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A platform for research: civil engineering, architecture and urbanism
Performance verification of typical and design weather year by thermal load calculation targeting office building
https://orcid.org/0000-0003-3709-4517
We proposed a new type of weather year data for building energy simulations named the typical and design weather year, which can be used for estimating both average and peak energy demand for one year of building energy simulation. The typical and design weather year is generated using a quantile mapping method. In this paper, we made the typical and design weather year for three cities, Tokyo, Sapporo, and Kagoshima, representing a wide range of climatic conditions in Japan, and evaluated its performance by conducting building energy simulations targeting prototypical office buildings. We found that the typical and design weather year was more than twice as accurate in estimating average energy demand as the existing typical weather year data. Typical and design weather year can also estimate peak energy demand with high accuracy.
Practical application: The cumulative distribution functions of a target weather data set, on which quantile mapping is performed, are modified to consist entirely of parent multi-year weather data. Therefore, typical and design weather years based on quantile mapping are expected to be useful as versatile weather year data representing the various weather characteristics of multi-year conditions. In this study, we found that the typical and design weather year can estimate both average and peak energy demands in building energy simulations. New type of weather year data named the typical and design weather year can be used as both typical and design weather data.
Performance verification of typical and design weather year by thermal load calculation targeting office building
https://orcid.org/0000-0003-3709-4517
We proposed a new type of weather year data for building energy simulations named the typical and design weather year, which can be used for estimating both average and peak energy demand for one year of building energy simulation. The typical and design weather year is generated using a quantile mapping method. In this paper, we made the typical and design weather year for three cities, Tokyo, Sapporo, and Kagoshima, representing a wide range of climatic conditions in Japan, and evaluated its performance by conducting building energy simulations targeting prototypical office buildings. We found that the typical and design weather year was more than twice as accurate in estimating average energy demand as the existing typical weather year data. Typical and design weather year can also estimate peak energy demand with high accuracy.
Practical application: The cumulative distribution functions of a target weather data set, on which quantile mapping is performed, are modified to consist entirely of parent multi-year weather data. Therefore, typical and design weather years based on quantile mapping are expected to be useful as versatile weather year data representing the various weather characteristics of multi-year conditions. In this study, we found that the typical and design weather year can estimate both average and peak energy demands in building energy simulations. New type of weather year data named the typical and design weather year can be used as both typical and design weather data.
Performance verification of typical and design weather year by thermal load calculation targeting office building
https://orcid.org/0000-0003-3709-4517
We proposed a new type of weather year data for building energy simulations named the typical and design weather year, which can be used for estimating both average and peak energy demand for one year of building energy simulation. The typical and design weather year is generated using a quantile mapping method. In this paper, we made the typical and design weather year for three cities, Tokyo, Sapporo, and Kagoshima, representing a wide range of climatic conditions in Japan, and evaluated its performance by conducting building energy simulations targeting prototypical office buildings. We found that the typical and design weather year was more than twice as accurate in estimating average energy demand as the existing typical weather year data. Typical and design weather year can also estimate peak energy demand with high accuracy.
Practical application: The cumulative distribution functions of a target weather data set, on which quantile mapping is performed, are modified to consist entirely of parent multi-year weather data. Therefore, typical and design weather years based on quantile mapping are expected to be useful as versatile weather year data representing the various weather characteristics of multi-year conditions. In this study, we found that the typical and design weather year can estimate both average and peak energy demands in building energy simulations. New type of weather year data named the typical and design weather year can be used as both typical and design weather data.
Performance verification of typical and design weather year by thermal load calculation targeting office building
Arima, Yusuke (author) / Ooka, Ryozo (author) / Kikumoto, Hideki (author)
Building Services Engineering Research & Technology ; 39 ; 147-160
2018-03-01
14 pages
Article (Journal)
Electronic Resource
English
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