A Special Issue on Foundational Support Systems

For a downloadable copy of the June 2016 eNewsletter, please visit the IEEE Smart Grid Resource Center


 By Lisa Schwartz

As the U.S. electric industry undergoes significant changes in response to shifting market dynamics and regulations, a new series of reports by the Electricity Markets and Policy Group at Lawrence Berkeley National Laboratory is advancing the discussion by examining issues related to electric industry regulation and utility business models.

 By Yezhou Wang, Jianhui Wang and Dan Ton

In recent years, many blackouts have occurred as a result of natural disasters, including such well-known disasters as 2005’s Hurricane Katrina in the United States, Japan’s 2011 earthquake, and 2012’s Hurricane Sandy (also in the United States). Between 2003 and 2012, 679 U.S.-based power outages resulted from weather events that each affected more than 50,000 customers. Therefore, research on the power grid’s resilience to natural disasters is of major societal significance.

 By Mehmet Hazar Cintuglu and Osama Mohammed

The Integration of a variety of systems governed by different regulations and owned by different entities in the smart grid environment introduces an interoperability challenge. There is a lack for common data modeling in all levels of smart grid applications. Moreover, newly developed protocols and communication standards should take into consideration the interoperability of previously deployed equipment and existing power system communication protocols.

 By Mike Zhou, XueWei Shang, Lin Zhao, JianFeng Yan, DongYu Shi, and Ying Chen

After a decade of development, online dynamic security assessment (DSA) analysis has been widely used in the power dispatching control centers in China. The current online DSA system is a near real-time analysis system with speed in the order of minutes. The development of a fast real-time DSA system with speed in the order of seconds has been started with the focus on helping the operator to perform DSA analysis in real-time. An end-to-end optimization approach is used to minimize the DSA system overall round trip time, including data acquisition, data processing and computation. The transient stability analysis is performed by searching of the existing simulation study cases in the knowledge base, rather than the step-by-step time-domain simulation method. Big Data technologies, including in-memory computing, complex event processing, search and pattern-matching, and deep machine learning, will be introduced to the power grid dispatching control centers in China in the near future.

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