On 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. 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 northeastern U.S. states.
All told, 50 million customers lost power for up to two days in the biggest blackout in North American history. For many, this blackout served as a wake-up call signaling the fragility of our electric energy grid.
Almost 10 years later, our 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 – with a two-way flow of electricity and information between utilities and consumers – could help address these challenges, but technical, regulatory and financial obstacles have slowed its deployment.
Researchers at Georgia Tech are helping advance the smart grid. They are developing technologies, creating methodologies and analyzing policies that will allow for integration of renewable energy sources and electric vehicles into the grid, with dynamic electricity pricing, and improved assessment and monitoring of the grid and its components. The researchers are supported by research resources that include the Strategic Energy Institute (SEI).
SEI provides the infrastructure and environment for research initiatives that improve the sustainability, affordability and reliability of the entire energy cycle – from generation to distribution to use.
“Sustainable and reliable electric energy provided at reasonable cost is essential to the economic future of our state, region and nation,” said Tim Lieuwen, executive director of SEI. “In collaboration with our industry partners, Georgia Tech is helping advance smart grid and related technologies that will help address the challenges of meeting this demand.”
Integrating Renewables into the Grid
The electricity grid is a large, complex system of power generation, transmission and distribution. High-voltage transmission lines carry power from large power plants to load centers hundreds of miles away. Next, lower-voltage distribution systems draw electricity from the transmission lines and distribute it to individual customers. 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.
Wind and sunshine constantly ebb and flow with the slightest weather shifts, creating a variable supply. 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 – wind, sun, water, wood, organic waste and geothermal – 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.
Integrating 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’s Advanced Research Projects Agency-Energy (ARPA-E) to develop and demonstrate a distributed control architecture and technologies for the electric power grid that would support high levels of renewable energy generation and storage.
The architecture is based on the emerging concept of electricity “prosumers” – a combination of the words “consumer” and “producer” – 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’ roofs that feeds back into the grid.
“The 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,” said Santiago Grijalva, associate director for electricity at SEI and Georgia Power Distinguished Professor in the School of Electrical and Computer Engineering. “We are taking one step toward that transformation by developing a reliable architecture that will allow the electricity industry to operate with characteristics similar to the Internet – distributed, flat, layered and scalable.”
To develop the architecture, Grijalva is collaborating with Marilyn Wolf, the Farmer Distinguished Chair in Embedded Computing Systems and a Georgia Research Alliance Eminent Scholar in the School of Electrical and Computer Engineering; Magnus Egerstedt, the Schlumberger Professor in the School of Electrical and Computer Engineering and an expert in networked robotics; and Shabbir Ahmed, a professor in the H. Milton Stewart School of Industrial and Systems Engineering. 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.
The 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 systemwide reliability and efficiency goals. The researchers have teamed with industry partners OSISoft, 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.
Craig Tovey, the David M. McKenney Family Professor in the School of Industrial and Systems Engineering, 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 Tanguy Hubert, an electrical and computer engineering graduate student advised by Grijalva, 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 the utility company’s optimal production plan.
“To solve this real-world inverse optimization problem, we need to decide what action we want the prosumers to take so that the overall goal is achieved 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,” said Tovey.
The addition of renewable energy to the grid also affects the day-ahead auction process used to determine the price of electricity in regions of the United States with wholesale markets. In a day-ahead electricity auction, participants bid today for electricity that they want to buy or sell the following day. Then, independent system operators find the equilibrium price based on the submitted bids. They also create a day-ahead schedule detailing which generators will be turned on and how much electricity each generator will produce the following day, a practice referred to as the unit commitment process. Higher use of renewable generation resources introduces challenges of uncertainty and intermittency into these processes.
As part of the Georgia Tech-led National Science Foundation Sustainable Infrastructure for Energy and Water Systems project, School of Electrical and Computer Engineering professor Miroslav Begovic is designing methodologies to determine how uncertainty and large swings in production could be met by other power plants. With this information, he will evaluate how much solar photovoltaic plant capacity can be safely installed in the U.S. power system without jeopardizing the reliability of the supply.
Andy Sun, an assistant professor in the School of Industrial and Systems Engineering, 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 decisions and ensures system reliability, while considering real-time uncertainty from renewable energy.
“Wind 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,” said Sun. “Unlike coal or natural gas plants, when a 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.”
With 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 over-committing generators to create a “just-in-case” reserve. Reserves can be expensive to maintain and inefficient 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 IEEE Transactions on Power Systems.
