Describing Energy as a Single Variable

Theory

Wind Number

The Wind Number was developed in 2013 by Scott Hoppe following a multi-year study of California energy consumers. The California Independent System Operator (CAISO) had been reporting hourly generation data, and Scott observed the correlation between wind power production and the overnight hours when demand was lower. Scott had been conducting energy audits with smart meter data since 2010, and created an energy analysis that combined wind power production data with consumption data. Scott prepared a patent application for a method of reducing energy costs, then entered Sabreez into the 2013-2014 US Department of Energy’s “American Energy Data Challenge” Contest.

In 2016 Sabreez introduced the Solar Boost in response to rapid development of solar resources in California. Whereas the Wind Number was defined as wind power resources over thermal resources times 100 (as shown below), the Solar Boost would be defined as the ratio of solar power resources over thermal resources times a constant. The value of the constant can be determined by Sabreez as solar resources are developed over time and on a market by market basis. The Solar Boost constant in California will not be the same constant as Texas (ERCOT) or other markets.

The sum of the Wind Number and Solar Boost produce a systemwide Clean Energy Factor that can be reported accurately and reliably without the need to estimate emissions. Our resource-based definition of clean energy production relative to power coming from fossil fuels can be used by energy stakeholders to produce consumer-facing marketing programs that reduce the need for monetary compensation of energy consumers. Telling people when the energy supply is awesome is a much more engaging message than reporting hourly levels of pollutants.

For more information on seasonal values for the Wind Number and Solar Boost, read our White Paper:

Sabreez White Paper August 2017 Final

For an evaluation of how the adoption of different technologies changes a Users Wind Number, read this:

Wind_number_analysis

To review our November 2018 report comparing the Clean Energy Factor with California’s hourly emissions, read this:

GHG_Signal_Executive _Summary

Appendix A

Appendix B

There is a strong inverse correlation between the Clean Energy Factor and wholesale pricing in real time, and this relationship is described in our January 2019 White Paper.

To view a comparison of the Clean Energy Factor, marginal emissions, wholesale prices in the CAISO real-time market, and systemwide emissions, Click Here.

To view our Presentation from the 2019 BECC Conference, Click Here.

Our Formulas are presented below: