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Rooftop analysis for solar flat plate collector assessment to achieving sustainability energy

机译:屋顶分析,用于太阳能平板集热器评估,以实现可持续能源

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The insufficiency of current energy sources, elevated costs and global climate worriment are distinctive factors making of renewable energy an issue of boosting consideration. In this concern, solar energy is viewed as being indefinitely environmental friendly, carbon-free, beneficial nature with appreciated cost potentials and is witnessing fast progressing. Following the Horizon 2020 climate and energy package, the volume of gases emitted by greenhouses has to be cut down by 20% by all the European Union (EU) member countries in order to enhance energy performance by 20% and raise the renewable energy rate to 20% by 2020. Solar energy on building roofs plays a crucial aspect in renewable and sustainable energy consumption of high-density human habitats. A merest energy should be allocated to provide hot water service from solar sources, as other European norms for new buildings by the Spanish Technical Building Code, similarly to other European regulation on achievement objectives. The climate zone and the overall demand of hot water in the building regulate this minimal amount needed. This manuscript use a new methodology for automatic detection of geometric patterns from aerial or space images using a Hierarchical Temporal Memory (HTM) algorithm. In this way, an automatic method for the identification of building roofs in order to assess the opportunities available to install solar thermal systems in small urban areas has been developed. As case of study: a village with 7000 inhabitants was analyzed in the South of Spain. The maximum overall accuracy obtained among the different classifications made was 98.05%, avoiding problems related to the use of images with high spatial resolution, as in the salt-and pepper noise effect. This approach contributes reducing the generated carbon and GHG emissions and open new perspectives for energy savings strategies to optimize the energy efficiency of buildings. In the case study, implementing the solar thermal systems would come out with a saving of 1.4 tons of CO2 per inhabitant. (C) 2017 Elsevier Ltd. All rights reserved.
机译:当前能源的不足,成本上升和全球气候担忧是使可再生能源成为人们日益关注的问题的独特因素。在这种情况下,太阳能被认为是无限期的环境友好,无碳,有益的性质,具有潜在的成本潜力,并且正在快速发展。遵循Horizo​​n 2020气候和能源计划之后,所有欧盟成员国都必须将温室气体排放量减少20%,以将能源性能提高20%并将可再生能源比率提高到到2020年达到20%。建筑物屋顶的太阳能在高密度人类栖息地的可再生和可持续能源消耗中起着至关重要的作用。与西班牙关于成就目标的其他欧洲法规类似,应分配最少量的能量来提供太阳能热水服务,这是西班牙技术建筑法规所制定的其他欧洲新建筑规范。建筑的气候区和整体热水需求调节了所需的最小数量。该手稿使用一种新的方法,使用层次时间记忆(HTM)算法自动从空中或空间图像中检测几何图案。以这种方式,已经开发了一种用于识别建筑物屋顶的自动方法,以便评估可在小型城市地区安装太阳能热系统的机会。作为研究案例:在西班牙南部对一个有7000名居民的村庄进行了分析。在进行的不同分类中获得的最大总体精度为98.05%,避免了与使用具有高空间分辨率的图像有关的问题,例如盐和胡椒噪声效果。这种方法有助于减少产生的碳和温室气体排放,并为节能战略打开了新视野,以优化建筑物的能源效率。在案例研究中,实施太阳能热系统将为每位居民节省1.4吨二氧化碳。 (C)2017 Elsevier Ltd.保留所有权利。

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