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Design Optimization of Renewable Energy Systems in Low/Zero Energy Buildings Using Single and Multi-Objective Optimization Methods

机译:用单一目标优化方法设计低/零能量建筑中可再生能源系统的优化

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Low energy buildings and zero energy buildings have attracted increasing attention in both academic and professional fields following the ambitions of many governments in reducing building energy consumption and carbon emission. This paper presents an investigation on the optimal design of renewable energy systems in two types of buildings: low energy buildings and zero energy buildings. The first zero energy building in Hong Kong, namely Hong Kong Zero Carbon Building, is taken as a reference building in this study. The TRNSYS building model is used to generate the annual cooling load profile of the building. Simplified models are developed to simulate the building energy systems including the air-conditioning systems and the renewable energy systems in Matlab while the building annual cooling load profile is taken as the input. Genetic Algorithm method and Non-dominated Sorting Genetic Algorithm (NSGA-II) approach are implemented for single objective optimization and multi-objectives optimization respectively. Three most important design parameters, i.e., sizes of photovoltaic, wind turbine and bio-diesel generator, are chosen as the variables to be optimized. The performances of buildings, each with different combinations of renewable system sizes, are compared and evaluated.
机译:在许多政府的雄心区降低建筑能源消耗和碳排放时,低能量建筑和零能量建筑吸引了学术和专业领域的越来越关注。本文提出了两种建筑物中可再生能源系统的最佳设计调查:低能量建筑和零能量建筑。香港的第一个零能量建筑即香港零碳建筑,是在本研究中的参考建筑。 Trnsys构建模型用于生成建筑物的年冷却负载曲线。开发了简化模型以模拟包括空调系统和Matlab中可再生能源系统的建筑能量系统,而建筑年冷却负载曲线作为输入。遗传算法方法和非统治分类遗传算法(NSGA-II)方法分别实施单个客观优化和多目标优化。选择三个最重要的设计参数,即光伏,风力涡轮机和生物柴油发电机的大小,作为优化的变量。比较和评估建筑物的性能,每个都具有不同的可再生系统尺寸的组合。

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