Naturally comfortable and sustainable: Informed design guidance and performance labeling for passive commercial buildings in hot climates. (15th July 2016)

• Record Type: Journal Article
• Authors: Rackes, Adams; Melo, Ana Paula; Lamberts, Roberto
• Is Part Of: Applied energy. Volume 174(2016)
• Page Start: 256
• Page End: 274
• Publication Date: 2016-07-15
• Subjects: AE95 95th percentile absolute error -- AFN airflow network -- AR aspect ratio -- CDD cooling degree day -- EH exceedance hour -- EHF exceedance hour fraction -- ELA effective leakage area -- ELPD equipment and lighting power density -- FPA footprint (projected) area -- GLM generalized linear model -- NVW night ventilation window -- PCA principal component analysis -- PI prediction interval -- PW primary window -- RMSE root mean square error -- SA sensitivity analysis -- SD standard deviation -- SHGC solar heat gain coefficient -- SRC standardized regression coefficient -- SVR support vector regression -- WWR window-to-wall ratio; Natural ventilation -- Building energy simulation -- Adaptive thermal comfort -- Sensitivity analysis -- Metamodel -- Sustainable development; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2016.04.081
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: Parameters varied in building energy simulations to assess adaptive comfort impacts. Building size and internal gains were most important; envelope properties less so. Ceiling fans and night ventilation were effective, low-energy comfort interventions. A new metamodel can support building labeling program and provide design guidance. With informed design, comfort achievable in most of Brazil with no air conditioning. Abstract: This work develops guidance and tools to understand the performance, improve the design, and simplify the evaluation of naturally ventilated low-rise commercial buildings in warm and hot climates. We conducted ∼50, 000 detailed energy and airflow simulations in 427 locations across Brazil, varying 55 parameters representing building morphology, fenestration, construction properties, internal gains, operating times, wind modifiers, flowpaths, window control, and soil traits. Comfort performance was quantified by the average annual fraction of occupied hours that exceeded the upper limit of an adaptive comfort zone, and investigated with sensitivity analysis and machine learning methods. Results indicated that, after climate, building size (both footprint area and number of stories) and internal gains were most influential and were positively associated with discomfort. Adding air movement with ceiling fans and providing for night ventilation both proved highly effective comfort interventions. Except for roof solar absorptance, opaque envelope changes, including increasing insulation or thermal mass, had only marginal impacts. A support vector regression metamodel, requiring 29 easily obtainable inputs plus a weather file, was fit to the simulation results and successfully validated ( R 2 = 0.97). The metamodel was developed as a simplified compliance path for naturally ventilated buildings to enhance Brazil's commercial building performance labeling program, which, because it currently provides such a path only for air conditioned buildings, may discouraging decision-makers from considering even more efficient passive solutions. We use a case study to show how the metamodel, which we will distribute publicly, can also serve as a design tool, and demonstrate that modifying a small set of parameters can drastically improve thermal performance and achieve sustainable comfort in hot and warm climates.