Abstract
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.
Highlights
Improving the energy efficiency of the building stock plays a key role in mitigating global climate change [1]
After the base model and existing conditions were modeled for each home type and compared to results from those in the Partnership for Advanced Residential Retrofit (PARR) report [18], building enclosure optimization simulations were performed for each home
The simulations demonstrate that once the corresponding optimal enclosure is implemented, frame construction homes are more likely to benefit from an upgrade to existing HVAC systems
Summary
Improving the energy efficiency of the building stock plays a key role in mitigating global climate change [1]. Several governmental and non-governmental organizations have proposed aggressive targets for applying deep energy retrofits to achieve a minimum of 50% reductions in annual energy use by existing residential buildings [5,6]. These goals create both a challenge and an opportunity for older homes in the U.S and abroad. It is common to apply a package, or “tool-box,” of prescriptive deep energy retrofits [7,8,9,10,11] This approach has the advantage of reducing the time and effort required for energy analysis on individual homes while allowing for efficient training of contractors to apply the same, or similar, retrofits to a large number of homes in a systematic way. Other more advanced performance-based approaches, such as calibrated whole building energy models coupled with optimization algorithms [12,13,14,15,16,17], are used to identify energy saving opportunities beyond those targeted by prescriptive measures, but they require more intensive analyses for individual buildings
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