Big Data Analytics For Smart Grid

By Dr. Ritula Thakur   |   National Institute of Technical Teachers Training and research, Chandigarh
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.

Learners enrolled: 8595


Course Status : Completed
Course Type : Core
Duration : 8 weeks
Start Date : 01 Sep 2019
End Date : 31 Oct 2019
Exam Date :
Category :
  • Annual Refresher Programme in Teaching (ARPIT)
  • Level : None
    This is an AICTE approved FDP course

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    Week1: Need of Data Analysis in Smart Grid
    Week2: 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


    1. Smart Grid: Fundamentals of Design and Analysis, 1st Edition, Wiley- IEEE Press.
    2. Python Programming, 3rd Edition, John Zelle and Michael Smith, Franklin Beedle & Associates Inc.
    3. Introduction to Machine Learning with Python, Andreas C. Mueller and Sarah Guido, O'Reilly Media, Inc.


    Dr. Ritula Thakur received B.E degree in Electrical engineering with Honours, M.E. degree in Power systems with distinction and Ph.D from Panjab University, Chandigarh. 
    Currently, she is working as Assistant Professor at National Institute of Technical Teachers Training and Research, Chandigarh, India. Dr. Thakur has also worked as Visiting Scholar in Richard Russel Research Laboratory, Athens, USA.
    Her research interests are in the areas of Real Time modeling & Simulation of Power Systems, Modeling of DFIG based WECS, Embedded systems and Microcontrollers, Electrical Engineering and Information Technology in Agriculture, Quality Analysis and Detection Technology in Food Materials, Sensors and Instrumentation, Power Systems, Power Quality, PLC and SCADA, Micro Grid and Smart Grid.