It’s a DER World, We’re Just Living in It

If you’re reading this and you’re a load forecaster like myself (or know a thing or two about load forecasting), then you are well aware of the…


Averaging the Weather First or Averaging the Energy Forecast

There is a question that has long vexed me: If we calculate a normal series of weather variables by averaging them first and running them through a…


Where Did Durbin and Watson Go Wrong?

I’m sure you have all been there—the spot where you mention autocorrelation and the Durbin-Watson statistic. I saw this recently in some testimony…


Holidays Are No Vacation for the Load Forecaster

Summer has arrived. While your friends are frolicking at the beach, you are struggling in a darkened cubicle to ensure that the load forecast…


Improving Financial Analysis with AMI Data

Smart meter data is more granular and more timely than monthly billing data. Access to this data supports a paradigm shift in forecasting processes,…


A Few Thoughts on P-Values

I recently read an article about P-Values that led to some discussion with my Itron colleagues, along with some thoughts on the matter. In the…


2019 Annual Energy Forecasting Meeting

Two pre-conference classes. Three conference days. Eighteen industry presentations. Forty-nine companies. Sixty-nine attendees. These are…


Developing Net Load Uncertainty Forecasts to Support System Operations

Today, the deep penetration of renewable generation resources system operators are requiring new tools to place reasonable confidence bands around…


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…