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Computational intelligence techniques for a smart electric grid of the future
Jiang Z.  ISNN 2009 (Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks--Part III, Wuhan, China, May 26-29, 2009)1191-1201.2009.Type:Proceedings
Date Reviewed: May 28 2010

The electric power grid in the US is built upon mature technologies, some of them dating back to the 1930s. A smart grid applies modern computer and communications technologies to bring the grid into the 21st century. Smart grid goals include enhanced reliability and security; robustness to outages (whether caused by nature or human attacks); accommodation of distributed energy resources, including green technologies (the current grid is built around centralized generation at power plants); demand-responsive techniques to shave peak demand; and interfaces to smart appliances and storage devices.

The paper begins with a high-level overview of the smart grid’s functions. Then, it identifies candidate technologies for implementing these functions. The technologies are structured into a five-part taxonomy: smart sensing, metering, and communications infrastructure; autonomous control and adaptive protection; advanced data management and visualization; intelligent interfaces with distributed resources and markets; and decision support systems for system operation and planning. In general, these technologies provide real-time information on the state of the grid and assist in making intelligent decisions in response to that information.

This well-written paper provides a good high-level overview of smart grid technologies; however, the content is not particularly novel. For example, the US Department of Energy’s National Energy Technology Laboratory (NETL) provides a more in-depth look at many of the same technologies on its Web site (http://www.netl.doe.gov/smartgrid/). The key to a smart grid’s success is to define an architecture that accommodates interoperability among a heterogeneous mix of technologies, and that allows the grid to evolve as newer technologies and functions are introduced.

Reviewer:  A. E. Salwin Review #: CR138052 (1103-0281)
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