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Sustainable Grid Integration of Distributed and Renewable Resources

Affiliate Research Abstracts

Advanced Building Thermal Management Systems- Steve Bourne (with Atila Novoselac) 

As we begin to increase our dependence on renewable but intermittent energy resources, such as wind and solar power, the management of energy demand becomes more critical.  Improving the thermal energy management of buildings has the potential to make their energy demand more flexible and thus more adaptable to these emerging energy sources.  One way of achieving this level of thermal energy management in buildings is through the controlled use of thermal mass.  Integrating phase-change compounds as thermal mass into common building materials, and coupling these materials with specialized thermal management systems, will allow for the strategic storage of heating and cooling energy.  This storage capacity will improve the robustness of the thermal system to intermittent energy availability.  The modeling and experimental testing of potential applications for phase-change materials in buildings and their interaction with other thermal control mechanisms - such as HVAC systems and facade-based thermal control systems - will enable us to evaluate the performance and benefits from these integrated systems and to design suitable application guidelines.  The Pecan Street Project, coupled with University of Texas test facilities, provides the unique opportunity to monitor actual building energy use and to utilize this data in our models, while the Pecan Street Project demonstration house offers the ability to validate our models by deploying this technology in a real-world building environmental system.

Energy Storage and the Pecan Street Project - Robert Fares (with Prof. Jeremy Meyers)

Energy storage has a wide range of benefits at all points in the generation, transmission, and receiving ends of the electric grid.  However, many emerging energy storage technologies have prohibitive costs which make experimentation with these technologies on a larger scale difficult.  Energy storage technologies will be evaluated as part of the five year smart grid demonstration project being carried out by Pecan Street Project Inc.  In order to determine the most appropriate technology to begin testing at a medium scale, energy storage options and their individual benefits and applications to Pecan Street Project will be examined and quantified. This study will be used to begin experimentation and documentation of the benefits of installed energy storage relative to baseline energy use data already collected by Pecan Street Project.

Disaggregation of Air-Conditioning Load from Smart Meter DataKrystian Perez (with Prof. T.F. Edgar, Prof. Michael Baldea and Prof. Michael Webber)

The mass installation of smart meters in the United States has provided an opportunity to better analyze and respond to fluctuations in residential energy consumption. Air-conditioning use, which is a significant and highly variable component of home energy consumption in the cooling-climate areas in the United States, can be determined from whole-home energy consumption data through non-intrusive load monitoring (NILM). In this paper, a NILM technique is developed and executed to disaggregate A/C usage from one-minute smart meter data provided by the Pecan Street Research Institute for 88 homes in Austin, TX, USA, from July 2012-June 2013.

The proposed NILM technique uses edge detection to identify large changes in instantaneous power [1]. The premise of the following algorithm is that during months where A/C is both present and dominant, the early morning time period can be used as a training period to determine key parameters, such as the magnitude of A/C spikes that indicate that the A/C unit has turned on. The algorithm then steps through a daily energy profile and identifies changes in loads that match on/off A/C events. From this information, overall A/C energy use is derived.

Of the 88 homes in the case study group, 19 have sub-metering provisions which directly measure A/C consumption; these homes provided a control group used to validate the accuracy of the NILM disaggregation technique. The R-squared value between the predicted and actual A/C energy use for homes that had been sub-metered was 0.90. When NILM was applied to all 88 homes it was found that the total energy from A/C increased 25 kWh between a mild temperature day of 15.5 °C (60 °F) and a hotter day of 33.2 °C (92 °F). The magnitude of change between the extremes in CDD shows that the total A/C consumption for the conglomerate of homes will increase by a factor of eight while the base-load (the difference in energy by taking A/C energy from the total) only doubles. The average time the A/C unit operated per day during the months for which A/C is a prevalent feature (May-October) in the energy profile was 7.4 hours. Similarly the average number of cycles per day was 32. The average A/C fraction of total energy total energy was on 40%. Average time operated, number of cycles, and A/C fraction of energy are reported and were all found to increase linearly with increasing outdoor temperature up to 25 °C (77 °F) and then began to level off.

[1] G. W. Hart, "Nonintrusive appliance load monitoring," Proc. Ieee, vol. 80, no. 12, pp. 1870–1891, 1992.

Smart Gas and Smart Water Systems - Joshua Rhodes (with Prof. Michael Webber)

“Smart energy” doesn’t just refer to the smart grid: it includes smart gas and water, both of which are essential to the smart energy infrastructure.  These systems are not impervious to interruptions as seen by the Texas gas grid depressurization of early 2011 and Austin water restrictions for most of 2009.  A better understanding of natural gas systems and usage can enable greater penetration of efficient appliances and distributed generation by products such as gas micro turbines, home car refueling, and bloom boxes.  With a large amount of energy used to treat, move, and remove our water, smart water systems will not only save water, but also have a positive feedback to the entire energy infrastructure.  Overall, my research is comprised of a systems analysis of smart gas and smart water meters, appliances, and business models for the built environment in partnership with the Pecan Street Project and the Doris Duke Charitable Foundation.  The analysis will include energetic balances, efficiency assessments, environmental tradeoffs, and economics.

