed and I will be reviewing the beta version and offering comments and suggestions
during phase 2 of the project. For the online database, lab attendants can login, search, edit, add,
and note hazards about the laboratory equipment, but these functions may not be carried over for
the published online version after the project is complete. For this database, it reflects the data
collection network used in Sutardja Dai Hall, except SEAMS is utilizing lab attendant
participation and cooperation. One problem that they will possibly run into is a lack of
participation, thus an educational marketing campaign may need to be implemented in order to
guarantee success for the online database. On the other hand, they are thoroughly surveying the
plug loads on each building and they may have more than enough data to complete the database
themselves. The only problem there is that they will not be able to track any new and incoming
appliances and electronic equipment after their complete their data collection and surveying
phase.
SEAMS has also provided me with an extensive spreadsheet of their data collection thus
far and while it is relatively rough, they aim to gather a lot of information. The information that
they are attempting to collect for each appliance includes the includes equipment category, name,
description, the manufacturer, model and serial number, weight, width, depth, height of the
appliance, the exact location of the appliance, the key contact person, status of use, whether it is
a shared appliance or not, the appliance’s chemical components and usage, the appliance’s water
usage, the appliance’s waste category, electrical power usage in voltage, wattage, ampage and
frequency, energy usage in standby mode and safety guidelines and operating manuals. If
SEAMS can collect all of this information by their projected June deadline, I will be able to help
them in the data collection process and help generate potential energy savings and create a
recommendation for departments.
This week I also did some background research on energy efficient research laboratories
from the Labs21 database. In their database their have a lab equipment wiki, which includes
energy information for a lot of commonly used lab equipment. The structure for their lab
equipment wiki is very similar to SEAMS beta database. The database will be useful once we are
able to get into the laboratories and see what type of equipment is being used. From the Labs21
database, we may be able to recommend more energy efficient options and provide potential
metrics and monetary savings. Additionally, Labs21 also provides a ton of case studies and
energy efficiency guides. I focused on the “Design Guide for Energy-Efficient Research
Laboratories,” which is interesting in that it is based on a new research laboratory, which may be
useful regarding the move of several building to the LBNL Richmond Bay Campus.
In the design guide, it is mentioned that many different things must be taken into account
with looking into energy efficiency in a research laboratory such as the fact that it is a “special
environment” and laboratories are designed to meet specific demands for experimental studies
thus safety and planning is essential. The energy-efficient design process includes the topics of
minimizing the energy load, determining potential energy load variability, matching the
variability with an adjustable system, using integrated energy engineering and understanding
barriers with consideration of safety precautions. For minimizing the energy load, the focus is
primarily on the heating and cooling ventilation system and the circulation of air in laboratories.
In this aspect, fume hoods are enormous energy users and would most likely be an area to focus
on when looking into energy usage on laboratories. As for the HVAC system, I can assume that
the Richmond Bay Campus has already taken energy efficiency into account on that matter. As
for variability in the energy load, this relates to how experiments and projects in a laboratory can
vary with time. Some projects take years to finish, while some only take months. In this aspect, it
would be important to consider what type of equipment these groups are using and how long
they will be using them for. For example, if the research group were to be working with high-
energy intensity equipment for many years, it would be a wise decision to prioritize purchase of
energy efficient equipment for that particular research group. Secondly, integrating energy
engineering involves planning ahead of time. This is for new research laboratories and allows
building facilities managers to take energy efficiency into account before there are building
attendants. This tends to be the case for newer LBNL buildings, thus this may not be important
when considering plug load energy usage.
Works Cited
"A Design Guide for Energy-Efficient Research Laboratories." Labs21. Labs for the 21st
Century, n.d. Web. 02 May 2013. <http://ateam.lbl.gov/Design-Guide/index.htm>.
Jacqueline Hsu
CITRIS Sustainability Internship
10 May 2013
Demand Control Ventilation
Demand control ventilation is heating, ventilation, and air conditioning system that aim to
provide the correct level of heating and cooling for the actual occupancy level. There are
multiple ways to provide demand controlled ventilation including developing a scheduled HVAC
system, use of motion sensors, use of carbon dioxide sensors, use of sound sensors, and use of
video cameras as occupancy sensors. This week I conducted research on different studies of
demand controlled ventilation for laboratories and hospitals.
