2016
DOI: 10.3390/buildings6010003
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Assessment of the Performance of a Ventilated Window Coupled with a Heat Recovery Unit through the Co-Heating Test

Abstract: Abstract:The aim of the article is to describe the results of an experimental campaign based on the assessment of a heat recovery unit coupled with a dynamic window. Two fully monitored and calibrated outdoor test cells are used, in order to evaluate the energy performance and the related thermal comfort. The former presents a traditional window with double-glazing, aluminum frame and indoor blind and a centrifugal extractor for the air circulation. The latter is equipped with a dynamic window with ventilated … Show more

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Cited by 11 publications
(8 citation statements)
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“…The overall saving provided by the automatic control is slightly higher than 7%. In this case, the linear dependence of the daily cumulated consumption from the average value of external temperature is confirmed by a correlation value (R 2 ) equal to 0.91: energy consumption increases with the increasing of the average outdoor air temperature as would be expected in summer conditions [ 50 , 51 , 52 ]. Instead, in the first case the R 2 index is equal to 0.1, which is symptomatic of a non-linear dispersion.…”
Section: Experimentation: Results and Discussionsupporting
confidence: 59%
“…The overall saving provided by the automatic control is slightly higher than 7%. In this case, the linear dependence of the daily cumulated consumption from the average value of external temperature is confirmed by a correlation value (R 2 ) equal to 0.91: energy consumption increases with the increasing of the average outdoor air temperature as would be expected in summer conditions [ 50 , 51 , 52 ]. Instead, in the first case the R 2 index is equal to 0.1, which is symptomatic of a non-linear dispersion.…”
Section: Experimentation: Results and Discussionsupporting
confidence: 59%
“…Even if this instrument is not properly designed to monitor the indoor variables over a long-term, but is designed to assess the indoor environmental data over a shorter time and closest to the positions of end users (i.e., office workstations) [ 36 ], a second test was performed after approximately two years (discontinuous use, no exposition to high relative humidity values or to direct sunlight) to verify the long-term stability of this sensor. In this second case, the nEMoS device was located directly in the climate box in order to verify the values recorded by the DHT22 over four different levels of Ta and RH.…”
Section: Optimization and Resultsmentioning
confidence: 99%
“…To verify the hypothesis the following formula is used. ti = i /SEi (5) Where i represents the estimate of the expected variation of IEQ associated with a unitary variation of TC and IAQ, respectively, keeping fixed the rest of the model. SE,i is the Standard Error of the regression coefficient i.…”
Section: F = Msr/mse (4)mentioning
confidence: 99%
“…IEQ is widely investigated and many findings about how the indoor quality affects human life were defined [4]. However, in the field of low energy buildings, that represent the current target for new and retrofitted buildings [5], few studies focused on IEQ and well-being effects [6], emphasizing the energy aspect [7,8]. In these buildings where the environmental variables are often automatically controlled by dedicated systems and the users' role in this task is low, attention must be paid on IEQ, avoiding possible discomfort [9,10].…”
Section: Introductionmentioning
confidence: 99%