In Europe, power exchanges run the day-ahead auctions, rather than independent system operators, but the exchanges consider network constraints regarding system feasibility and reliability provided by the system operators. Sebastian Pokutta, an assistant professor in the School of Industrial and Systems Engineering, and researchers from Friedrich-Alexander-Universität Erlangen-Nürnberg in Germany, created a model of the European electricity market, with support from the German Stock Exchange “Deutsche Börse Frankfurt.”
Determining 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.
“While 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,” said Pokutta. “The market coupling optimization problem involves demand and supply orders of different exchanges that need to be matched to maximize the total gains from trade.”
Pokutta 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.
Members 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. 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.
Examining the Effect of Electric Vehicles on the Grid
Electric vehicles could make it easier and cheaper to have renewables – particularly wind energy – 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. The study was conducted by Valerie Thomas, an associate professor in the School of Industrial and Systems Engineering and the School of Public Policy; Deepak Divan, a professor in the School of Electrical and Computer Engineering; and their graduate students Dong Gu Choi and Frank Kreikebaum.
The 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.
“Our 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,” said Thomas, who is the Anderson Interface Associate Professor of Natural Systems. “The main cost saving is from reduced electric system capacity requirements.”
Controlled charging occurs when a driver plugs in a vehicle after completing the last trip of the day, but charging doesn’t begin until off-peak nighttime or early-morning hours when the cost of electricity is lowest. This contrasts with uncontrolled charging, when charging commences immediately upon plugging in the vehicle. 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.
Bert Bras, a professor in the George W. Woodruff School of Mechanical Engineering, is collaborating with Ford Motor Company to examine how to optimize the driving and charging habits of people using Ford’s C-MAX Energi plug-in hybrids. To complete his assessment, Bras will use data from Ford’s MyFord Mobile app that provides real-time battery charge status and automatically schedules recharging at lower-cost, off-peak times.
Earlier research by Bras found that charging electric vehicles when renewables are online would be beneficial to the water supply because generating power from wind and solar sources requires significantly less water than traditional coal or nuclear power plants. This study was published in the December 2012 issue of the journal Energy Policy and was supported by the National Science Foundation and Georgia Tech’s University Transportation Center.
Bras is also collaborating with Ford on its MyEnergi Lifestyle initiative. The project, which launched at the Consumer Electronics Show in January 2013, showcases how combining renewable energy generation with time-flexible loads optimizes energy consumption in homes with plug-in vehicles and smarter, more-efficient home appliances. Bras, School of Mechanical Engineering professor Chris Paredis and School of Architecture professor Godfried Augenbroe created a computer model that calculates the electricity use of a typical family in their home for one year.
The researchers’ model predicted a 60 percent reduction in energy costs and a 55 percent reduction in carbon dioxide emissions from a single home by exchanging a gasoline car for an electric vehicle, adding a small photovoltaic array, and shifting activities – such as charging a plug-in vehicle or running a dishwasher – to off-peak nighttime or early-morning hours.
Assessing the Condition and Security of the Grid
The recent prolonged power outages in New York and New Jersey caused by Hurricane Sandy have shown how vulnerable America can be to losing its lights. In the United States, 149 power outages affecting at least 50,000 customers occurred between 2000 and 2004, a number that rose to 349 from 2005 to 2009. Heading off large-scale failures requires a view of grid operations that utility companies cannot currently get. Utilities receive a snapshot of what’s happening in the system every several minutes, which frequently is not quick enough when potentially catastrophic events can develop in a second.
Real-time measurement and management of grid components, both utility- and customer-owned, will help to accomplish the goal of optimally and securely operating the power grid. School of Electrical and Computer Engineering professor A.P. Sakis Meliopoulos and visiting professor George Cokkinides have developed a real-time monitoring system to protect, control, optimize and stabilize the power grid.
“Our approach for an autonomous, plug-and-play distributed control system is to use dynamic state estimation to continuously monitor the condition of grid components and use this information to determine if any action should be taken,” said Meliopoulos, who is also a Georgia Power Distinguished Professor and site director for the Power Systems Engineering Research Center (PSERC), a National Science Foundation Industry-University Cooperative Research Center.
In the infrastructure they have proposed, grid components are equipped with a universal monitoring, protection and control data acquisition unit. The unit is constructed from a phasor measurement unit, a complex number that represents both the magnitude and phase angle of the sine waves found in electricity. The technology collects the measurements that are location- and time-tagged and transmits them via local area network to create a real-time model of the system and estimate the system’s operating condition, a process called dynamic state estimation. Because the relaying and recording equipment available today contains phasor measurement units, the proposed distributed state estimation system can be implemented in any modern substation.
