Looking south at the New York City Housing Authority Amsterdam Houses at West End Avenue and 63d Street in NYC, Nov. 28, 2008. The Amsterdam Houses superblock energy model is validated by both total energy consumption and end use breakdown metrics.
"Energy Saving Alignment Strategy: Achieving Energy Efficiency in Urban Buildings by Matching Occupant Temperature Preferences with a Building's Indoor Thermal Environment"
Journal Article, Applied Energy, volume 123, page 209–219
June 15, 2014
Authors: Xiaoqi Xu, Former Giorgio Ruffolo Postdoctoral Research Fellow, Sustainability Science Program/Energy Technology Innovation Policy research group, 2013–2014, Patricia J. Culligan, John E. Taylor
Existing strategies for residential energy savings through physical renovation or motivating occupant energy conservation behavior can be costly and/or have transitory effects. Focusing on multi-family dwellings, an important subset of the urban residential sector, we propose an Energy Saving Alignment Strategy (ESAS) that has advantageous cost-effectiveness and a long-lasting influence. By aligning the distribution of residents' thermostat preferences with the indoor temperature, ESAS aims to maximize thermal comfort and, accordingly, energy savings in multi-family buildings where indoor temperatures vary between apartments as a function of apartment orientation and floor level. Using a case study of a 1084-apartment public housing complex in New York, we classify both occupants’ thermostat preferences and apartments' operative temperatures into five groups, and optimize energy efficiency by assigning each group of occupants to the group of apartments that best aligns with their thermostat preference. We test ESAS in eight cities representing all four U.S. census regions and six climate zones. Simulation results reveal 2.1–42.0% in energy savings compared to random apartment assignments depending on geographic location, with the highest energy reductions occurring in cities with mild climates, where the range of occupant thermostat preferences coincides with the natural indoor temperature range. We conclude by providing suggested guidelines on how ESAS might work in practice, and recommendations for extending ESAS research.
Read the full article (log in may be required): http://www.sciencedirect.com/science/article/pii/S0306261914001834
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