Implementation Status of Electric Distribution Systems in U.S. Smart Grid Projects Funded Under the 2009 American Recovery and Reinvestment Act

by Stephanie Oehler
As climate change continues to have a greater impact on individuals and habitats around the world, many nations are taking actions to reduce their impacts by minimizing greenhouse gas emissions. Modernization of electrical grids in order to increase efficiency, accommodate new sources of energy and technology, minimize losses, and ultimately reduce harmful emissions from high-polluting forms of energy production has become a priority for many countries. For example, the American and Chinese governments each contributed over seven billion U.S. dollars to national Smart Grid deployment in 2010, with numerous other developed countries investing similarly large amounts in their own electricity infrastructures. Ghosh et al. (2013) explored the current status of projects partially funded through the Smart Grid Investment Grant (SGIG)  and the Smart Grid Demonstration (SGDP) programs created under the American Recovery and Reinvestment Act (ARRA) of 2009. Through a quantitative analysis of customer profile and distribution circuit data collected by the Department of Energy (DOE) specific to the progress of implementation of federally funded Smart Grid projects, the authors were able to observe trends in the impacts of utility size and type of technology on status of completion of Electric Distribution Systems (EDS) modernization specifically. Using these data, the authors concluded that SCADA technology tended to be implemented more quickly than DA devices, regardless of utility size. In the future, this may have an impact on which technologies developers decide to use in upgrading electricity grids. 
Ghosh, S., Pipattanasomporn, M., Rahman, S., 2013. Technology deployment status of U.S. Smart grid projects — electric distribution systems. IEEE Innovative Smart Grid Technologies, 1—8.

                  There is a variety of Smart Grid technologies that improve communication between the supply and demand sides of the grid, increase the efficiency of electricity transmission, reduce consumption, and increase reliability.  Ghosh and colleagues at the Advanced Research Institute at Virginia Tech briefly explored the five types of projects that the 99 recipients of $3.5 billion in grants from the DOE through the SGIG program fell under. These projects improved Advanced Metering Infrastructure (AMI), Customer Systems (CS), Electric Distribution Systems (EDS), Electric Transmission Systems (ETS), and Equipment Manufacturing. Due to the interconnections between these operations, 39% of the projects incorporated several of them. However, a large percentage (57%) of projects were related to EDS, which focuses on the operations and communications of distribution technologies. The authors explored the different types, status of deployment, and significance of EDS projects. In 2009, $1.96 billion in federal funding was distributed to EDS projects which have been estimated by the U.S. Energy Information Administration to impact over 34 million consumers, 30 million of which are in the residential sector and comprise 23% of America’s total residential electricity consumers. The authors went on to define the parameters that they would refer to throughout the article as they evaluated the extent of implementation of various projects, which included the size of the utility as determined by the number of distribution circuits within a service area, ranging from Very Small ( under 50 substations) to Large (more than 500 substations). They considered two types of EDS technologies, DA devices and SCADA systems. DA devices include technologies such as automated feeder switches, automated capacitors, automated regulators, fault current limiters, smart relays, remote fault indicators, and monitoring systems; while SCADA systems are implemented in large, spread out systems where uniformity of operations and extensive communication efforts are critical. Ultimately, they examined the ratio between the number of substations that have the new technologies to the total number within each area. The ratio of substations integrating EDS technologies to baseline substations was much higher in those with SCADA systems than those with DA devices, and they were more completely implemented. The results for DA devices varied between utility sizes and appeared to be dependent on which technology was used in each specific situation. Overall, most projects that were partially funded by federal grant money through the SGIG program were near completion if they had used SCADA, and still progressing if they had used DA devices.

                  This quantitative case study will be useful as a model for systems progress as new technologies are implemented, particularly with respect to EDS projects. While this study focuses on the EDS side of the SGIG grant, there is much more to explore regarding the successes and failures of the other types of Smart Grid projects. Additionally, comparative quantitative studies offer the federal government a tool to evaluate the effectiveness of its investments and the results may direct investments in the future.

Noncooperative and Cooperative Demand

by Stephanie Oehler
Electricity production and usage are closely related with the impacts of climate change because many forms of energy come from the combustion of fossil fuels and emit high amounts of carbon dioxide into the atmosphere. Smart grids, electricity networks that incorporate communication devices and allow energy to flow both to and from consumers and producers in order to increase efficient energy usage, offer a promising solution to many problems that are associated with traditional energy grids. By accommodating individual energy producers and storers, in addition to traditional production methods, smart grids provide a necessary modernization of energy management systems. Atzeni et al. (2013) studied several optimization methods that cater to different types of users on the demand side of smart grids. Through day-ahead demand-side management, the authors monitored the behavior of noncooperative and cooperative energy users in order to determine which was more beneficial in reducing costs among consumers. Both simulations demonstrated that active electricity users had the potential to reduce costs by distributing generation and storage according to time-slot dependent rates, regardless of whether they were strategizing individually or within a group, thereby stabilizing the load throughout the day and improving predictability of aggregate demand.
Atzeni, I., Ordonez L., Scutari, G., Palomar, D., Fonollosa J., 2013. Noncooperative and cooperative optimization of distributed energy generation and storage in the demand-side of the smart grid.              IEEE Transactions on Signal Processing 61, 2454—2472.

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