{"231121":{"#nid":"231121","#data":{"type":"news","title":"Building the Future Power Grid:  Researchers Tackle Energy Challenges with Technology Development and Policy Analysis","body":[{"value":"\u003Cp\u003EOn a warm afternoon in August 2003, a high-voltage power line in a rural area of Ohio brushed against some untrimmed trees, tripping a relay that turned off the power it was carrying.\u0026nbsp; As system operators tried to understand what was happening, three other lines sagged into trees and were also shut down, forcing other power lines to shoulder the extra burden until they also tripped off, starting a cascade of failures throughout southeastern Canada and eight northeaster U.S. states.\u003C\/p\u003E\u003Cp\u003EAlmost 10 years later, out electric power system continues to be challenged, by increasing demands of a digital society, the need to accommodate renewable energy generation, growing threats to infrastructure security and concerns over global climate change. The technology for a smart grid \u2013 with a two-way flow of electricity and information between utilities and consumers \u2013 could help address these challenges, but technical, regulatory and financial obstacles have slowed its deployment.\u003C\/p\u003E\u003Cp\u003EResearchers at Georgia Tech are helping to advance the smart grid.\u0026nbsp; They are developing technologies, creating methodologies and analyzing policies that will allow for integration of renewable energy sources and electric vehicles in the grid, with dynamic electricity pricing, and improved assessment and monitoring of the grid and its components.\u0026nbsp; Here are some highlights of how researchers at the Georgia Tech Stewart School of Industrial \u0026amp; Systems Engineering (ISyE) and their colleagues are researching and studying these issues.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EIntegrating Renewables into the Grid\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EThe electricity grid is a large, complex system of power generation, transmission and distribution.\u0026nbsp; High-voltage transmission lines carry power from large power plants to load center hundreds of miles away.\u0026nbsp; Next, lower-voltage distribution systems draw electricity form the transmission lines and distribute it to individual customers.\u0026nbsp; This long-standing electricity paradigm is being challenged as the grid becomes equipped with advanced sensing, communication, and control systems, and as an increasing quantity of power is generated by renewable sources.\u003C\/p\u003E\u003Cp\u003EWind and sunshine constantly ebb and flow with the slightest weather shifts, creating a variable supply.\u0026nbsp; So even when the renewables are going strong, conventional power plants must always be ready to step in and carry the load. Renewable energy sources \u2013 wind, sun, water, wood, organic waste, organic waste, and geo thermal \u2013 generated about 12 percent of the electricity in the United States in 2012. Increasing that percentage will require redesign of the power grid control architecture, scheduling framework and market mechanisms to balance supply and demand in the presence of these energy sources.\u003C\/p\u003E\u003Cp\u003EIntegrating renewable electricity into the grid requires a transition by the electric industry from a centralized control architecture to a more distributed and flexible one that allows many actors to participate. To help accomplish that, Georgia Tech researchers in 2012 received a three-year, $2 million grant from the U.S. Department of Energy\u2019s Advanced Research Projects Agency-Energy (ARPA-E) to develop and demonstrate a distributed electric power grid that would support high levels of renewable energy generation and storage.\u003C\/p\u003E\u003Cp\u003EThe architecture is based on the emerging concept of electricity \u201cprosumers\u201d \u2013 a combination of the words \u201cconsumer\u201d and \u201cproducer\u201d \u2013 which are economically motivated small-scale energy ecosystems that can consume, produce, and store electricity. For example, prosumers could include homeowners who consume energy from the grid while also producing power onsite from solar panels on their homes\u2019 roofs that feeds back into the grid.