Smart Grid: Sensing, Data Analytics and Control

XEIET137

Stanford School of Engineering


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Description

This course is expected to return Summer 2019. If you wish to be alerted when it becomes available click "Request Information." In the mean time, please review our other course offerings here .

Many countries set aggressive goals to reduce greenhouse gas emissions, and renewable energy production has increased exponentially as a result. Yet renewable energies are extremely variable, making it hard to predict how much power they will produce at any given time. Smart grids counteract variability by providing more accurate information, more refined control, and tighter feedback. This course teaches the fundamental components of smart grids including sensing, data analytics and control. Learn how to optimize smart grids so they are cost effective and efficient, how to increase grid reliability, and how to measure performance through data analytics. Explore how monitoring and modeling can improve forecasting and provide critical data for decision making. Develop an understanding of the information and communications technology that enable the expanding field of smart grids.

What you will learn

  • The basics of power networks
  • How to manage renewable energy resources and optimize your grid
  • How to create a better system of forecasting of demand and supply
  • Improved and cost-effective measurements to improve grid performance

Topics include

  • Renewables integration
  • Demand side management
  • Distribution automation
  • Data analytics
  • The future of smart grid technology

Tuition

  • $295 per online course

Questions

Please contact the Program Manager at
650.273.5459
scpd-energy@stanford.edu