Click here to register for a Utility University course.
This course provides background information, real-world development experience, and in-depth discussions of big data analytics and machine learning in smart grid. The value, velocity, volume, and variety of big data in smart grid will be discussed. The basics of machine learning algorithms such as unsupervised learning, supervised learning, and reinforcement learning algorithms will be taught. Important real-world applications of big data analytics and machine learning in transmission systems, distribution systems and electricity market will be presented.
These applications include 1) wind and solar generation forecasting; 2) topology identification; 3) electricity theft detection; 4) predictive maintenance of equipment; 5) load forecasting; 6) estimation of behind-the-meter solar generation; 7) reinforcement learning-based distribution system controls, 8) predictive state estimation, and 9) algorithmic trading with virtual bids in electricity market.
Attendees will learn:
- Understand how to assess the business value of machine learning and big data analytics in smart grid
- Identify important machine learning and big data applications in smart grid
- Master the skills of big data management and processing
- Explain and illustrate machine learning algorithms
- Develop big data applications in smart grid
- Apply machine learning algorithms to solve problems in transmission system, distribution system and electricity market
Knowledge, skills and/or capabilities that attendees should acquire through this course:
- Identify problems in smart grid that can be solved with machine learning algorithms
- Apply supervised, unsupervised, and reinforcement learning algorithms to solve problems in smart grid
- Explain and interpret the results of big data analytics and machine learning
Who should attend this course:
- Electric, combination utility, software provider, consulting company, proprietary trading firms, independent system operator
- Engineers, data analysts, data scientists, business analysts, and managers
- Distribution Planning, Distribution Engineering, Distribution Operators, Transmission Planning, Transmission Engineering, Transmission Operations, Customer Service
Prerequisite skills, knowledge, certifications: No prior knowledge of machine learning and big data analytics or certification required