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

Buildings

Honnie Aguilar Leinartas²  Brent Stephens¹ 

[1] Department of Civil, Architectural and Environmental Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA; E-Mail

关键词: BEopt;    EnergyPlus;    energy simulation;    deep energy retrofit;    residential;   

DOI  :  10.3390/buildings5020323

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.