Deep Learning and its Application to Power System Analysis

Posted:
21 Nov 2017
Authors:
Mike Zhou
Primary Committee:
IEEE Power & Energy Society Webinar Series
Page/Slide Count:
Time: 00:50:48
After the AlphaGo winning game, there is a renewed interest in artificial intelligence, especially in the area of Deep Learning. This Webinar will give a general overview of Deep Learning and its potential application to power system analysis. It will include two parts. In the first part, an open platform for exploring the application of Deep Learning to power system analysis will be introduced, including the discussion of its system architecture, and some sample application scenarios. The platform is based on the integration of InterPSS, an open source power system simulation software project, and TensorFlow, Google's Deep Learning engine; In the second part, some of our recent research work in the area of applying Deep Learning to perform fast power system stability assessment will be presented. Different types of neural networks model, both steady-state and dynamic power system operation information as the neural networks model prediction input are studied for the assessment. Some preliminary results of applying Deep Learning to assess the stability of large-scale power networks will be presented.

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