Abstract: System and method include precisely modeling of a facility's energy usage over time based on historic data, and precisely predicting or measuring its actual, reduced energy usage over time after a redesign, retrofit, or renovation, or other positive change to the facility. The energy cost savings, whether over a time point of view (POV) of predicted, real-time, or historic, are creditable to the intervening remediation or renovation of the facility's energy footprint. In accordance with one embodiment, multiple-variable inputs are modeled using arithmetic regression and steepest-descent convergence arithmetic solutions based in large part on building-science (construction) data versus outside average temperature (t) that simplifies the modeling and measurements. Additionally is thus addressed along with a system and method that is more accurate, more repeatable, more reliable, and thus more credible and more readily monetized.

Abstract: System and method include precisely modeling of a facility's energy usage over time based on historic data, and precisely predicting or measuring its actual, reduced energy usage over time after a redesign, retrofit, or renovation, or other positive change to the facility. The energy cost savings, whether over a time point of view (POV) of predicted, real-time, or historic, are creditable to the intervening remediation or renovation of the facility's energy footprint. In accordance with one embodiment, multiple-variable inputs are modeled using arithmetic regression and steepest-descent convergence arithmetic solutions based in large part on building-science (construction) data versus outside average temperature (t) that simplifies the modeling and measurements. Additionality is thus addressed along with a system and method that is more accurate, more repeatable, more reliable, and thus more credible and more readily monetized.

Abstract: System and method include precisely modeling of a facility's energy usage over time based on historic data, and precisely predicting or measuring its actual, reduced energy usage over time after a redesign, retrofit, or renovation, or other positive change to the facility. The energy cost savings, whether over a time point of view (POV) of predicted, real-time, or historic, are creditable to the intervening remediation or renovation of the facility's energy footprint. In accordance with one embodiment, multiple-variable inputs are modeled using arithmetic regression and steepest-descent convergence arithmetic solutions based in large part on building-science (construction) data versus outside average temperature (t) that simplifies the modeling and measurements. Additionality is thus addressed along with a system and method that is more accurate, more repeatable, more reliable, and thus more credible and more readily monetized.

Abstract: System and method include precisely modeling of a facility's energy usage over time based on historic data, and precisely predicting or measuring its actual, reduced energy usage over time after a redesign, retrofit, or renovation, or other positive change to the facility. The energy cost savings, whether over a time point of view (POV) of predicted, real-time, or historic, are creditable to the intervening remediation or renovation of the facility's energy footprint. In accordance with one embodiment, multiple-variable inputs are modeled using arithmetic regression and steepest-descent convergence arithmetic solutions based in large part on building-science (construction) data versus outside average temperature (t) that simplifies the modeling and measurements. Additionality is thus addressed along with a system and method that is more accurate, more repeatable, more reliable, and thus more credible and more readily monetized.