In August 2012, the researchers demonstrated their distributed dynamic state estimation system on the Water and Power Authority’s five-substation system in St. Thomas, U.S. Virgin Islands, and achieved a dynamic state estimation rate of 60 times per second. They also recently installed their system in Pacific Gas and Electric’s (PG&E) Midway and Vaca-Dixon Substations and in Southern Company’s Klondike and Scherer Substations. At the New York Power Authority’s Blenheim-Gilboa Power Project, the researchers are using state estimation results to monitor the system and predict imminent instabilities.
This research is supported by the U.S. Department of Energy; New York Power Authority; PG&E; GE Energy; U.S. Virgin Islands Water and Power Authority; NEC; Southern Company, and the PSERC.
Miroslav Begovic, a professor in the School of Electrical and Computer Engineering, analyzes a phenomenon called voltage collapse, which can afflict transmission networks and cause a blackout when the demand reaches a critical level, even if there is sufficient power generation to meet the demand. The Northeast Blackout of 2003 led utilities and the government to team up to install a phasor network throughout the United States. The North American SynchroPhasor Initiative expects that approximately 1,000 phasor measurement units will be in place and networked by the end of 2014.
By placing phasor measurement units at critical points in the network, such as in certain substations, operators can assess system stress by measuring voltage and current phasors. Begovic worked with industry to develop a methodology that uses the data collected from phasor measurement units to quickly assess the state of the power system and determine in real time whether it is in danger of a blackout.
“The uniqueness of the methodology is that it only relies on a single measurement point in a single location to gain knowledge of what’s happening across the entire system,” said Begovic. “While the accuracy of the methodology is reduced, our ability to monitor the state of the system and quickly employ corrective actions to avoid a collapse is increased.”
This research is supported by ABB through its membership in the National Electric Energy Testing Research and Applications Center (NEETRAC). NEETRAC provides an array of analytical, engineering, research and testing services to help improve electric grid reliability and efficiency. Part of the School of Electrical and Computer Engineering, NEETRAC is supported by 40 equipment manufacturers and utility companies that serve more than 60 percent of U.S. electric customers.
NEETRAC and the U.S. Department of Energy supported a project aimed at understanding how to effectively use diagnostic technologies to establish the condition of underground cable circuits and locate degradation that may cause cables to fail. Cable systems are designed to have a lifetime of 30 to 40 years with high reliability, but many underground cable systems installed in the United States are reaching the end of their design lives.
“We did not want to develop our own diagnostic testing technology and compete with the equipment already on the market,” said Rick Hartlein, director of NEETRAC. “We wanted to use our neutral perspective and highly analytical capabilities to analyze commercial devices and determine whether their measurements were providing a true indication of the condition of a cable circuit.”
NEETRAC research engineers Nigel Hampton and Joshua Perkel collected dielectric loss and partial discharge measurements at different voltages and frequencies within cable insulation systems to develop decision tools for utilities to use to determine whether a circuit needed to be repaired or replaced. Their methodology for testing the condition of underground cables was incorporated into an IEEE industry standard.
Steve Potter, an associate professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University, and Ronald Harley, a Regents’ professor in the School of Electrical and Computer Engineering, are studying how neural networks integrate and respond to complex information. They expect this work to inspire new methods for managing the country’s ever-changing power supply and demand.
In collaboration with Ganesh Kumar Venayagamoorthy, Duke Energy Distinguished Professor of Electrical and Computer Engineering at Clemson University, the researchers have trained a network of rat cortical neurons in a petri dish to recognize and respond to voltage and speed signals from a simulated power grid. They are using the results from these experiments to develop bio-inspired artificial neural networks that will control synchronous generators connected to a power system. This project is supported by the National Science Foundation.
Predicting the degradation and remaining useful life of generators, transformers and transmission lines could also significantly improve the performance of the grid and reduce maintenance costs. Nagi Gebraeel, an associate professor in the School of Industrial and Systems Engineering, is developing methods for monitoring the degradation of power grid components and predicting their remaining lifetimes.
“Recent 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,” said Gebraeel.
Gebraeel has developed models that use data from real-time sensor measurements – such as vibration, temperature, insulation degradation and partial discharge – to calculate and continuously revise the amount of remaining useful life of mechanical systems based on their current condition.
“We want to ensure the power grid remains reliable,” said Gebraeel. “Power 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.”