\u003C\/p\u003E\u003Cp\u003E\u201cThe power network from generation to transmission and distribution to consumption, needs to undergo the same kind of architectural transformation that computing and the communications network have gone through in the past few decades,\u201d said \u003Cstrong\u003ESantiago Grijalva\u003C\/strong\u003E, associate director for the electricity at the Strategic Energy Institute and the Georgia Power Distinguished Professor in the School of Electrical and Computer Engineering (ECE). \u201cWe are taking one step toward transformation by developing a reliable architecture that will allow the electricity industry to operate with characteristics similar to the Internet \u2013 distributed, flat, layered, and scalable.\u201d\u003C\/p\u003E\u003Cp\u003ETo develop the architecture, Grijalva is collaborating with \u003Cstrong\u003EMarilyn Wolf\u003C\/strong\u003E, the Farmer Distinguished Chair in Embedded Computing Systems and a Georgia Research Alliance Eminent Scholar in ECE; Magnus Egerstedt, the Schlumberger Professor in ECE and a robotics expert; and \u003Cstrong\u003EShabbir Ahmed\u003C\/strong\u003E, a professor in ISyE.\u0026nbsp; The system will be backward compatible with the current electricity industry model, deployable by incrementally enabling prosumer services and interoperable with emerging smart grid technologies.\u003C\/p\u003E\u003Cp\u003EThe system relies on a computational cyber infrastructure and an autonomous secure prosumer energy scheduler that allows small-scale producers to offer energy and grid services based on their capabilities and desire to achieve their sustainability, efficiency, reliability, and economic objectives, while contributing to system-wide reliability and efficiency goals.\u0026nbsp; The researchers have teamed with industry partners ISISoft, PJM, Midwest ISo, and Duke Energy to demonstrate the architecture and software using realistic utility datasets. They are also exploring commercialization opportunities for the technology.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ECraig Tovey, \u003C\/strong\u003Ethe David M. McKenny Family Professor in ISyE, is taking an inverse optimization approach to determining the least expensive way for a utility company to produce, store, and use electricity to meet demand in an area that contains prosumers.. Tovey and \u003Cstrong\u003ETanguy Hubert\u003C\/strong\u003E, and electrical and computer engineering graduate student, are developing a computational model to determine what prices to offer small-scale producers to provide enough incentive that they will make production, storage, and use choices consistent with utility company\u2019s optimal production plan.\u003C\/p\u003E\u003Cp\u003E\u201cTo solve this real-world inverse optimization problem, we need to decide what action we want the prosumer to take so that the overall goal is to achieve and then determine what price to offer so that when they minimize their own costs, they will select the action that is optimal for the general welfare,\u201d said Tovey.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAndy Sun\u003C\/strong\u003E, assistant professor, has been collaborating with researchers at the Massachusetts Institute of Technology and ISO New England to create an adaptive optimization model that makes robust unit commitment decision and ensures system reliability, while considering real-time uncertainly from renewable energy.\u003C\/p\u003E\u003Cp\u003E\u201cWind and solar energy sources are intermittent and uncertain because they are greatly impacted by slight changes in weather and because predicting wind or sunshine amounts a day ahead can be difficult,\u201d said Sun. \u201cUnlike coal or natural gas plants, when wind farm is scheduled to generate 100 megawatts of electricity at 7 a.m., there is no guarantee that amount of power will be produced.\u201d\u003C\/p\u003E\u003Cp\u003EWith support from ISO New England, the team tested its model on the large-scale system operated by the organization and compared its model with the current approach of overcommitting generators to create a \u201cjust \u2013in-case\u201d reserve.\u0026nbsp; Reserves can be expensive to maintain and ineffective due to the mismatch of supply and demand. The adaptive model demonstrated sizable savings on average operating and total costs and significantly reduced the volatility of the operating cost. A paper on the model was published in the February 2013 issue of the journal \u003Cem\u003EIIE Transactions on Power Systems\u003C\/em\u003E.\u003C\/p\u003E\u003Cp\u003EIn Europe, power exchanges run the day-ahead auctions, rather than independent systems operators, but the exchanges consider network constraints regarding system feasibly and reliability provided by the system operators.\u0026nbsp; \u003Cstrong\u003ESebastian Pokutta\u003C\/strong\u003E, ISyE assistant professor, and researchers from Friedrich-Alexander-Universitat-Erlangen-Nurnberg in Germany, created a model of the European electricity market, with support from the German Stock Exchange \u201cDeutsche Borse Frankfurt.