In a rapidly evolving energy industry, utilities are dealing with new challenges like
integrating distributed energy resources and market saturation for advanced lighting retrofits.
Demand-side management programs require new approaches to meet aggressive carbon
reduction goals. Advanced measurement & verification (M&V) is an energy data analysis
method using smart meter data in combination with analytics to quantify energy efficiency
project savings. Advanced M&V shows great promise for supporting next generation
commercial programs including retro commissioning, multi-measure retrofits, and behavior
change programs.
Advanced M&V captures real project impacts at the meter, but sometimes non-project
events can also impact consumption (so-called “non-routine events” [NREs]). Accurately
detecting and accounting for NREs is important for reducing uncertainty of savings estimates
and helps manage investment risk for different stakeholders (e.g., utilities, building owners,
ESCOs). Recent research has shown promise in establishing data-driven techniques to identify
and adjust for NREs, but fundamental questions still remain, such as: how can you distinguish
NREs from acceptable noise in energy consumption profiles? What is the frequency and
magnitude of NREs? Can their detection and adjustment be automated and streamlined?
This paper documents the state of the art in NRE quantification and analysis. The results
of research to quantify the frequency, nature and direction of NREs, and methods and metrics for
determining a trigger threshold for taking action on NREs are presented. The paper also
documents the latest technical guidance on application of NRE detection and adjustment
methods.