4.7 Article

Lessons learned from implementing night ventilation of mass in a next-generation smart building

期刊

ENERGY AND BUILDINGS
卷 207, 期 -, 页码 -

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2019.109547

关键词

Night ventilation; Thermal mass; Energy efficiency; Resilience; Smart buildings

资金

  1. Northwest Energy Efficiency Alliance (NEEA)

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Summer temperature extremes are expected to increase during the next century. Integrating night ventilation of mass (NVM) strategies in new 'smart' buildings could increase resilience to warming temperatures and reduce reliance on mechanical cooling. However, designing and operating buildings with NVM is challenging due to the complexity of interacting variables and difficulty of accurately measuring and predicting them, particularly when using automated controls and sensors. In this study we evaluated NVM performance by monitoring two night-ventilated classrooms in a mixed-mode smart academic building during October 2014 and June-July 2016. We investigated whether NVM systems were operating as intended, altered operation as needed to match design intent, and compared NVM efficacy during incorrect and corrected operation. We calculated the amount of heat NVM removed from each room overnight and visualized gradients of heat removal across the mass surface. We found that incorrect building automation system (BAS) operation during June 2016 resulted in overuse of mechanical cooling, while corrected operation later in July reduced the number of hours mechanical cooling was required, although average outdoor temperatures were higher. Our results also showed greatest overnight reductions in mass surface temperatures in locations nearest to the air inlets on the exterior south-facing walls. This critical evaluation quantifies the agreement between NVM performance as modeled during the design phase and during post-occupancy operation several years after construction. We conclude that the observed performance gap may be addressed through periodic or continuous re-commissioning. (C) 2019 Elsevier B.V. All rights reserved.

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