AI For Load Forecasting, DER Hosting Capacity & Distribution Planning
This online engineering PDH course examines how artificial intelligence (AI) and machine learning (ML) support load forecasting, DER hosting capacity analysis, and distribution system planning.
Distribution planners now need granular feeder-level forecasts that account for weather, customer behavior, and the rapid growth of solar PV, battery storage, electric vehicles, and building electrification. AI tools can process large data sets, estimate hosting capacity across thousands of nodes, and evaluate many DER scenarios far faster than manual studies.
AI remains an advisory tool, so the Professional Engineer must validate its forecasts against traditional power flow studies and field data, apply safety margins, and remain accountable for decisions that are safe, reliable, and code-compliant.
This course covers load drivers and feature engineering, weather normalization, short-term and long-term load forecasting, and feeder-level spatial forecasting. It also explains hosting capacity analysis and DER scenario planning, validation metrics such as MAE, MAPE, and RMSE, handling uncertainty and model drift, model risk management and FMEA, ISO 9001 alignment, and documentation for professional defensibility.
This 1 PDH online course is applicable to electrical and utility engineers, as well as other technical professionals who are interested in learning more about AI for load forecasting and distribution planning.
This PE continuing education course is intended to provide you with the following specific knowledge and skills:
- Understanding the role of AI as an advisory tool and the Professional Engineer's accountability in distribution planning
- Familiarizing with load drivers, feature engineering, and weather normalization for load forecasting
- Explaining short-term, long-term, and feeder-level spatial load forecasting methods and applications
- Understanding DER hosting capacity analysis and AI-assisted DER scenario planning
- Explaining validation metrics, uncertainty, model drift, and decision thresholds for AI forecasts
- Familiarizing with model risk management, FMEA, and documentation for professional defensibility
In this professional engineering CEU course, you need to review the course document titled, “AI For Load Forecasting, DER Hosting Capacity & Distribution Planning”, prepared by Brian Lisiewski, P.E.
Once you complete your course review, you need to take a multiple-choice quiz consisting of ten (10) questions to earn 1 PDH credits. The quiz will be based on the entire document.
Upon successful completion of the quiz, print your Certificate of Completion instantly. (Note: if you are paying by check or money order, you will be able to print it after we receive your payment.) For your convenience, we will also email it to you. Please note that you can log in to your account at any time to access and print your Certificate of Completion.