computing and computing architecture to maximize grid flexibility-九游会平台
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  • 清华大学电机系
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    清华大学电机系本科生
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    清华大学能源互联网创新研究院
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    清华四川能源互联网研究院
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特邀报告 2017.1.17 iii-102 9:00~12:00

zhenyu (henry) huang (m’01 sm’05 f’17 ieee) he is currently chief engineer and technical group manager at pacific northwest national laboratory, richland, washington, usa. his research interests include high performance computing, phasor technology, and power system stability and simulation. dr. huang is a fellow of ieee and active in several ieee power and energy society (pes) technical committees.

this talk will present recent advancements in applying high performance computing to power grid applications. extending from computing, a data-driven computing architecture is proposed to link measurements to computation and then to visualization, so computing methods and tools can leverage new data sources and account for new grid behaviors in order to ensure a reliable, efficient, and secure future power grid. it would harmonize the grid evolution and the information revolution and convert data to actionable information. examples will be provided to illustrate the concept and value of such an architecture. the examples cover real-time stability assessment, transmission congestion management, and uncertainty quantification. in these examples, significant flexibility can be identified even when the grid is subject to many constraints. this will greatly facilitate the adoption of new generation and loads such as renewable energy and demand response.

联系人:陈颖

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