At the scheme design stage,the potential of daylighting is significant due to the saving for electric lighting use. There are few simple tools for architects to optimize the daylighting design. Therefore,it is useful ...At the scheme design stage,the potential of daylighting is significant due to the saving for electric lighting use. There are few simple tools for architects to optimize the daylighting design. Therefore,it is useful to develop a design guideline related to the evaluation of lighting energy saving potential and sunlight design strategies. This paper analyzes the impacts of different artificial lighting control methods and design parameters on daylighting. A direct correlation between lighting energy consumption and parameters such as orientations,window to wall ratio (WWR) and perimeter depth is established. A simplified prediction model is proposed to estimate lighting energy consumption with the given perimeter depth,WWR,and window transparency. Validation of the model is carried out compared with detailed lighting simulation software for an office building. After the variation analysis for these parameters,design advises for the daylighting design at scheme design phase are summarized.展开更多
A smart city incorporates infrastructure methods that are environmentally responsible,such as smart communications,smart grids,smart energy,and smart buildings.The city administration has prioritized the use of cuttin...A smart city incorporates infrastructure methods that are environmentally responsible,such as smart communications,smart grids,smart energy,and smart buildings.The city administration has prioritized the use of cutting-edge technology and informatics as the primary strategy for enhancing service quality,with energy resources taking precedence.To achieve optimal energy management in themultidimensional system of a city tribe,it is necessary not only to identify and study the vast majority of energy elements,but also to define their implicit interdependencies.This is because optimal energy management is required to reach this objective.The lighting index is an essential consideration when evaluating the comfort indicators.In order to realize the concept of a smart city,the primary objective of this research is to create a system for managing and monitoring the lighting index.It is possible to identify two distinct phaseswithin the intelligent system.Once data collection concludes,the monitoring system will be activated.In the second step,the operation of the control system is analyzed and its effect on the performance of the numerical model is determined.This evaluation is based on the proposed methodology.The optimized resultswere deemed satisfactory because they maintained the brightness index value(79%)while consuming less energy.The intelligent implementation system generated satisfactory outcomes,which were observed 1.75 times on average.展开更多
The"11th Five-Year"plan sets the objective of reducing energy consumption per unit of GDP by 20% in five years.Readjusting industrial structure is one of the possible means to reach this goal.As for energy c...The"11th Five-Year"plan sets the objective of reducing energy consumption per unit of GDP by 20% in five years.Readjusting industrial structure is one of the possible means to reach this goal.As for energy consumption reduction through industrial readjustment,however,present research only explores the effects of industry structural change in the six sectors such as agriculture,industry,construction,transportation and commerce,yet without considering the ramifications of sub-sector two-digit code industry structure.In this paper,we have calculated the effects of structural change in light- heavy industries on energy consumption and energy intensity from 1993 to 2005 using the factor decomposition method.As a result,we found for each percentage point gain in favour of heavy industry in the light-heavy industry mix,China’s energy consumption increases by nearly 9 million metric tons of coal equivalent.However the overall effects of structural change in light-heavy industry are less than those of sub-sector intensity factors on industrial energy intensity and energy consumption per unit of GDP.The heavy industry share gain has over recent years exerted a significant impact on industrial energy intensity.For example,78% of the abnormal increase in industrial energy intensity in 2003 could be attributed to this factor.Finally,an analytical framework for energy intensity based on this study is presented.展开更多
基金Project(2006BAJ02A02) supported by the National Key Technologies R & D Program of China
文摘At the scheme design stage,the potential of daylighting is significant due to the saving for electric lighting use. There are few simple tools for architects to optimize the daylighting design. Therefore,it is useful to develop a design guideline related to the evaluation of lighting energy saving potential and sunlight design strategies. This paper analyzes the impacts of different artificial lighting control methods and design parameters on daylighting. A direct correlation between lighting energy consumption and parameters such as orientations,window to wall ratio (WWR) and perimeter depth is established. A simplified prediction model is proposed to estimate lighting energy consumption with the given perimeter depth,WWR,and window transparency. Validation of the model is carried out compared with detailed lighting simulation software for an office building. After the variation analysis for these parameters,design advises for the daylighting design at scheme design phase are summarized.
文摘A smart city incorporates infrastructure methods that are environmentally responsible,such as smart communications,smart grids,smart energy,and smart buildings.The city administration has prioritized the use of cutting-edge technology and informatics as the primary strategy for enhancing service quality,with energy resources taking precedence.To achieve optimal energy management in themultidimensional system of a city tribe,it is necessary not only to identify and study the vast majority of energy elements,but also to define their implicit interdependencies.This is because optimal energy management is required to reach this objective.The lighting index is an essential consideration when evaluating the comfort indicators.In order to realize the concept of a smart city,the primary objective of this research is to create a system for managing and monitoring the lighting index.It is possible to identify two distinct phaseswithin the intelligent system.Once data collection concludes,the monitoring system will be activated.In the second step,the operation of the control system is analyzed and its effect on the performance of the numerical model is determined.This evaluation is based on the proposed methodology.The optimized resultswere deemed satisfactory because they maintained the brightness index value(79%)while consuming less energy.The intelligent implementation system generated satisfactory outcomes,which were observed 1.75 times on average.
基金A key Project of the National Research Base for Humanities and Social Sciences under the Ministry of Education(Grant No.05JJD630035)
文摘The"11th Five-Year"plan sets the objective of reducing energy consumption per unit of GDP by 20% in five years.Readjusting industrial structure is one of the possible means to reach this goal.As for energy consumption reduction through industrial readjustment,however,present research only explores the effects of industry structural change in the six sectors such as agriculture,industry,construction,transportation and commerce,yet without considering the ramifications of sub-sector two-digit code industry structure.In this paper,we have calculated the effects of structural change in light- heavy industries on energy consumption and energy intensity from 1993 to 2005 using the factor decomposition method.As a result,we found for each percentage point gain in favour of heavy industry in the light-heavy industry mix,China’s energy consumption increases by nearly 9 million metric tons of coal equivalent.However the overall effects of structural change in light-heavy industry are less than those of sub-sector intensity factors on industrial energy intensity and energy consumption per unit of GDP.The heavy industry share gain has over recent years exerted a significant impact on industrial energy intensity.For example,78% of the abnormal increase in industrial energy intensity in 2003 could be attributed to this factor.Finally,an analytical framework for energy intensity based on this study is presented.
