KFUPM Tutorial – AI-Driven Load Forecasting and Monitoring for Sustainable Smart Grids: A Hands-on MATLAB Tutorial

AI-Driven Load Forecasting and Monitoring for Sustainable Smart Grids: A Hands-on MATLAB Tutorial

Part of the IEEE SUSTAIN 2026 pre-conference activities, this tutorial, delivered by Prof. El-Sayed M. El-Alfy from KFUPM, introduces artificial intelligence techniques for electricity load forecasting and monitoring through guided MATLAB examples and practical applications.

Tutorial Details

DateSunday, 29 November 2026

Time Part A: 13:00 – 14:30 Part B: 15:00 – 16:30

Duration3 hours of tutorial activities, in two parts

VenueKFUPM, Dhahran

FormatIn-person lectures and hands-on MATLAB activities

Target AudienceStudents, researchers, engineers, and professionals interested in artificial intelligence, load forecasting, and smart grids

CapacityUp to 30 participants

All times are in Saudi Arabia time (UTC+3).

Registration closes on 22 November 2026

About the Tutorial

Accurate electricity load forecasting helps power systems respond to changing demand, integrate renewable energy, and maintain reliable operation. This tutorial provides a practical introduction to using artificial intelligence and MATLAB for load prediction and monitoring in sustainable smart grids.

Participants will explore AI-based forecasting models, including neural networks, long short-term memory (LSTM) networks, convolutional neural networks, transformers, and ensemble and hybrid models. Guided examples and case studies will cover data preparation, model training, validation, visualization, and comparison of forecasting performance.

What Participants Will Explore

Smart grid concepts and their relationship to sustainability.

Fundamentals of electricity load monitoring and forecasting.

Short- and medium-term forecasting techniques.

Data preprocessing and feature engineering.

AI models for load forecasting and real-time monitoring.

Model evaluation, visualization, and performance comparisons.

Challenges and emerging directions in AI applications for smart grids.

Presenter

Prof. El-Sayed M. El-Alfy

Professor of Computer Science and Engineering

King Fahd University of Petroleum & Minerals

Senior Member of IEEE

Participant Preparation

Basic knowledge of programming and data visualization, preferably using MATLAB, is recommended. Participants are encouraged to attend both parts to follow the hands-on activities.

Participants are recommended to bring a laptop with MATLAB R2022b or a later version activated, along with:

Signal Processing Toolbox
Deep Learning Toolbox
Statistics and Machine Learning Toolbox
Optimization Toolbox

Registration

Registration closes on 22 November 2026

Places are limited to 30 participants.

Submit your registration request using the registration button below. Submission does not guarantee a place; participation confirmation will be sent by email.

Upon successful completion of the tutorial, attendees will receive digital certificates for participation and completion.