Smart Grid Analytics for Electrical Engineers

About the Course:

This course empowers electrical engineers with analytics skills to optimize grid performance. You'll learn how to collect, process, and analyze energy consumption data, and use predictive models for fault detection and load forecasting. This three-hour course on Smart Grid Analytics is designed for electrical engineers seeking to leverage data-driven techniques to enhance grid performance and reliability. The session begins with an overview of key smart grid data sources and formats, providing a foundation for effective data handling. Participants will then explore time-series forecasting methods such as ARIMA and LSTM for accurate load prediction, followed by the application of clustering and anomaly detection techniques to identify faults and irregularities within the grid. The course concludes with practical guidance on data visualization using Power BI and Python-based dashboards, enabling engineers to interpret and communicate insights clearly for informed decision-making.

Course Objectives:

• Collect and preprocess smart meter and IoT grid data
• Build time-series models for load prediction
• Use anomaly detection for predictive maintenance

Who is the Target Audience?

• Engineers, analysts, and professionals interested in smart grid analytics for electrical engineers.

Basic Knowledge:

• Basic understanding of related engineering or technical concepts.