A new RTTV (roof thermal transfer value) calculation method for cool roofs. (1st March 2015)

• Record Type: Journal Article
• Authors: Zingre, Kishor T.; Wan, Man Pun; Yang, Xingguo
• Is Part Of: Energy. Volume 81:(2015)
• Page Start: 222
• Page End: 232
• Publication Date: 2015-03-01
• Subjects: Cool roof -- Solar reflectance -- R-value -- RTTV (roof thermal transfer value); Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2014.12.030
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Methods to estimate RTTV (roof thermal transfer value, or equivalent) currently adopted by numerous South East Asian countries have different inherent limitations in accurately evaluating the thermal performance of cool roofs. These existing methods either use a fixed value to represent the solar reflectance effect or assume a linear correlation between annual-averaged conduction heat gain and solar absorptance, which are shown to be inaccurate. In this paper a new RTTV model is proposed with new formulation for modelling the equivalent thermal resistance increment due to the solar reflectance effect on opaque roofs using the previously developed CRHT (Cool Roof Heat Transfer) model. The new formulation is incorporated into the U-value estimation of the heat conduction gain component. The new RTTV model is validated against computational simulations and experiments on an air-conditioned test building with flat concrete roof in Singapore. The Current RTTV model adopted in Singapore gives large error in RTTV estimation for the test building at high-reflectance (over-estimates by 20 times at reflectance = 0.90) whereas the new RTTV model gives much more accurate estimations (maximum error within 12%). The proposed method for new RTTV model formulation is also applicable to other similar models, and is not limited by climate conditions. Highlights: A novel and accurate method is proposed to evaluate the performance of cool roofs. The proposed method overcomes the inherent deficiencies of the existing methods. The proposed method is applicable to RTTV, OTTV and ETTV models for all climates. A new RTTV model is developed using proposed method and computationally validated. The new RTTV model imparts high accuracy (maximum error < 12%) at all reflectance.