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Simplified analysis methods for thermal responsive performance of passive solar house in cold area of China

机译:中国寒区被动式太阳房热响应性能的简化分析方法

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摘要

Since the first Chinese passive solar house was built in 1977, a large number of passive solar houses have been built within 20 years. However, many problems appeared during the long-term utilization process, such as poor heating effect, inconvenient operation control and incomplete design standards, which lead to the development of passive solar houses stagnant in the past decade. To solve the above- mentioned problems, technical improvement and free running temperature prediction methods of passive solar house were investigated in this study. As a case study, a two-year experiment was undertaken in an improved passive solar house, located in Dalian city, northeast China, and the performance of solar air collector was investigated in winter mainly. The experimental results showed the indoor-outdoor temperature differences were about 13.4-24.5℃ without auxiliary heat exchanger. According to the function of useful heat gain and solar irradiance obtained through regression analyses of experimental data, a simple free running temperature prediction formula of passive solar house for engineering application was obtained, which can be expressed as the linear superposition function of three main factors, including outdoor temperature, internal gains and solar irradiance. Taking the improved solar house as an example, a good agreement between monitored data and predicted data proved the feasibility of the prediction formula. In addition, weighed coefficients of influence factors in prediction formula were determined based on five typical cities in cold areas of China.
机译:自1977年中国建造第一座被动式太阳能房屋以来,在20年内建造了许多被动式太阳能房屋。然而,长期使用过程中出现了许多问题,例如加热效果差,操作控制不便,设计标准不完善,导致被动式太阳能房屋的发展停滞了近十年。为了解决上述问题,本研究对被动式太阳能房屋的技术改进和自由运行温度预测方法进行了研究。作为案例研究,在位于中国东北大连市的一栋经过改进的被动式太阳能房屋中进行了为期两年的实验,并主要在冬季对太阳能空气收集器的性能进行了研究。实验结果表明,不带辅助换热器的室内外温差约为13.4-24.5℃。根据对实验数据进行回归分析得到的有用热增益和太阳辐照度的函数,得出了一种简单的工程用被动式太阳房自由运行温度预测公式,可以表示为三个主要因素的线性叠加函数,包括室外温度,内部增益和太阳辐射。以改进的太阳能房屋为例,监测数据与预测数据的良好吻合证明了该预测公式的可行性。此外,根据中国寒冷地区的五个典型城市,确定了预测公式中影响因素的加权系数。

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