Course Overview:

Load forecast is critical for power planning and power trade in the country and at cross-borders. Understanding the concepts of forecasting methodologies provides insights to both operators on the generation side and the system operators. The course has been designed to provide a comprehensive approach to all aspects of load forecasting using traditional modelling techniques such as linear regression and autoregressive integrate moving average as well as other recent models such as neural network models.

Course Outcomes

• Provides a review of the advanced concepts and forecasting methodologies,
• Energy demand forecasting techniques
• Creates and understanding of Artificial Neural Networks and Probabilistic forecasting methods to manage forecasting uncertainties in short time frames,
• Market segmentation and Econometric framework for long-term forecast,

Topics

• Economic foundations of energy demand
• Introduction to econometrics
• Introduction to Load Forecasting principles
• Application of the Electricity Demand Forecasting Methodology
• Statistical Properties of Electric Load Time Series
• Multiple Linear Regression
• Deep Neural Network-Based Load Forecasting
• Residential annual consumption modelling
• Temporal Granularity:
• Introduction to Model for Analysis of Energy Demand(MAED)