With the fast development of digital technology and cloud computing, more and more data are produced through digital equipment and sensors, as well as through human activities and communications. The collected data are mounting at an exponential rate and the structure of them is also becoming much more complicated. The processing and analysis method of these large volume data is a new challenge but also an opportunity with the concept of “big data”.
This course explores the usage of open source software python for demonstration of usage of big data in smart grid. It begins with the importance of big data analysis in smart grid, intelligent data collection devices followed by machine learning and deep learning algorithms used in data analytics for smart grid.

INTENDED AUDIENCE: Undergraduate students, Postgraduate students, research scholars, faculties of technical institutes, Industrial professionals.

PREREQUISITES: Basics of Power Systems, Basic knowledge of statistics.

INDUSTRY SUPPORT: The course is organised in Collaboration with eminent Industries such as Opal-RT and IBM.

COURSE LAYOUTWeek1: Need of Data Analysis in Smart GridWeek2: Intelligent Data Collection Devices in Smart Grid Week3: Data Science Pertaining to Smart Grid Analytics Week4: Tools for Big Data Analytics Week5: Conventional Machine Learning Algorithms for Data Analytics Week6: Advanced Machine Learning Algorithms for Data Analytics Week7: Big Data Analytics for Smart Grid- Case Studies Week8: Cloud and edge computing for Big data analytics