Hi,
While learning about different algorithms such as Regression, Clustering, Classification, etc. in Machine Learning in different domains such as Medicine (Patient data analysis, etc.), Market analysis, etc. I wonder, how these algorithms could be implemented in Power Electronics or Grid Applications? Any ideas?? Are there any datasets available similar to the ones in UCI ML repositories??
Thanks in advance.
In my opinion the AI can be applied in different sector , Computer Versions (Robotic), Automotive sector(Autonomous vehicle's), economics (financial)....etc.
For Grid Applications that you can do it the smart Network for gesture the power Electric or surveying the Sun for the most energy for stocks in batteries to do it With Deep Leraning.
I hope that be Clair. @Ravi Verma
In my opinion the AI can be applied in different sector , Computer Versions (Robotic), Automotive sector(Autonomous vehicle's), economics (financial)....etc.
For Grid Applications that you can do it the smart Network for gesture the power Electric or surveying the Sun for the most energy for stocks in batteries to do it With Deep Leraning.
I hope that be Clair. @Ravi Verma
i can recommend you a nice lecture from Professor Line Roald. Her team have worked with statistical ML to recognize power grid congestion patterns in order to determine the most relevant cases required for consideration
Here is the link
https://www.public.asu.edu/~yweng2/Tutorial5/22_talk_line.html
ofcourse there are other areas, and research is being carried out in this area to amalamate ML and Power Systems/Power Electronics
Hi Ravi Verma, I think you got some nice suggestions from Barodi Anass and Neelotpal Majumdar.
Besides, people have also tried to use ML for detecting faults in semiconductor devices. You can go through the following link:
https://ieeexplore.ieee.org/abstract/document/8870440
Paper title: "TCAD-Enabled Machine Learning Defect Prediction to Accelerate Advanced Semiconductor Device Failure Analysis".
Presentation Recent Trends in Electrical Power Systems: Application of Ma...
I just found this recommendation, maybe you can have a look through itRavi Verma
Hi,
The following documents and links give details:
Machine learning support for logic diagnosis
L Rodríguez Gómez - 2017 - elib.uni-stuttgart.de
http://elib.uni-stuttgart.de/bitstream/11682/9216/1/VeroeffentlichungLRG.pdf.
Best Regards
In power plant, use of the ML algorithm to predict energy level and power gridline analysis for future further forecast of the energy level consumption to have a better view of the trend analysis to predict overloading in the power grid system. Similarly, the ML prediction in the close feedback loop to control the energy balance when used in a network of power components such as power electronics. So the power electronics and converters can accurately adjust the level of electrical power to the generator component to consume or output to the motor. So better power grid stability can be utilized as much when compared to without ML in the loop.
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