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A new approach for developing a hybrid sun-tracking method of the intelligent photovoltaic blinds considering the weather condition using data mining technique

机译:一种新方法,用于使用数据采矿技术考虑天气条件的智能光伏百叶窗的混合阳光跟踪方法

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As a part of technology innovation in the building sector, an intelligent photovoltaic blind (i-PB) with direct and indirect sun-tracking methods were previously developed by this research team. Due to the shadows on the tightly aligned slats of the i-PB, however, there is a difference in the electricity according to the weather and sun-tracking method. Accordingly, this study aimed to develop a hybrid sun-tracking method of the i-PB, which can determine the sun-tracking method with highest electricity generation between the two sun-tracking methods according to the weather. To this end, this study proposed a new approach for developing a hybrid sun-tracking method by selecting the main climate factors and their threshold using data mining technique. As a result of the experimental study conducted in South Korea, a hybrid sun-tracking method in autumn was developed. To ensure the effectiveness of the new approach, a real-time sun-tracking system was developed and used for the experimental validation. As a result, the hybrid sun-tracking method showed the highest electricity generation (i.e., 97.3 Wh/m(2)) among the three sun-tracking methods, and 84.9% prediction accuracy. The proposed approach can provide a more comprehensive solution by maximizing the advantages of each sun-tracking method and minimizing its weaknesses. (C) 2019 Elsevier B.V. All rights reserved.
机译:作为建筑业技术创新的一部分,智能光伏盲(I-PB)以前由这支研究团队开发了直接和间接的太阳跟踪方法。然而,由于I-Pb的紧密对齐板条上的阴影,根据天气和太阳跟踪方法存在电力差异。因此,本研究旨在开发I-Pb的混合速率跟踪方法,其可以根据天气确定两种太阳跟踪方法之间具有最高发电的太阳跟踪方法。为此,本研究提出了一种通过使用数据挖掘技术选择主要的气候因子及其阈值来开发混合阳光跟踪方法的新方法。由于韩国在韩国进行的实验研究,开发了一种秋季的混合阳光跟踪方法。为确保新方法的有效性,开发了一个实时的太阳跟踪系统并用于实验验证。结果,混合的太阳跟踪方法显示了三种太阳跟踪方法中的最高发电(即97.3WH / m(2)),预测准确性为84.9%。该方法可以通过最大化每个太阳跟踪方法的优点并最大限度地减少其缺点来提供更全面的解决方案。 (c)2019 Elsevier B.v.保留所有权利。

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