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Project Website: http://resstock.nrel.gov/
Performer: National Renewable Energy Laboratory (NREL) – Golden, CO
Performance Period: 2014 –
DOE Funding:
Related Projects: OpenStudio, Scout

Project Objective

Traditional stock models are coarse grain, often relying on a few prototype models to represent a single building type in a single climate zone. For some analyses, such coarse granularity can average out relevant details and return “all-or-nothing” results that miss significant opportunities. ResStock is a multi-resolution residential stock modeling framework. ResStock combines data from multiple sources including the EIA’s Residential Energy Consumption Survey (RECS) to create high-resolution conditional probability tables for home characteristics like square footage, insulation, window-type, HVAC type, and HVAC efficiency. ResStock then uses sampling to generate a statistically representative set of models for the desired region. ResStock leverages OpenStudio to create the models and run them.

Payback period “heat maps” for insulation upgrades in various housing stock segments in Washington and Oregon with short payback cost effective upgrade opportunities are in green.
Payback period “heat maps” for insulation upgrades in various housing stock segments in Washington and Oregon with short payback cost effective upgrade opportunities are in green. Traditional coarse-grain analysis misses many opportunities.
NREL

Contacts

DOE Technology Manager: Eric Werling and Amir Roth
Principal Investigator: Eric Wilson, NREL