DDDAS-based Communication in Distributed Smartgrid Networks

Abstract

The U.S. military spends over nine billion dollars annually to provide electrical power to its vast array of installations throughout the U.S. In an effort to reduce those costs and improve the security of their installations, the military in conjunction with the Department of Energy has started to install renewable energy infrastructure at various department owned facilities. One method to integrate these resources is by installing micro grids. Micro grids, however, are still reliant on a local utility for the vast majority of its electricity, and necessitate design of powerful decision-making units to function at its full utility allowing for isolation/desolation processes when an emergency occurs. In this work, we introduce a two-stage real-time decision-making and communications structure for integrating micro grids into a larger smart grid network using dynamic data driven adaptive simulation techniques. Through its demand prioritization scheme, the proposed framework has the capability to adjust to various micro grid types that have the potential for deployment in various municipalities throughout the country. Preliminary experiments have shown that different micro grid enabling parties may achieve significant cost savings by integrating micro grids into a larger regional or national smart grid across the U.S

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