In addition to asset management concerns, utilities are also worried about cyber threats. A National Research Council report, completed in 2007 but declassified by the Department of Homeland Security last November, warned that a coordinated strike on the electric grid could have devastating effects on the American economy. Researchers in the Georgia Tech Research Institute (GTRI) and NEETRAC are investigating potential cybersecurity gaps in utility substation devices.
“Many older pieces of equipment in utility substations were not built with security in mind,” said Andrew Howard, a GTRI research scientist. “This equipment is now becoming Internet-enabled as part of the smart grid, and this presents a lot of security concerns.”
Howard, GTRI research engineer David Huggins and NEETRAC research engineer Carson Day are developing strategies for testing and evaluating security vulnerabilities in intelligent electronic devices, which receive data from sensors and can issue control commands, such as tripping circuit breakers or changing voltage levels. In laboratory tests, the researchers uncovered security vulnerabilities in which some devices could be turned off, potentially by persons without privileged access to them.
“We found a way that we could flood the devices with certain types of information so that they would turn themselves off,” said Huggins. “If someone did that in the real world, he or she could knock out a substation and the power could go down.”
GTRI researchers have helped secure and protect devices that are deployed throughout U.S. government and corporate networks for years. They are leveraging their experience in network device security and applying the techniques, tactics and procedures they learned from the Internet world to the power grid and the energy community.
Analyzing State, National and International Energy Policies
In recent years, a number of U.S. states, the federal government and other countries have adopted or are considering energy-related laws, regulations, programs, and voluntary or mandatory requirements aimed at improving and enhancing power systems. This includes programs that promote renewable energy development or energy efficiency, policies that support development and deployment of smart grid technologies, and laws mandating renewable portfolio standards. Researchers in Georgia Tech’s School of Public Policy, Sam Nunn School of International Affairs and School of Economics have analyzed these policies and uncovered their similarities and differences.
Japan was resistant to adopting smart grid technologies for years. Because 10 regional utilities held a monopoly on the power supply, there was little discussion of the smart grid. Then came Fukushima in March 2011. Following a major earthquake, a tsunami disabled the power supply and cooling of three Fukushima Daiichi reactors, causing a nuclear accident. Because only two of Japan’s 50 nuclear reactors are currently operating, the country must now rely more heavily on renewable energy sources – and that requires a smart grid.
Brian Woodall, an associate professor in the School of International Affairs, has studied energy policy in Japan dating back to the 1950s. Now, he’s analyzing Japanese energy strategy and the policies that will foster the development of a smart grid and the effective and sustained use of renewable energy in Japan. Collaborating with Woodall on this work are School of International Affairs associate professor Adam Stulberg, associate professor Mark Zachary Taylor, senior research associate William Foster and graduate student Liz Dallas; School of Mechanical Engineering professor Glenn Sjoden; and School of Industrial and Systems Engineering associate professor Valerie Thomas.
In the 1980s and 90s, Japan’s “Rooftop Program,” which subsidized consumers who put solar panels on their homes, became the world’s first large-scale development of photovoltaic technology and demonstrated its feasibility as an energy source. Today, the government is encouraging the creation of large-scale solar farms and geothermal energy. In 2012, the Japanese government lifted its decades-old ban to allow geothermal projects in national parks and monuments and earmarked $67 million for a program to aid geothermal power developers through capital injections and debt guarantees. By 2030, the Japanese government aims to triple renewable energy sources, which today make up about 10 percent of the country’s power supply.
“To achieve this goal, the government will likely need to increase its support for the introduction of new renewable technologies through tax reductions, subsidies, and support for research and development,” said Woodall. “Japan may also need to create new energy policies that promote the development of smart cities and the installation of smart meters and other energy management systems.”
School of Public Policy professor Marilyn Brown and graduate student Shan Zhou recently analyzed smart grid policies in Great Britain, Italy, China, Japan, South Korea and the United States. In a study published in the March/April 2013 issue of the journal Wiley Interdisciplinary Reviews: Energy and Environment, they found that governments have overcome various financial, regulatory and technical barriers to facilitate grid modernization.
“Currently, government is still the key player in smart grid investments. Our research suggests the need for a policy framework that attracts private capital investment, especially from renewable project developers and communication and information technology companies,” said Brown.
