Journal
SOLAR ENERGY
Volume 137, Issue -, Pages 11-24Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.solener.2016.07.053
Keywords
Solar energy; Urban form; Design of experiments; Tropical climate
Categories
Funding
- CAPES
- CNPq
- Institut National des Sciences Appliquees de Toulouse
- company ESSS
- company ESTECO
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Today, 75% of global energy consumption occurs in cities. On the topic of climate change, adapting urban settlements to face this growing demand is a priority issue, especially for fast-growing cities in developing countries such as Brazil. Planning the urban morphology of the built environment is a key issue in shifting to a climate adapted urban environment. This paper addresses an important threefold energy challenge of tropical cities: the major potential of harnessing solar energy as renewable resource for local electricity production and the energy-saving paradox of reducing the undesirable solar heat gains in buildings while providing satisfactory levels of daylight. It aims at measuring the effect size of urban form factors regarding these energy goals. This study applies the Design Of Experiments (DOE) approach. A DOE analysis is a statistical technique that provides a set measure of how design parameters are correlated and the effective contribution of each one to a given response of interest. This study proposes a fractional factorial DOE method coupled to a Simplified Radiosity Algorithm (SRA) aiming to evaluate the irradiation availability on building envelopes while taking a large representative sample of contrasted urban block geometries into account. The buildings' envelope solar irradiation availability assesses a set of energy-related morphological parameters. Results indicate a significant impact of the aspect ratio, the distance between buildings and the surface equivalent albedo. Establishing high values of street aspect ratio may cut solar irradiation on roofs by 130 kW h/m(2) year, while increasing the plot ratio may only yield 26 kW h/m2 year. The results also point out important first order interaction effects between certain variables. (C) 2016 Elsevier Ltd. All rights reserved.
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