It’s All the Same, Only the Names Will Change
Last year, Itron was contracted by a small utility (about 11,000 customers) to construct a 10-year-ahead load forecast for capacity planning. I was…
Capped vs. Uncapped Degree Days
In energy modeling, we often utilize spline variables to capture the non-linear relationship between consumption and temperature. These variables…
Leveraging a Waterfall Approach to Explain the Load Forecast
Our first brown bag seminar of the year is entitled “Leveraging a Waterfall Approach to Explain the Load Forecast”. This session introduces a…
When Does Humidity Make the Meter Spin?
For anyone that has tried to improve a model by changing the specification, you know it is very much a trial and error process. You create variables…
A Practitioner’s Guide to Short-term Load Forecast Modeling
Over the years, numerous clients have requested a “recipe book” for building powerful short-term load forecast models. This guide to Short-term Load…
Short-term Load Forecasting: A Practitioner’s Handbook
Our final brown bag seminar of the year—hosted on Tuesday, Dec. 4—is entitled “Short-term Load Forecasting: A Practitioner’s Handbook.” Ever wonder…
Aggregation Bias Strikes Again!
The issue of aggregation bias should not be a new concept to any of us in the energy forecasting world. In April, my colleague David Simons posted…
Odds and Sods
Probabilities and odds express the same information in different ways. In science and economics, people tend to think in terms of probabilities,…
What are Weather Groups?
If you’re a user of Itron’s Automated Demand Forecasting System, MetrixIDR, then chances are you’ve probably seen the words “Weather Groups” at some…
A Simple Approach for Addressing Behind-the-Meter Solar Generation
I was recently asked to account for behind-the-meter (BTM) solar generation in a set of day-ahead hourly electric models. Fundamentally, the problem…
Load Forecasting Using Machine Learning: Does the Hype Meet Reality?
It is easy to stub your toe on the voluminous literature available on machine learning when the question of how to improve your operational forecast…
Upcoming Seminar: Budget Forecasting – A Practitioner’s Handbook
Our second brown bag seminar of the year is entitled “Budget Forecasting – A Practitioner’s Handbook.” This Brown Bag distills twenty-plus years of…
The Pitfalls and Pain of Aggregation Bias
As forecasters, averaging is something that we do a lot. We like averaging because it helps us filter out much of the noise in our data so that we…
Daylight Saving Time: The Bane of the Load Forecaster
Sunrise and sunset times vary from summer to winter because of earth’s tilt with respect to its orbit around the sun. This difference is magnified at…
Ignore Missing Option
The Sum function in MetrixND seems like a complex way to make adding difficult. In a MetrixND transformation, numbers are added by joining variables…
Using Neural Networks to Build Robust Hourly Models
Our first brown bag seminar of the year is entitled, “Using Neural Networks to Build Robust Hourly Models.” Neural networks are flexible functional…
Dividing Two Interval Series in MetrixLT
In my previous post, I showed that MetrixLT can multiply two hourly data series even though the software was not designed for that specific purpose.…
Multiplying Two Interval Series in MetrixLT
“Help” was the desperate cry of a MetrixLT user after the close of the workday. “I need to multiply two hourly interval data series in MetrixLT!”…
There’s More Than One Way to Round a Number
When we were in school, we all learned the general rule for rounding – if a significant digit is followed by a number that is greater than or equal…
Calculating an Average Annual Growth Rate in MetrixND
After finishing my forecast, I like to present forecast average annual growth rates. These results are calculated by converting the monthly forecast…
Seasonal Sales? Not a Problem.
There is a client who has a reporting issue problem. Let’s call him Ray. His annual sales are to be split into summer and winter sales, but on a…
Forecast Tests in MetrixND
Out-of-sample tests are a useful tool for seeing how well a model performs with data it hasn’t seen before (i.e., data that weren’t used to estimate…
Who is Forecasting Long-Term Solar Generation?
In this last forecasting brown bag presentation on solar load forecasting, we asked participants who had developed a long-term solar load forecast…
Using In-Line Transformation in the Report Object
I’m developing a forecast that requires base, high, and low scenarios. After building the base scenario, the high and low scenarios are…