Forecasting

A Grand View

May 06, 2017

The view from the 96th floor of the John Hancock Center is amazing. From here, cars are merely dots between the straight rows of lights and people are absent. Even the contours formed by the cluster of high-rise buildings pale in comparison to the largeness of Lake Michigan and the vastness of the city.

Itron’s 15th Annual Energy Forecasting Meeting provided a similar perspective pushing aside our small daily challenges to see the grand view of the energy forecasting world. This year’s meeting was held in Chicago from April 26-28 where 60 attendees from 38 companies spent three days discussing the implication of the economy, new technologies, prices, energy efficiency, and normal weather on the electric and gas forecasting world.

The View. The broadest pictures of the electric industry were covered by Mark Quan and Mike Russo (Itron), Steve Cochran (Moody’s Analytics) and Erin Boedecker (Energy Information Administration). Mark and Mike stepped back and showed historical growth of the industry and preliminary projections based on Itron’s latest Benchmarking and Trend survey. Steve presented the current state of the U.S. economy and forward-looking risks, and Erin provided details about the EIA’s latest forecast for the residential and commercial sectors which go through 2050. These presentations painted a picture of the horizon and direction for the electric and gas industries.

The Contour. The current challenges of the industry shape the horizon. These challenges include the penetration of AMI data, behind-the-meter technology such as solar and batteries, and changing weather patterns. Andy Sukenik, Mike Russo, and William Marin (Itron) discussed solar penetration, solar shape modeling, and battery technology. Kristin Larson (Storm Geo) showed alternative climate normal calculations, and Dennis Kelter (ComEd) addressed the uses of AMI data.

The Details. Within the broad view and the contours of the industry, several attendees addressed specific issues and techniques useful in our current situation. Bo Xing (Salt River Project), Abdul Razack (Nevada Power), and Reynaldo Guerra (CPS Energy) showed modeling techniques including peak calibration, model selection tests, and incremental change techniques. Andrew Trachsell (IESO) and Chad Burnett (AEP) discussed time-of-use pricing and price elasticities, and Markus Leuker (DTE) showed the power of daily tracking and weather normalization with AMI data.

With the broad array of topics and multiple perspectives, attendees found the discussion challenging and informative. When reflecting on the experience, Nicole Fan (Alectra Utilities) said, “The meeting was a great success; the topics have been expanded so much including regulations, pricing, economics and new technologies. I enjoyed it a lot.”

I agree. The view is amazing.

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.


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