Skip to main content

Showing results 1 - 5 of 5

Author(s)
Tim Guiterman, EnergySavvy,
Sarah Zaleski, U.S. Department of Energy,
Ethan Goldman, Vermont Energy Investment Corporation,
Diane Duva, Connecticut Department of Energy and Environmental Protection,
Bill Norton, Opinion Dynamics
Publication Date

This presentation covers the current pilot project testing M&V2.0 as an evaluation tool facilitated by Connecticut Department of Energy and Environmental Protection (CT DEEP).  Speakers on this panel presented examples of how whole building modeling is currently being used for M&V now and its potential future applications. Speakers also discussed benchmarking, data access and other protocols, and how experience with efficiency programs teach us so we can build upon the current experience.

Author(s)
Claire Miziolek, Northeast Energy Efficiency Partnerships, Inc.,
Joe Loper, Itron,
Abigail Daiken, U.S. Environmental Protection Agency,
Richard Counihan, Nest Labs,
Nkechi Ogbue, ecobee
Publication Date

This presentation covers control technologies, such as smart thermostats, and the opportunities they provide for program evaluation, monitoring and verification.

Author(s)
U.S. Department of Energy
Publication Date
Organizations or Programs
Energy Impact Illinois,
Connecticut Neighbor to Neighbor Energy Challenge

This summary from a Better Buildings Residential Network peer exchange call focused on the advantages and challenges of data tracking systems.

Author(s)
U.S. Department of Energy
Publication Date
Organizations or Programs
Connecticut Neighbor to Neighbor Energy Challenge,
NeighborWorks H.E.A.T. Squad

This summary from a Better Buildings Residential Network peer exchange call focused on evaluating and demonstrating the cost-effectiveness of energy upgrades to programs.

Author(s)
U.S. Department of Energy
Publication Date
Organizations or Programs
Connecticut Neighbor to Neighbor Energy Challenge

This peer exchange call summary focused on effective program evaluation and incorporating changes into programs based off evaluation insight.