Machine Learning Applications in Microgrid Systems

Learning Objectives – 1. to impart basic understanding of machine learning concept to audience .2. To explain Python programming as a back end tool. 3. To explain applications of machine learning in Smart Microgrids The session is broadly divided in three parts, as follows-1. Part I-Review of Grid System, Microgrid, Smart Grid, Smart Microgrid. 2. Part II -Review of Machine Learning Concepts, Python programming and IoT 3. Part III-Applications of Machine Learning Tools in Microgrid – ANN based OR gate, SVM, K means Clustering, Decision tree, Linear Regression, Virtual Meter, Summation meters, Theft detection, Thermography. Conclusion- The audience would learn about basic fundamentals of machine learning and their applications in Microgrids. They would be able to develop small applications based on this topic.