This project team aims to develop “CLEAN” a Cloud-computing based Environmental Analytics Network that leverages crowd-sourcing techniques to bring together the collective efforts of social media data and heterogeneous air quality monitors in Hong Kong to reliably identify air quality, and provide accurate and personal healthcare advisory to the public in real-time. They will develop a software platform for smart phones which is intended to inform citizens about air quality, and health advisories, using analytics.
We are well on our way to developing an understanding of what measurable effects common faults in HVAC systems have on power (W) and energy use (kWh) of residential air conditioning units. These faults can include clogging of the outdoor unit from leaves and dust, dirty filters, refrigerant over or under charge, or other issues. By quantifying what effects these faults have, through the use of real time energy use data that a typical HEMS (Home Energy Management System) can record, we hope to develop a low-cost methodology to detect and help diagnose a fault or problem in an HVAC system before it fails or costs the home owner greater energy bills due to inefficiencies in the system.
The first step in this research is to develop models to understand what measurable variables in the energy use data are affected by these faults. This first requires the development of a baseline model that mimics how a correctly-functioning building and HVAC system work. We decided to use two models – one to focus on predicting power (W), and the other on predicting energy use (kWh). Caitlyn has been working on developing these two models.
Building Energy Model (Predicting HVAC Energy Use): The first is a building energy model that mimics the UTest House and its HVAC system at the research campus of UT Austin. Using EnergyPlus (simulation software, see Figure 1) and BEopt (Building Energy Optimization) as the interface, we used the results of the simulation models to analyze the relationship between energy use and outdoor temperature, and peak power draw and outdoor temperature. Figure 2, shows these results, comparing energy use (kWh) to outdoor temperature for each hour of the summer months (May –September) of the simulation.
HVAC Model (Predicting HVAC Power Draw): The second model is the HVAC model that mimics the behavior of the UTest House’s air conditioner. We are using a highly detailed model called ACHP (Air conditioning/ heat pump) (Figure 3). Caitlyn compiled the specs of the air conditioning unit that will be used for testing (Trane 4TTR3030A), and used them as inputs for the model. She has been working on understanding the effects of indoor and outdoor temperature on the power draw (W) of the compressor and condenser fan, and COP (coefficient of performance) (i.e. efficiency) of the system. This provides a baseline, predicted power draw and efficiency of the correctly-functioning HVAC system. Figure 4 shows an example of the variation in power and COP.
By developing these models, we will be able to understand the typical energy usage and power of an HVAC system. Having a “control” is helpful as we introducing faults to the HVAC system and see how these variables change. Caitlyn has also been working on varying flow rates of the condenser at specific outdoor temperatures to understand how a partially blocked condenser fan, one of the common faults being studied, affects power and COP.
The second step is field testing – Melissa has been spearheading this initial effort by identifying the equipment and procedures that related studies have used test the variables we need to measure in this study. She will provide more detailed updates in the next post!
Figure 1: BEOpt Energy Model of the UTest House
The interface BEopt allowed us to easily create a geometric visualization of the UTest House using physical characteristics of the building such as square footage, window areas, and orientation.
Figure 2: Energy Use (kWh) vs. Outdoor Temperature – Building Energy Modeling Results
This graph represents the relationship between outdoor temperature and energy usage. At varying indoor temperature set points, the slopes of the relationship also varies. At an indoor set point of 70°F, the rate of energy usage increases far more quickly with increase in outdoor temperature, than at an 80°F indoor set point.
Figure 3: HVAC Model
The mechanics of an HVAC system shown in this graphic are provided by the ACHP software, and include the compressor, evaporator, condenser, and expansion valve (XV).
Figure 4: Power (W) vs. Outdoor Temperature – HVAC Model Results
This graph shows the effects changes in outdoor temperature have on the predicted power draw (W) and efficiency (COP, %) of the system. With increasing outdoor temperature, power draw increases and efficiency decreases.
SmRTsolutions’ project goal is aimed at increasing the energy efficiency of residential buildings and their systems using Real Time data. We are a group of Architectural Engineering students from the University of Texas at Austin. Our team is made up of, graduate student, Kristen Cetin, undergraduate students Caitlyn Kallus, a sophomore, and Melissa Flores, a freshman. SmRTsolutions’ project goal is aimed at increasing the energy efficiency of residential buildings and their systems using Real Time data.
Greetings from all of us on ESA Team Mongolia,
The past month has flown by. The team has been busy studying the bridge, booking flights, applying for visas, laying out our schedule, and getting a better idea of our day-to-day plans while in Mongolia. We hope to have a 3D CAD model of the bridge completed soon. Please stay tuned for further updates!
Spreading the Word!
This month we had the honor of presenting about LLO at the TRACS (Texas Regional Alliance for Campus Sustainability) Summit in College Station, TX on February 27th and 28th. The event attendees included approximately 150 students, faculty, and sustainability professionals from across Texas, who came together to share ideas, collaborate and improve the sustainability of higher education campuses. It was great to see so much energy and interest in sustainability programs! We are also excited that we were invited to present our efforts at the ACUHO-I/APPA Housing Facilities Conference in October, in Kansas City, Missouri. We look forward to sharing our progress and improvements, our lessons learned, as well as help other universities develop similar programs on their own campuses.
Thanks are needed! On that note, we’d also like to thank Kate Curley and Paul Ruskin from Penn State University, Nick Hennessy from Bowling Green State University, Elaine Durr from Elon University, and Jeff Severin from Kansas State University for sharing information, ideas and suggestions about their campuses’ programs, to help us build the LLO program at UT and make it a success. We hope to do the same for other universities.
This month’s LLO: March’s Longhorn Lights Out will be on March 28th. We will meet at 6:30 pm as usual. Even if you are not a part of the UT campus, we encourage you to participate in these efforts remotely, and turn off your lights and electronics with us, and help us save energy! We’re working on developing an electronic way to allow everyone, not just UT, to participate and track your efforts. Stay tuned for more updates next month.
If you are on campus, after LLO this month we will be watching the documentary “Switch” – a great film produced under the direction of Harry Lynch and with expert guidance from Dr. Scott Tinker from UT. Below are also some pictures from the most recent LLO.
About LLO: Longhorn Lights Out was started in April 2013 by the Energy and Water Conservation Program at the University of Texas at Austin. The goal of LLO is to engage students, faculty, and staff in reducing energy use in the buildings at UT. As a part of this program, once a month LLO students meet on Friday and go to campus buildings and turn off lights, electronics, projectors and monitors that are left on in order to to reduce energy use.
Arnob is a senior at Carnegie Mellon University. In May 2014, he will graduate with a double major in Electrical & Computer Engineering and Biomedical Engineering. Arnob has experience in software development and has an interest in medical devices.