About: Recently, a growing literature pay attention to the green buildings, and most of them focuses on design, energy simulation, and post-occupancy evaluation but rarely involves the integration analysis of energy consumption, indoor environmental quality, and occupant satisfaction in the operational stage. In this paper, the authors propose a comprehensive quantitative study based on energy-environment-satisfaction (EES) and take a three-star green building in Shanghai as an example. Through the use of real-time monitoring data, the study analyses the distribution characteristics of the parameters of EES. Meanwhile, this study discusses the differences between operational energy consumption and design parameters and also quantifies the exponential relationship between per floor personnel density and building energy consumption. Moreover, combined with the user satisfaction survey, some improvements are suggested. Furthermore, the relationship between daily energy consumption and the environmental parameters of daily energy consumption, PM2.5, CO(2), temperature, relative humidity, and illumination is fitted, and the results indicate that there is a multivariate linear relationship with a correlation of 0.876. Through the sensitivity analysis, we found that the relative humidity affects 1.4 times as much as CO(2). Therefore, its control value is critical to reduce energy consumption in the operation of green buildings.   Goto Sponge  NotDistinct  Permalink

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  • Recently, a growing literature pay attention to the green buildings, and most of them focuses on design, energy simulation, and post-occupancy evaluation but rarely involves the integration analysis of energy consumption, indoor environmental quality, and occupant satisfaction in the operational stage. In this paper, the authors propose a comprehensive quantitative study based on energy-environment-satisfaction (EES) and take a three-star green building in Shanghai as an example. Through the use of real-time monitoring data, the study analyses the distribution characteristics of the parameters of EES. Meanwhile, this study discusses the differences between operational energy consumption and design parameters and also quantifies the exponential relationship between per floor personnel density and building energy consumption. Moreover, combined with the user satisfaction survey, some improvements are suggested. Furthermore, the relationship between daily energy consumption and the environmental parameters of daily energy consumption, PM2.5, CO(2), temperature, relative humidity, and illumination is fitted, and the results indicate that there is a multivariate linear relationship with a correlation of 0.876. Through the sensitivity analysis, we found that the relative humidity affects 1.4 times as much as CO(2). Therefore, its control value is critical to reduce energy consumption in the operation of green buildings.
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  • Energy consumption
  • Metropolitan areas of China
  • Quantitative research
  • 10th-century establishments in China
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