\u201d\u003C\/p\u003E\u003Cp\u003EDetermining the price of power in Europe has recently become more difficult with power market coupling, an initiative to integrate transmission allocation and power trading across national borders so that cheaper electricity generation in one country can meet demand and reduce prices in another country.\u003C\/p\u003E\u003Cp\u003E\u201cWhile market coupling creates a more efficient market because of a strong interaction between price zones, it creates a very challenging real-world optimization problem that needs to be solved daily,\u201d said Pokutta. \u201cThe market coupling optimization problem involves demand and supply orders of different exchanges that need to be matched to maximize the total gains from trade.\u201d\u003C\/p\u003E\u003Cp\u003EPokutta and his colleagues analyzed optimization techniques for determining the price of electricity that would maximize the financial surplus of all participants, while considering quantity and price constraints. The algorithms matched energy demand and supply for 24 hours and calculated all market prices, net positions, and cross-border flows at the same time.\u003C\/p\u003E\u003Cp\u003EMembers of the European Union aim to deliver 20 percent of their energy from renewable sources, which is based on a target in the European Renewables Directive of 2008. The increase in renewable generation will require an intraday market that will allow for adjustments after the closure of the day-ahead market.\u0026nbsp; Pokutta plans to create an intraday market model and combine the market models he has developed with atmospheric models to consider air quality, sustainability and energy generation together.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EExamining the Effect of Electric Vehicles on the Grid\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EElectric vehicles could make it easier and cheaper to have renewables \u2013 particularly wind energy \u2013 on the grid and make it easier to manage electricity with its peaks at high demand times, according to the preliminary findings of a new study.\u0026nbsp; The study was conducted by \u003Cstrong\u003EValerie Thomas\u003C\/strong\u003E, the Anderson Interface Associate Professor of Natural Systems at ISyE; \u003Cstrong\u003EDeepak Divan\u003C\/strong\u003E, a professor in the School of Electrical and Computer Engineering; and their graduate students \u003Cstrong\u003EDong Gu Choi\u003C\/strong\u003E and \u003Cstrong\u003EFrank Kreikebaum\u003C\/strong\u003E.\u003C\/p\u003E\u003Cp\u003EThe researchers modeled the electricity system in six eastern and midwestern regions of the United States and are examining the interplay among the use, availability, and cost of different energy sources in those regions and electric vehicle adoption levels, electric vehicle charging methods, fuel economy standards, and renewable portfolio standards. Initial results from the study show how the time of day that users charge their electric vehicles affects how much electricity must be generated and the sources and costs of that power.\u003C\/p\u003E\u003Cp\u003E\u201cOur preliminary findings indicate that controlled charging of electric vehicles reduces cost and makes it significantly less expensive to have large amounts of renewables in the electric system,\u201d said Thomas. \u201cThe main cost saving is from reduced electric system capacity requirements.\u201d\u003C\/p\u003E\u003Cp\u003EControlled charging occurs when a driver plugs in a vehicle after completing the last trip of the day, but charging doesn\u2019t begin until off-peak nighttime or early-morning hours when the cost of electricity is lowest.\u0026nbsp; This contrasts with uncontrolled charging, when charging commences immediately upon plugging in the vehicle.\u0026nbsp; Additional findings of the study detail the effects of electric vehicle adoption levels, electric vehicle charging methods, fuel economy standards, and renewable portfolio standards on gasoline consumption, electricity cost, greenhouse gas emissions, and consumer cost. The study is supported by the Intelligent Power Infrastructure Consortium, a university-industry-utility consortium that fosters and accelerates the development and adoption of early-stage, high-risk and high-impact technologies in power applications.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAssessing the Condition of the Grid\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EPredicting the degradation and remaining useful life of generators, transformers, and transmission lines could significantly improve the performance of the grid and reduce maintenance costs.