The study also revealed growing worldwide consensus that smart meters are an essential enabler of grid modernization. A smart meter can measure real-time electricity consumption and communicate the information to the utility and the consumer. Britain, Italy and South Korea expect full adoption of smart meters by 2020. In the United States, many utilities used Smart Grid Investment Grants (with a total public investment of about $4 billion) to pay up to 50 percent of costs to install advanced metering infrastructures.
South Korea’s Smart Grid Road Map 2030 plans to spend $25 billion to facilitate the development and construction of smart grid technologies for the power grid, vehicles, and renewables. In contrast, China’s 2012 plan for its smart grid emphasizes power generation and transmission, reflecting its relatively underdeveloped power distribution system and the challenge the Chinese electricity market faces in developing effective interaction mechanisms between customers and utility companies.
Feed-in tariffs, which pay a premium to small-scale renewable electricity producers for the purchase of their renewable energy, are popular worldwide for encouraging renewable electricity generation. Britain introduced feed-in tariffs for small low-carbon electricity generation facilities through its 2008 Energy Act. Japan, China and Italy have feed-in tariffs to develop domestic markets for solar power. A few utilities in the United States also offer feed-in tariffs for solar power purchases.
Although smart grid policies vary across the United States, Brown and Zhou found that most states have implemented interconnection standards and net metering policies, although constraining limits also exist in some states. Net metering allows customers to connect the power they generate to utility grids to offset their electricity consumption and sell excess generation to the utility. Dynamic pricing programs, which provide real-time prices to customers and let them decide when to consume electricity based on cost, are also widely used in industrial and commercial sectors of the United States, but are just beginning to become available to residential customers.
Daniel Matisoff, an assistant professor in the School of Public Policy, is examining the factors that drive states to adopt policies promoting renewable energy development or energy efficiency. Because the vast majority of literature suggests that states either learn from each other or compete with each other, Matisoff and graduate student Jason Edwards are currently investigating two competing theories about what drives renewable energy policy adoption at the state level: the internal characteristics of the state or the fact that other states have already adopted the policy. The researchers are assessing three highly competitive policies aimed at economic development and five low-competition policies.
“Our preliminary findings show that states do not tailor their policies to match their geographic characteristics,” said Matisoff. “More than anything else, renewable energy policy and energy development appear to be outcomes of a political market.”
States with larger numbers of carbon intensive industries are less likely to adopt renewable energy programs, while states with more liberal populations and stronger environmental interest groups are more likely to adopt programs. In addition, states with more liberal populations, higher levels of air pollutants, more renewable potential and a less carbon dioxide-intensive industry make more attempts to adopt renewable energy policies.
Renewable portfolio standards have become a popular tool for state governments to promote renewable electricity generation and to decrease carbon dioxide emissions. A renewable portfolio standard is a mandate that retail electricity providers purchase a specified fraction of their electricity sales from renewable sources. By March 2013, 29 states, the District of Columbia, Puerto Rico, and the Northern Mariana Islands had passed mandatory renewable portfolio standards; and eight states, Guam, and the U.S. Virgin Islands had passed voluntary renewable portfolio standards.
Erik Johnson, an assistant professor in the School of Economics, is estimating the long-run price elasticity of supply of renewable electricity generation. This is a measure of the responsiveness of the quantity of renewables supplied to a change in its price. It gives the percentage change in quantity demanded in response to a one percent change in price. The price elasticity is an important parameter for policymakers to determine the cost of carbon abatement from these policies relative to other methods of reducing carbon dioxide emissions.
Johnson’s preliminary findings suggest that renewable portfolio standards are an expensive way to decrease carbon dioxide emissions, costing more than six times more than a cap-and-trade program to reduce carbon dioxide emissions by 2.5 percent. In a cap-and-trade program, emissions allowances are allotted to polluters, and companies whose emissions exceed their allocations must either obtain extra allowances or buy credits from projects that cut greenhouse gas emissions.
Georgia Tech supports multidisciplinary research teams that are developing technologies and methodologies to improve the efficiency, performance and reliability of the power system. Researchers are also analyzing the policies that will promote the path toward creating the next generation of the electric utility grid. Together, they are all contributing to finding ways to keep the lights on.
The research described in this article has been supported by the National Science Foundation (NSF) under contracts EFR-0836046 (Sustainable Infrastructures for Energy and Water Supply) and EEC-0080012 (Power Systems Engineering Research Center) and by the Department of Energy (DOE) through contracts DE-OE0000117 (National Energy Technology Laboratory); DE-FC02-04CH11237 and DE-AR0000225. The conclusions and recommendations contained in the article are those of the authors and do not necessarily reflect the official positions of the NSF or DOE.