Forecasting

Laissez Les Bon Temps Rouler!

April 17, 2024

That was Laura Plante’s (Entergy) call to introduce the 2024 Energy Forecasting Group (EFG) Meeting, also known as Itron’s Annual Energy Forecasting Meeting. Originally scheduled for 2020, we finally made it to New Orleans this year from March 12-15. Over four days, 71 attendees representing 45 companies participated in the two pre-conference workshops and a two-and-a-half day general meeting. For those who did not attend or are new to New Orleans, “Laissez les bon temps rouler!” means “Let the good times roll!”

The meeting consisted of 15 technical sessions and three roundtables covering topics including the short-term and long-term economic outlook, long-term energy efficiency trends, electric vehicle market, electrification impacts, industrial customer forecasting, time-of-use rate impacts, distribution system forecasting, DSM forecasting issues and neural networks. The round table discussions centered on “hot” forecasting issues, managing the industrial forecast and distribution system forecasting.

While it’s impossible to encapsulate the two-and-a-half days into a short blog post, I can confidently assert the top three issues that dominated the discussion, which include:

Electric vehicles growth and load shape impacts
Accurately capturing large (and lumpy) industrial growth from data centers and manufacturing additions
Electrification in the form of heat pump adoptions transforming winter (and summer) loads

The only thing that might be scarier than these long-term issues was the New Orleans ghost tour. But unlike the forecasting issues, ghosts aren’t real (at least, that’s what they tell us).

I hope to see everyone next year in Savannah, Georgia on April 8-11, 2025. Submit your abstracts to forecasting@itron.com.

By Mark Quan

Principal Forecast Consultant

Mark Quan is a Principal Forecast Consultant with Itron’s Forecasting Division. Since joining Itron in 1997, Quan has specialized in both short-term and long-term energy forecasting solutions as well as load research projects. Quan has developed and implemented several automated forecasting systems to predict next day system demand, load profiles, and retail consumption for companies throughout the United States and Canada. Short-term forecasting solutions include systems for the Midwest Independent System Operator (MISO) and the California Independent System Operator (CAISO). Long-term forecasting solutions include developing and supporting the long-term forecasts of sales and customers for clients such as Dairyland Power and Omaha Public Power District. These forecasts include end-use information and demand-side management impacts in an econometric framework. Finally, Quan has been involved in implementing Load Research systems such as at Snohomish PUD. Prior to joining Itron, Quan worked in the gas, electric, and corporate functions at Pacific Gas and Electric Company (PG&E), where he was involved in industry restructuring, electric planning, and natural gas planning. Quan received an M.S. in Operations Research from Stanford University and a B.S. in Applied Mathematics from the University of California at Los Angeles.