1 Research background
In recent years, with the increasing attention to environmental and energy-saving issues, natural lighting as an important energy-saving strategy has received more and more attention in architectural design. Reasonable use of natural light can effectively reduce lighting energy consumption; by effectively controlling the solar radiation entering the room, the air conditioning load can also be reduced.
However, the design calculation of natural lighting is a complex task. On the one hand, natural light varies greatly with time and region, and is affected by environmental conditions and indoor layout. On the other hand, the design of lighting needs and Equipment systems such as lighting systems and shading systems are combined and coordinated. Therefore, it is difficult to scientifically and accurately complete the lighting design task only by experience or habit. In order to accurately grasp the effect of the light environment, quantitative lighting analysis and calculation are needed.
For different application purposes, the methods and focus of daylighting calculation analysis are different, and the requirements for light climate data are also different. For example, if you want to compare the light and climatic conditions of different regions and evaluate the availability of sunlight, you only need to know the annual average illuminance or the illuminance. If you need to determine the lighting strategy in a certain area, you can understand the different time of the year. The light and climatic conditions, that only need monthly average illumination and so on.
With the development of computer technology and the improvement of indoor light environment requirements, the traditional lighting calculation and evaluation methods based on single lighting coefficient can not meet the needs of engineering practice. Foreign scholars have proposed an annual dynamic lighting evaluation index, which can more comprehensively evaluate the indoor light environment by dynamically simulating and predicting the change of indoor light environment with time. On the other hand, with the emphasis on energy conservation in society, the prediction of lighting energy consumption has received increasing attention. However, to determine the state and control strategy of lighting systems at different times, it is first necessary to accurately calculate the indoor lighting level at different times. At this time, only representative annual or monthly average illuminance data can no longer meet the needs of simulation analysis.
Therefore, to carry out the dynamic optical environment simulation for the whole year, it is necessary to illuminate the data day by day or even hour by day. However, so far, China has not established a complete set of light climate data that can be used for the simulation of dynamic light environment throughout the year, which greatly restricts the development and application of the daylighting analysis method, and thus cannot meet the needs of increasingly complex lighting design. .
The research content of this paper is to study the method of obtaining the typical annual data of illuminance, and establish a set of light climate data that can reflect the characteristics and laws of light climate in China, which can be used for the simulation of dynamic light environment throughout the year. Simulation analysis provides the basis.
2 typical year data
2. 1 Proposal of the concept
Usually we use light climate to characterize the natural conditions of outdoor natural light, including the composition of local natural light and its illumination changes, the brightness of the sky and its distribution in the sky. Among them, illuminance is the most basic and the most easy to obtain data, which is the premise of lighting design calculation and research.
However, as a meteorological parameter, the illuminance has great uncertainty, and even in the same area, the outdoor illuminance changes with time. Taking Beijing as an example, we selected the total illuminance and scatter illuminance data for comparison in 1983, 1984, 1991 and 2009, and we can see the obvious difference (see Figure 1, Figure 2).
Obviously, using different outdoor illuminance data for daylighting analysis, the results are different. Therefore, it is necessary to select representative year-by-year data from years of meteorological data to establish typical annual meteorological data as the calculation conditions for light environment simulation.
2. 2 Typical year data value method
Under the condition of long-term time-lapse measured data, the most direct way to obtain time-lapse meteorological data for dynamic simulation is to select some representative data that can reflect meteorological laws from historically observed meteorological data. However, since the illuminance data is not a routine observation project of the meteorological department in China, only a few sites in China observe it, so the data of natural illuminance data is very scarce. The conditions for establishing typical annual data by using the illuminance data obtained by direct observation are not yet mature.
Another method is to use the existing irradiance data, as well as the radiation light equivalent model, to obtain illuminance data. Since the irradiance data is a routine observation item of the meteorological department, it has abundant data, and the relationship between irradiance and illuminance can be expressed by the following formula:
Where: E â€” illuminance, G is irradiance;
GÎ» â€”â€”â€”the spectral distribution of solar radiation;
VÎ» â€”â€”â€”spectral luminous efficiency;
Km = 683 lm /W, which is a constant under bright visual conditions.
K is called radiant light equivalent and is used to characterize the relationship between irradiance and illuminance, which varies with meteorological conditions.
Equation (1) shows that illuminance data can be obtained as long as there is irradiance data and a radiation light equivalent model. Therefore, the key to obtaining typical annual data for illuminance is which irradiance data is selected and which radiation-equivalent model is used.
2. 3 irradiance typical annual data
In the field of building simulation, hourly time-based calculations have been widely used. Some building energy simulation software at home and abroad, such as EnergyPlus, provides time-to-day typical meteorological data, including solar irradiance and other parameters. . The Daysim software developed by Christoph et al. for year-round lighting simulation can use the weather data provided by EnergyPlus as a calculation parameter. However, the meteorological data provided by the international community cannot guarantee the reliability and accuracy of the source data, and the meteorological elements are not comprehensive. Therefore, it is not suitable as the standard meteorological data for building simulation analysis in China.
China's self-developed building thermal environment simulation analysis software
DeST provides a set of hourly and typical annual data for the simulation of the built environment. The data is based on meteorological observations from 1971 to 2003 of the country's 270 ground meteorological stations provided by the Meteorological Information Office of the Meteorological Information Center of China Meteorological Administration. Reliable and can truly reflect the characteristics and laws of Chinese meteorology. These meteorological data also include irradiance and other meteorological elements that establish a model of the radiant light equivalent. Therefore, here we choose this set of typical annual meteorological data as the basic data, and use the radiant light equivalent method to obtain typical annual data of illuminance.