Project code: AAI-03 (ELE)
Title: Energy Data Analytics
Primary mentor: Jing Xiong
Faculty advisor: Prof. Yu Zhang
Number of interns: 3
Have you heard of the Smart Grid on the news or from your energy provider? In this next generation of the electric grid, a huge amount of data is generated and exchanged every day: markets, equipments, and power system data which can be used for reliable and efficient planning and operation, predicting states, providing situational awareness, analyzing stability, detecting faults and providing advance warning. Therefore, energy data analytics have a significant role to make the grid more intelligent, efficient, and productive. This summer, the mentor and SIP interns will explore machine learning (ML) and deep learning (DL) models to play with the energy data, build up the pipeline and increase the performance.
The SIP interns will: (1) learn to use Python for programming; (2) gain experience in machine learning frameworks and/or deep learning frameworks such as pytorch; (3) gain exposure on how to collect data from online resources; (4) gain exposure to multiple ML/DL techniques for time series data analytics; (5) learn how to read related researc