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Climate change, the depletion of natural resources and rising energy costs have led to an increasing focus on renewable sources of energy. A lot of research has been devoted to the technologies used to extract energy from these sources; however, equally important is the storage and distribution of this energy in a way that is efficient and cost effective. Achieving this would generally require integration with existing energy infrastructure. The challenge of renewable energy integration is inherently multidisciplinary and is particularly dependant on the use of techniques from the domains of data analytics, pattern recognition and machine learning. Examples of relevant research topics include the forecasting of electricity supply and demand, the detection of faults, demand response applications and many others. This workshop will provides a forum where interested researchers from the various related domains will be able to present and discuss their findings.

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重要日期

2014-07-06
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征稿范围

Scope Data analytics for renewable energy sources Smart Grid applications of data analytics Data analytics for power generation, transmission, and distribution SCADA/DCS data analytics Fault detection, classification, location, and diagnosis Power quality detection Power system state estimation Load forecasting, wind power forecasting, and PV power forecasting Islanding detection Demand response Smart grid cyber security Customer profiling and smart billing Parallel and distributed data analytics for renewable energy integration Big data and cloud-based analytics for renewable energy integration

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重要日期
  • 09月19日

    2014

    会议日期

  • 07月06日 2014

    摘要截稿日期

  • 09月19日 2014

    注册截止日期

主办单位
Massachusetts Institute of Technology
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