\u0026nbsp; \u003Cstrong\u003ENagi Gebraeel\u003C\/strong\u003E, associate professor at ISyE, is developing methods for monitoring the degradation of power grid components and predicting their remaining lifetimes.\u003C\/p\u003E\u003Cp\u003E\u201cRecent advances in sensor technology and wireless communication have enabled us to develop innovative methods for indirectly monitoring the health of different engineering systems and using that information in decision-making processes,\u201d said Gabraeel.\u003C\/p\u003E\u003Cp\u003EGabraeel has developed models that use data from real-time sensor measurements \u2013 such as vibration, temperature, insulation degradation, and partial discharge \u2013 to calculate and continuously revise the amount of remaining useful life of mechanical systems based on their current condition.\u003C\/p\u003E\u003Cp\u003E\u201cWe want to ensure the power grid remains reliable,\u201d said Gebraeel. \u201cPower utilities can no longer rely on time- or usage-based maintenance policies for generators or transformers. They need to be able to monitor the units in operation for up-to-date information on their condition and functionality to avoid unexpected failure.\u201d\u003C\/p\u003E\u003Cp\u003E---\u003C\/p\u003E\u003Cp\u003EThis article, written by Abby Robinson, has been excerpted from the full story that appears in the Spring-Summer 2013 issue of \u003Cem\u003EResearch Horizons\u003C\/em\u003E.\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EResearch surrounding smart grid issues is a major focus of energy and sustainable infrastructure studies at Georgia Tech.\u0026nbsp; The Stewart School of Industrial \u0026amp; Systems Engineering plays a strong role in researching and studying these issues.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":"","uid":"27868","created_gmt":"2013-08-22 14:11:07","changed_gmt":"2016-10-08 03:14:46","author":"Lizzie Millman","boilerplate_text":"","field_publication":"","field_article_url":"","dateline":{"date":"2013-08-22T00:00:00-04:00","iso_date":"2013-08-22T00:00:00-04:00","tz":"America\/New_York"},"extras":[],"hg_media":{"231111":{"id":"231111","type":"image","title":"A study led by ISyE professor Valerie Thomas showed that electric vehicles could make it easier and cheaper to have renewable energy in the grid.","body":null,"created":"1449243602","gmt_created":"2015-12-04 15:40:02","changed":"1475894903","gmt_changed":"2016-10-08 02:48:23","alt":"A study led by ISyE professor Valerie Thomas showed that electric vehicles could make it easier and cheaper to have renewable energy in the grid.","file":{"fid":"197546","name":"130402cr082.jpg","image_path":"\/sites\/default\/files\/images\/130402cr082_0.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/130402cr082_0.jpg","mime":"image\/jpeg","size":6782480,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/130402cr082_0.jpg?itok=aI0hcFFN"}},"231101":{"id":"231101","type":"image","title":"Andy Sun, assistant professor at ISyE, is collaborating with other research groups on an adaptive optimization model that considers the uncertainty of renewable resources in systems capacity and reliability.","body":null,"created":"1449243602","gmt_created":"2015-12-04 15:40:02","changed":"1475894903","gmt_changed":"2016-10-08 02:48:23","alt":"Andy Sun, assistant professor at ISyE, is collaborating with other research groups on an adaptive optimization model that considers the uncertainty of renewable resources in systems capacity and reliability.","file":{"fid":"197545","name":"130415ar099.jpg","image_path":"\/sites\/default\/files\/images\/130415ar099_0.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/130415ar099_0.jpg","mime":"image\/jpeg","size":6904029,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/130415ar099_0.jpg?itok=kRSP5YC3"}}},"media_ids":["231111","231101"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[{"id":"134","name":"Student and Faculty"}],"keywords":[{"id":"479","name":"Green Buzz"},{"id":"1191","name":"industrial engineering"},{"id":"365","name":"Research"},{"id":"623","name":"Technology"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:barbara.christopher@isye.gatech.edu\u0022\u003E\u003Cstrong\u003EBarbara Christopher\u003C\/strong\u003E\u003C\/a\u003E\u003Cbr \/\u003EIndustrial and Systems Engineering\u003Cbr \/\u003E\u003Cstrong\u003E404.385.3102\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"email":["bchristopher@isye.gatech.edu"],"slides":[],"orientation":[],"userdata":""}}}