About this Course

This 5 full-day course is focused on load forecasting in the power industry, a critical aspect of managing electricity generation and distribution with a focus on key areas described as follows:

Load Forecasting: The course presents advanced load forecasting techniques, which are essential for predicting electricity demand accurately. Load forecasting is critical for grid management and resource planning across all forecasting time horizons.

Temporal Granularity: Some regions have transitioned to load forecasts with finer temporal granularity, moving beyond hourly predictions. This shift aims to reduce forecasting uncertainties and improve real-time grid management and generate improved hybrid methodologies

Frequency of Updates: As the operation of electric grids becomes more complex, there’s a need for more frequent updates in load forecasts, due to the increased penetration of inverter-based resources, which can vary in output rapidly.

Weather Sensitivity Analysis: The course examines how weather conditions impact load forecasts. It covers weather sensitivity analysis, which quantifies the influence of meteorological factors on electricity demand. It presents the weather impacts on the load forecasts and the methodologies employed to quantify the weather effect and building a repository of weather normal data.

Statistical and Mathematical Models: The course delves into the application of statistical and mathematical models for load forecasting. These models often include time series analysis, regression analysis, and other mathematical tools to make predictions.

Artificial Intelligence and Machine Learning (AI/ML): The course highlights the integration of AI and ML techniques in load forecasting. Machine learning algorithms are used for data-driven predictions and pattern recognition, improving forecast accuracy.

Grid Complexity: As the power grid becomes more complex due to increased penetration of renewable and inverter-based resources, load forecasts require higher temporal resolution and adaptability to changing conditions.

Practical Applications-Industry Examples: It emphasizes practical applications of forecasting methods, supported by real-life examples from large control areas in North America, Australia, Europe. This approach helps professionals understand how to apply these methods effectively.

This training course will also feature a guest speaker, who is a Ph.D candidate to provide insights into the most modern aspects of Artificial Intelligence in the context of load forecasting.

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TRAINING OBJECTIVES

This course offers a comprehensive approach to all aspects of load forecasting:

Gain a perspective of load forecasting from both operators in the generating plant and system operators.
Understand and review the advanced load forecasting concepts and forecasting methodologies
Learn the application of Artificial Neural Networks and Probabilistic Forecasting methods to manage forecasting uncertainties in short time frames
Appreciate market segmentation and econometric framework for long term forecasts
Find out the most recent practical application of load forecasting as examples from large power companies
Get access to recent industry reports and developments

TARGET AUDIENCE

Energy load forecasting professionals from power plant and system operators
Energy planners and energy outlook forecasters and plant operators
Fuel procurement professionals
Planners and schedulers of thermal generating units

COURSE LEVEL

Intermediate

TRAINER

Your expert course instructor is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5.

With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana.

Our Key expert delivered over 60 specialized seminars to executives and engineers from Canada, Europe, South and North America, Middle East, South East Asia and Japan. Few examples are:

Modern Power System in Digital Utilities – The Energy Commission, Malaysia and utilities in the Middle East, GCCIA, June 2020
Assessment of OETC Control Centre, Oman, December 2019
Demand Side management, Load Forecasting in a Smart Grid, Oman, 2019
Renewable Resources in a Smart Grid (Malaysia, Thailand, Indonesia, GCCIA, Saudi Arabia)
The Modern Power System: Impact of the Power Electronics on the Power System
The Digital Utility, AI and Blockchain
Smart Grid and Reliability of Distribution Systems, Cyme, Montreal, Canada
Economic Dispatch in the context of an Energy Market (TNB, Sarawak Energy, Malaysia)
Energy Markets, Risk Assessment and Financial Management, PES, IEEE: Chicago, San Francisco, New York, Portugal, South Africa, Japan. Provided training at CEO and CRO level.
Enterprise Risk methodology, EDP, Portugal
Energy Markets: Saudi Electricity Company, Tenaga National Berhad, Malaysia
Reliability Centre Maintenance (South East Asia, Saudi Electricity Company, KSA)
EUSN, ENERGY & UTILITIES SECTOR NETWORK, Government of Canada, 2016
Connected+, IOT, Toronto, Canada September 2016 and 2015
Smart Grid, Smart Home HomeConnect, Toronto, Canada November 2014
Wind Power: a Cautionary Tale, Ontario Centre for Public Policy, 2010

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POST TRAINING COACHING SUPPORT (OPTIONAL)

To further optimise your learning experience from our courses, we also offer individualized “One to One” coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.
Request for further information post training support and fees applicable

Advanced Load Forecasting & Methodology