Utilities and other power organizations nowadays are caught in a crossfire of patterns and trends that often run counter to what seemed incontrovertible fact just a few years ago. Other perplexing conditions are present, also, that seem difficult to gauge – changes in the mix of supply and demand side resources, the impact of technology on the grid and access it allows to system and customer data, dramatic shifts in commodity prices, the emergence of intermittent and variable resources, flat to declining load growth, and so on.
The problem is largely due to the inaccurate, unexplainable and indefensible forecasts generated from the forecasting practices in the pre-computer era. Trend analysis and other traditional methodologies cannot properly capture these unstable conditions. Thankfully, though, new forecasting methods have been developed that take account of behavioral and technological changes affecting electricity use.
This course offers the fundamentals of energy forecasting principles, practices, and their applications in the utility industry, such as demand forecasting, renewable generation forecasting, and price forecasting – the essential tools for making sense of today’s power environment and delivering proper guidance for industry decision-makers. It will be loaded with energy forecasting examples and illustrations that translate these methodologies into the corollary utility practices.
- Examine and review the concept of predictability
- Recognize how to describe a forecasting process using formal and rigorous terminologies
- Identify the basic forecasting concepts, such as signal and noise
- Recognize the practical value of forecast combination
- Apply diffusion of innovation principle in long term forecasting
- Discuss the do’s and don’ts in judgmental forecasting
- Relate how to evaluate forecasts and forecasting systems
- Distinguish the pros and cons of commonly used univariate models, multivariate models and machine learning techniques
- Define the general methodologies for short-term and long-term electric load forecasting, gas demand forecasting, wind and solar power forecasting, and gas and electricity price forecasting
EUCI has been accredited as an Authorized Provider by the International Association for Continuing Education and Training (IACET). In obtaining this accreditation, EUCI has demonstrated that it complies with the ANSI/IACET Standard which is recognized internationally as a standard of good practice. As a result of their Authorized Provider status, EUCI is authorized to offer IACET CEUs for its programs that qualify under the ANSI/IACET Standard.
EUCI is authorized by IACET to offer 1.0 CEUs for this event.
Requirements For Successful Completion Of Program
Participants must sign in/out each day and be in attendance for the entirety of the course to be eligible for any continuing education credit.
PowerPoint presentations, case studies, and workshop exercises will be used in this program.
Tuesday, June 6, 2017
12:30 – 1:00 p.m. :: Registration
1:00 – 3:00 p.m. :: Forecasting Principles
- Predictable or not?
- Forecasting terminologies
- Signal, noise and tradeoff
- Forecast combination
- Diffusion of innovation
- Judgmental forecasting
3:00 – 3:15 p.m. :: Afternoon Break
3:15 – 5:00 p.m. :: Forecasting Practices
- Forecast evaluation
- Univariate models
- Multivariate models
- Machine learning techniques
5:00 p.m. :: Course Adjourns for the Day
Wednesday, June 7, 2017
8:00 – 8:30 a.m. :: Continental Breakfast
8:30 – 10:15 a.m. :: Electricity Demand Forecasting
- Driving factors
- Short-term load forecasting
- Long-term load forecasting
10:15 – 10:45 a.m. :: Networking Break
10:45 – 11:30 p.m. :: Gas Demand Forecasting
- Driving factors
11:30 a.m. – 12:15 p.m. Demonstration
12:15 – 1:30 p.m. :: Group Luncheon
1:30 – 3:00 p.m. :: Renewable Generation Forecasting
- Wind power forecasting
- Solar power forecasting
3:00 – 3:15 p.m. :: Afternoon Break
3:15 – 4:30 p.m. :: Price Forecasting
- Gas price forecasting
- Electricity price forecasting
4:30 – 4:45 p.m. :: Summary
4:45 p.m. :: Adjournment
Tao Hong, Director of BigDEAL (Big Data Energy Analytics Laboratory), University of North Carolina at Charlotte and Chief Data Scientist, Hong Analytics
Dr. Tao Hong is the Director of BigDEAL (Big Data Energy Analytics Laboratory) at University of North Carolina at Charlotte and Chief Data Scientist of Hong Analytics. He has been providing training and consulting services to more than 100 organizations in the energy industry worldwide. He is the Founding Chair of IEEE Working Group on Energy Forecasting, General Chair of Global Energy Forecasting Competition, lead author of the online book Electric Load Forecasting: Fundamentals and Best Practices, and author of the blog Energy Forecasting. Dr. Hong received his B.Eng. in Automation from Tsinghua University in Beijing and his PhD with co-majors in Operations Research and Electrical Engineering from North Carolina State University.
The Hotel Minneapolis, Autograph Collection
215 S 4th St.
Minneapolis, MN 55401
To reserve your room, please call 1-612-340-2000
Please indicate that you are with the EUCI group to receive the group rate.
The room rate is $229.00 single or double plus applicable taxes.
Room Block Dates:
A room block has been reserved for the nights of June 4 – 8, 2017.
Rate Available Until:
Make your reservations prior to May 17, 2017. There are a limited number of rooms available at the conference rate. Please make your reservations early.