Fire Safety in Green/Sustainable Buildings - Bonnie Roberts (with Prof. Michael Webber and Prof. Ofodike Ezekoye)

More than half of US direct energy consumption occurs in buildings. Driven by the desire to reduce consumption and improve sustainability, many new buildings are designed to be "green". As the green industry develops, changes in materials, energy monitoring (smart meters/appliances), production (solar panels), and storage (batteries), HVAC, water collection and reuse, etc., will impact fire prevention and mitigation for these sustainable structures. Some alterations can improve fire safety (monitoring systems), while others are likely to increase risk (on-site energy storage). A detailed analysis should be undertaken to understand the individual and cumulative effects that these changes will have on fire suppression. Building codes and standards will need to address these concerns. Our research aims to identify the key areas requiring further analysis and development, regarding the interlinking of fire safety and green buildings. Literature review, interviews with concerned parties, and numerical modeling is being conducted in the following areas: (1) Materials - new types of flooring, insulation, furnishing, and the like will alter heat release rates, flame travel, and other fire characteristics. Furthermore, new framing materials may undermine the structural integrity of the building under heat loads. (2) Windows/skylights/solar tubes - various changes in window manufacturing (e.g. Number of panes, glazing) may affect their response to fire loads. Radiant heat can break windows and subsequently oxygenate the fire. (3) HVAC - traditional air duct conditioning vs. ductless liquid conditioning systems may vary fire spread rate. (4) Smart sensors - meters, smoke alarms, appliances, etc. may be used in diagnostics for risk assessment as well as allow faster response times from first responders. (5) Energy Production & Storage - the intermittent supply of solar and wind generated power creates the need for batteries or other storage devices. Not only may the on-site power production pose a shock risk to firefighters, but storage may significantly increase the risk and intensity of the fire. (6) Water collection & Reuse - conservation techniques such as rain harvesting and grey water reuse systems can also serve as firefighting mechanisms if designed as integrated parts of sprinkler networks.

Integration of Plug-In Electric Vehicles (PEVs) and the Grid - Dave Tuttle (with Prof. Ross Baldick)

There are a number of motivations for developing alternative energy sources and associated vehicle powertrains to reduce a widespread dependence on oil for powering transportation.  The motivations include energy security and its related costs, environmental concerns (including climate change and oil spills), air quality, and trade deficits (with oil imbalances constituting close to half of the U.S.’s trade deficit, for example).  A variety of PEV models and architectures are arriving to the market or are under development.  While each PEV architecture has its own particular strengths, weaknesses, and individual capabilities, all have the common trait of a relatively large on-board battery.  The many methods to intelligently control the charging of the PEV battery and also for the grid to temporarily borrow energy from the vehicle’s battery create a unique opportunity to not only use these electrified vehicles to solve important transportation related problems, but also to create synergistic interactions with the grid.  These synergistic interactions between the grid and PEVs offer the promise of enabling greater amounts of clean renewable generation sources on the grid to be economically deployed.  The Pecan Street Project is a unique smart grid demonstration project which will provide opportunities to evaluate intelligent PEV charging.  Topics to be studied include charging behavior data, charging infrastructure implementation, intelligent charging and communications, and PEV usage models.

Analysis of Energy Use Patterns in Smart Grids - Charles Upshaw (with Prof. Michael Webber)

Given the technological demands of the 21st century and with computers, internet, cell phones, and other sensitive electronics so integral to modern life, it has become imperative to rethink the way electricity is generated, distributed, and consumed.  ‘Smart Grid’ is a term used by many to describe an electric grid built to be robust, intelligent, interactive, and sustainable; however, how these goals are accomplished, is still the subject of much debate and research.  Technologically, the Smart Grid incorporates modern power electronics, controls, and communication technologies to create a robust and flexible system.  Eventually, technologies incorporating home energy management systems, smart appliances, home generation and storage, and smart electric vehicle charging will be readily available.  This opens the door for next generation energy use management by the customers and utilities, including time-of-day pricing, load shedding incentive programs, and other strategies to manage peak demand and reduce energy consumption.  The impact of these technologies is not yet known and will depend greatly on how they are implemented and controlled.  This research, performed in support of the Pecan Street Project, will analyze energy use patterns before and after the installation of smart grid technologies in order to determine the effects of technologies and management strategies.

Autonomous Trading Agents for the Smart Grid - Daniel Urieli (with Prof. Peter Stone)

The vision of a smart electricity grid is central to the efforts of moving society to a sustainable energy consumption. Two main goals of the smart grid are (1) supporting the integration of intermittent renewable energy sources while maintaining the balance between supply and demand at all times, and (2) reducing the peak electricity demand. To achieve these goals, one of the proposed suggestions is to insert an intermediate layer between energy producers and energy consumers, in the form of automated broker agents that trade energy while being financially incentivised to maintain balance between energy supply and demand in their portfolios. Such broker agents need to make effective sequential decision making under uncertainty. To remain active, they must be profitable, and for that they must be able to (1) learn (2) predict (3) plan (4) adapt. Developing such broker agents should give insight regarding (1) the computational techniques that are required for designing a successful broker (2) the overall impact on the smart grid's power flow and supply-demand balance in the presence of such broker agents. The PowerTAC simulation platform is an open-source smart grid simulator that would serve as a testbed for this domain. An overall goal of this research direction is to provide concrete insights to the question of using financial incentives for affecting consumption/production behaviors.