Optimizing Whole House Deep Energy Retrofit Packages: A Case Study of Existing Chicago-Area Homes

Autor: Honnie Aguilar Leinartas, David Dernie, Brent Stephens
Jazyk: angličtina
Rok vydání: 2015
Předmět:
Zdroj: Buildings, Vol 5, Iss 2, Pp 323-353 (2015)
Buildings; Volume 5; Issue 2; Pages: 323-353
ISSN: 2075-5309
Popis: Improving the energy efficiency of the residential building stock plays a key role in mitigating global climate change. New guidelines are targeting widespread application of deep energy retrofits to existing homes that reduce their annual energy use by 50%, but questions remain as to how to identify and prioritize the most cost-effective retrofit measures. This work demonstrates the utility of whole building energy simulation and optimization software to construct a “tool-box” of prescriptive deep energy retrofits that can be applied to large portions of the existing housing stock. We consider 10 generally representative typology groups of existing single-family detached homes built prior to 1978 in the Chicago area for identifying cost-optimal deep energy retrofit packages. Simulations were conducted in BEopt and EnergyPlus operating on a cloud-computing platform to first identify cost-optimal enclosure retrofits and then identify cost-optimal upgrades to heating, ventilation, and air-conditioning (HVAC) systems. Results reveal that prescriptive retrofit packages achieving at least 50% site energy savings can be defined for most homes through a combination of envelope retrofits, lighting upgrades, and upgrades to existing HVAC system efficiency or conversion to mini-split heat pumps. The average upfront cost of retrofits is estimated to be ~$14,400, resulting in average annual site energy savings of ~54% and an average simple payback period of ~25 years. Widespread application of these prescriptive retrofit packages across the existing Chicago-area residential building stock is predicted to reduce annual site energy use by 3.7 × 1016 J and yield approximately $280 million USD in annual energy savings.
Databáze: OpenAIRE