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A platform for research: civil engineering, architecture and urbanism
Regional adaptivity of electrochromic glazing in Japan and operational improvement in energy saving using machine learning
Electrochromic (EC) glazing reduces the cooling load via solar radiation shielding. However, excessive solar radiation shielding increases the heating load. In other words, the energy‐saving effect of EC glazing is dependent on the energy performance of the building. This study compares the heating and cooling loads reduction effects of static and EC glazing under various conditions to evaluate the regional applicability of EC glazing in Japan. Furthermore, to maximize the effect, we employ a machine learning (ML)‐based operation and evaluate its efficiency. A parametric study is conducted based on a standard office model in Japan using the DesignBuilder software. The result shows that the heating and cooling loads reduces by 17.1% compared with low‐E glazing in warm climates (Miyazaki, Zone 7). However, in cold climates (Obihiro, Zone 2), the energy increase is 25.4% and the trend of the effect changes near Zone 4. Therefore, on days when the heating load is expected to occur in Zones 3–5, we incorporate solar heat before working hours. The results show that reduction in heating and cooling loads of 2–3% can be expected and that the operation schedule can be set accurately via ML.
Regional adaptivity of electrochromic glazing in Japan and operational improvement in energy saving using machine learning
Electrochromic (EC) glazing reduces the cooling load via solar radiation shielding. However, excessive solar radiation shielding increases the heating load. In other words, the energy‐saving effect of EC glazing is dependent on the energy performance of the building. This study compares the heating and cooling loads reduction effects of static and EC glazing under various conditions to evaluate the regional applicability of EC glazing in Japan. Furthermore, to maximize the effect, we employ a machine learning (ML)‐based operation and evaluate its efficiency. A parametric study is conducted based on a standard office model in Japan using the DesignBuilder software. The result shows that the heating and cooling loads reduces by 17.1% compared with low‐E glazing in warm climates (Miyazaki, Zone 7). However, in cold climates (Obihiro, Zone 2), the energy increase is 25.4% and the trend of the effect changes near Zone 4. Therefore, on days when the heating load is expected to occur in Zones 3–5, we incorporate solar heat before working hours. The results show that reduction in heating and cooling loads of 2–3% can be expected and that the operation schedule can be set accurately via ML.
Regional adaptivity of electrochromic glazing in Japan and operational improvement in energy saving using machine learning
Kobayashi, Takuma (author) / Hiyama, Kyosuke (author) / Omodaka, Yuichi (author) / Oura, Yutaka (author) / Asaoka, Yukiyasu (author)
Japan Architectural Review ; 5 ; 269-278
2022-07-01
278 pages
Article (Journal)
Electronic Resource
English
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