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Energy cost impact of non-residential energy code requirements

  • Date:
  • Author(s)/Creator(s):
    Jian Zhang
    Reid Hart
    Michael Rosenberg
  • Publisher(s)/Producter(s):
    2016 ACEEE Summer Study on Energy Efficiency in Buildings, 21-26 August 2016, Pacific Grove, United States
Description

The 2012 International Energy Conservation Code contains 396 separate requirements applicable to non-residential buildings; however, there is no systematic analysis of the energy cost impact of each requirement. Consequently, with limited building department resources, the efforts for plan review, inspection, and training may not be focused on the most impactful items. An inventory and ranking of code requirements based on their potential energy cost impact is under development and the approach is described in this study.

The initial phase was a pilot project focused on office buildings with simple HVAC systems in Climate Zone 4C. Prototype building simulations were used to estimate the energy cost impact of varying levels of noncompliance. A preliminary estimate of the probability of occurrence of each level of noncompliance was combined with the estimated lost savings for each level to rank the requirements according to expected savings impact. The methodology to develop and refine further energy cost impacts, specific to building type, system type, and climate location is demonstrated. As results are developed, an innovative alternative method for compliance verification can focus efforts so only the most impactful requirements from an energy cost perspective are verified for every building and a subset of the less impactful requirements are verified on a random basis across a building population. The results can be further applied in prioritizing training material development and specific areas of building official training.

Determining which energy code measures have the greatest impact on lost savings can be very useful in targeting inspections, verification, or training. This work shows that most of the potential lost savings can be attributed to a small set of measures. A method of measure ranking is proposed that uses a base set of simulated values that can be augmented with field data as it is collected. This will establish a set of preliminary rankings that can be improved over time.

Funder
US Department of Energy
Policy Quality
5
Subject(s)
Sustainable building design and construction
Building energy codes
commercial buildings
energy costs

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