As ventilation in hospitals is essential to the indoor environmental health of both patients
and hospital staff, most hospitals pay close attention to new technologies related to HVAC
systems. In addition to that, a hospital’s air conditioning and ventilation systems are exposed to
more airborne contaminants than general areas. Thus, hospitals tend to have strict regulations for
HVAC systems. For instance, in the Tampa Bay area, hospitals have adopted a multi-parameter
demand controlled ventilation system. This system senses airborne contaminants and increases
the ventilation rate to dilute and purge the affected areas. The system does this through the use of
contaminant sensors that are placed throughout the hospital. Air samples are collected every
three minutes and analyzed locally or transported to a centralized sensor array for further
analysis. In addition to this new sensor system, these Florida hospitals have taken the extra step
to hire MSCA Green Star certified air conditioning contractor, an Energy Star partner provider,
and LEED accredited professionals to develop this demand controlled ventilation system. From
this study, their best practice is using the overall goal of sustainability to take advantage of an
energy efficient system that will also provide them with economic and monetary savings.
Another study I looked into is UC Irvine’s initiative to compare ventilation control
systems to reduce their overall energy consumption and increase lab user safety. At the UC
Irvine campus, lab buildings consume two-thirds of the overall campus energy usage. Their
current ventilation systems run at a constant rate and are usually running excessively during
periods of low-level process activity or non-occupancy. During this study, they evaluated three
different systems including a centralized demand controlled ventilation system (CDCV), a zone-
occupancy control system, and a combined control system using both the CDCV and zone-
occupancy. From their study, they found that a monitoring-based commissioning program was
best for their lab buildings and this program combined different aspects of the systems they
tested. This type of program would increase safety and reduce energy consumption by
monitoring lab areas on a steady basis, provide quick and easily accessible data, and involve
onsite personnel for accurate monitoring. In addition to this program, they believe that installing
occupancy sensors will make their monitoring system more accurate and useful for the
ventilation controls.
Another resource that I found it the Aircuity paper on demand control ventilation. The
main demand control ventilation system method that they mention is carbon dioxide sensors.
They note that the main challenges with a demand control ventilation system is the inability to
address non-human pollutants, inaccuracy of control leading to excess use of outside air, and
carbon dioxide sensor calibration and maintenance considerations. To overcome these
challenges, they recommend a multi-parameter demand control ventilation system, such as the
one used by the Tampa Bay hospitals. This type of system will be able to accurately provide
differential sensing of carbon dioxide, be cost effective and have simple sensor calibration and
maintenance. To implement this system, one individual sensor for each contaminant that should
be sensed would have to be installed. To make this more cost effective, sensor equipment that
combines at least two or more of the sensors onto one circuit board can be installed. This would
lower the cost, as these sensors would share packing, energy consumption, and signal processing.
The only issue here is that the quality and accuracy of the sensor may diminish.
Before researching demand-controlled ventilation, I thought that the concept would be
similar to demand side management for energy consumption, but it is not. Demand controlled
ventilation focuses on providing the right indoor environmental air quality for the occupants,
especially in sensitive areas and locations, such as a hospital and a laboratory. Thus, such a
system would be beneficial for LBNL to utilize. As of right now, the most similar type of
ventilation used in laboratories would be a fume hood, unless the laboratory has installed a
system-wide demand controlled ventilation system. The difficulty for laboratories, especially
ones like LBNL, is that projects change every few years, thus the chemicals used may change. If
the chemicals used change, then the sensors would also need to be replaced. This would most
likely be a main concern for why demand controlled ventilation systems may not be best for
laboratories. Additionally, there is the question of whether or not the use of a demand controlled
ventilation system would replace the need for a fume hood. I believe that these issues depend on
the laboratory and the type of study the lab group is conducting.
Works Cited
"Advanced Ventilation Strategies for Tampa Hospitals." Hill York. N.p., n.d. Web. 07 May 2013.
<http://www.hillyork.com/advanced-ventilation-strategies-for-tampa-hospitals/>.
"A Healthier, More Energy Efficient Approach to Demand Control Ventilation." Aircuity, n.d.
Web. 7 May 2013. <http://www.aircuity.com/wp-content/uploads/7c-Healthy-Demand-
Control-Ventilation.pdf>.
Gudorf, Matt. "Laboratory Ventilation Performance: Comparing Centralized Demand Control
and Zone-Occupancy Control Systems." I2SL: E-Library. Labs21, n.d. Web. 07 May
2013. <http://www.i2sl.org/elibrary/gudorf2010.html>.