A smart grid is made possible by applying sensing, measurement and control devices with two-way communications to electricity production, transmission, distribution, and consumption parts of the power grid that communicate information about grid condition to system users, operators and automated devices, making it possible to dynamically respond to changes in grid condition. A smart grid is eventually a wireless hybrid network, and its capacity and achievability are studied. An information theoretic approach for multiple access channels is applied to increase the throughput capacity, and three tasks are studied: 1) smart grid versus smart home, 2) square network versus smart grid network, and 3) base stations with antenna array. The achievability of the capacity is studied via analyzing the rate of smart grid which consists of multimodal sensors/meters. Different sensor modalities may be independent or dependent, and some preliminary fundamental results are derived and are subsequently applied to smart grid wireless network.

One study conducted by the US Department of Energy concludes that internal modernization of US grids with smart grid capabilities would save between 46 and 117 billion dollars over the next 20 years. With the segments set to benefit the most will be smart metering hardware sellers and makers of software used to transmit and organize the massive amount of data collected by meters. The capacity study performed in this project provides the upper bound for the smart grid to transmit the massive amount of data, and the achievability study provides an efficient way to organize the massive amount of data collected by meters.

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University of Texas at Arlington
United States
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