Synthesis, Characterization, and Properties of Thin Film Materials with High Thermal Conductivity - Matthew Charlton (with Prof. Rod Ruoff)
Proper handling of thermal energy is becoming an important challenge as smart energy grid technology develops. Many power generation facilities are now harvesting the heat byproducts from their processes and converting this thermal energy into usable forms. The management of this thermal energy is a big challenge from a number of aspects beyond the actual conversion process. For example, efficient transport and storage of the waste heat prior to transformation can be difficult to achieve. New materials like graphene and hexagonal boron nitride thin films show great promise for applications in thermal transport. The extremely high thermal conductivity exhibited in the basal plane by these materials may help to control the flow of heat from the generation source to the conversion site, while low conductivity perpendicular to the plane will serve to minimize energy losses during transport. Developing production capabilities of these new materials as well as understanding the specific thermal transport mechanisms will be important steps toward implementation of new technologies in this industry. Studies involving the Pecan Street Project, an investigation on smart grid technology, will help to identify needs and possible applications for these new materials.
Reliability Studies of Microgrids - Greg Dahlberg (with Prof. Alexis Kwasinski)
According to the Department of Energy, “the reliability and power quality of electricity in North America is poor compared to other developed countries”. Considering that the US power grids are one of the fundamental supports of US economy, power supply availability improvement is an urgent need. This need was the original motivation for development of smart grid systems. One possible solution to the power grid availability problem is distributed generation and the development of microgrid technology. In particular, a combination of local energy storage and local renewable power generators is seen as an advantageous approach because these technologies do not require lifelines. My research focuses on modeling the availability outcomes for various types of microgrid configurations (e.g., distribution line redundancy, transformer redundancy, etc.). The problem of computing microgrid availability is a complex task due to the numerous ways a system can fail. A network with four degrees of redundancy, for instance, where each line is modeled as having ten distinct components, can fail up to 10,000 different ways. To calculate the probability of failure or unavailability requires considering every possible failure permutation. Systems with combinations of parallel and series components make the calculation more complex since the number of ways that a series-parallel system can fail is an initially unknown subset of the total permutation set. Determination of this subset, which is composed of so-called “minimal cut sets”, is a sufficient requirement to efficiently quantify a network’s availability. In addition to a graphical minimal cut set method, simulation techniques such as the Monte Carlo method and probabilistic “Markov Chain” models are also employed in order to validate the analysis. Minimal cut sets will also be used in order to develop a new availability analysis approach termed Reduced Markov-based availability model.
Power Flow, Load Balancing, and Distributed Architecture in a Localized Microgrid with DC Grid-Tie Connections - Hunter Estes (with Prof. Alexis Kwasinski)
Pecan Street Project aims to intelligently monitor power flow issues across a localized grid, hopefully in greater detail and resolution than ever before. By doing so, we gain a more accurate picture of how energy is deployed to meet changing load demands. The Mueller project will include additional grid-tie components such as solar PV, electric vehicle charging, and even some forms of energy storage. To build a grid of the future, Pecan Street Project will study and quantize these effects so we are better prepared for the future generation of microgrid deployment and management. Safety consideration related to open series faults within a system become very important as DC generation (solar PV) is integrated into the existing grid. This study aims to determine how DC faults differ from AC, how dangerous they are, if they can be modeled, what types of circuit detection and protection schemes are needed, and suggestions on HVDC breaker designs. With an increasing number of circuit measurement elements, individualized home circuitry can be independently studied, resulting in better load flow analysis than if energy deployment were studied solely at the home meter. Additionally, issues such as intermittent generation (solar PV generation influenced by cloud cover), constant power loads, large loads such as vehicle charging, cyclical loads (heating and cooling), and even load harmonics can be studied to gain insight. With a complete picture of load demand and energy generation, the most sophisticated techniques of energy deployment can then be suggested, along with control features that should be incorporated into a home energy management system.
Customer Behavior Modeling in the Pecan Street Project - Akshay Sriprasad (with Prof. T.F. Edgar)
The current ineffectiveness of the grid’s status-quo business model drives research in the area of customer-utility behavior modeling. At present, many electricity providers employ a flat tariff plan for its residential customers, charging the same amount for power irrespective of peak load and time-of-day usage. This model does not reflect the true cost of generation to the provider, which must make capital and operational expenditures on peaking plants to meet peak demand. Ultimately, high residential peak energy consumption increases the cost to the customer as well, through higher rates set by the utility to offset their own burden. One of the broad aims of the PSP smart grid project is to implement demand response into an improved business model that incorporates real-time cost of usage and motivates customers by monetarily incentivizing a shift of usage away from peak hours. The end result from demand response will directly benefit the utility with a lower peak load as well residential customers who save money from smarter consumption habits. Realization of these benefits, however, requires broad customer adoption and responsiveness to the proposed variable pricing. Modeling customer behavior will become a key tool in monitoring program adoption and success. Data collected from PSP residential participants will be used to develop models of customer behavior. These models will consider many external and internal factors, including but not limited to: pricing signals from utilities, residential PV/renewable generation, as well as the evolving paradigm of plug-in vehicles and energy storage. Using behavioral models will make it possible to optimize these systems and identify factors that contribute to program success.
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.