اعتبار تجربی مصرف انرژی روشنایی با استفاده از روش شبیه سازی یکپارچه
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|6331||2013||11 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Energy and Buildings, Volume 57, February 2013, Pages 144–154
The objective of this study is to evaluate the predictive accuracy of lighting energy consumption carried out by the EnergyPlus program and by the integrated simulation method (ISM), using the Daysim program. EnergyPlus calculates the interior illuminance based on the split-flux and radiosity method, and overestimates the interior illuminance, and we can see large differences in the EnergyPlus interior illuminance results. MBE by the split-flux method was found to range between 81.5% and 463.4%, and the largest MBE occurred at the deepest point. The Daysim program calculates the interior illuminance based on the ray-tracing method, and the largest MBE is −18.9%, at the middle point of the room. Lighting energy consumption differences are caused by the interior illuminance calculation algorithms in the simulation programs. As a result, the lighting energy consumption derived by the EnergyPlus program without ISM is approximately 34.6% smaller, than that of real consumption. The ISM was improved in the prediction accuracy of lighting energy consumption by 24.6% in absolute value. The results of the lighting energy consumption with ISM are relatively more accurate than the EnergyPlus results without ISM, because the modified lighting schedule is similar to the actual situation.
The use of daylighting is a cost-effective way to reduce building energy consumption, and improve the quality of the visual environment. In an office building, lighting energy consumption comprises about 30% of the total energy consumption in South Korea. Therefore, we should consider the daylighting design, and apply lighting control systems to reduce energy consumption. In the design phase of the building, we can predict the building performance using computer simulation. There are various tools that have daylight algorithms, such as Radiance/Daysim  and , SPOT , ECOTECT , and EnergyPlus . We therefore need to choose the appropriate daylight algorithm for each case. The EnergyPlus program is an energy analysis and thermal load simulation program developed by the U.S. Department of Energy , while Daysim is a Radiance-based daylighting analysis tool that has been developed at the National Research Council Canada, and the Fraunhofer Institute for Solar Energy Systems in Germany . The two programs give different results of lighting energy consumption, due to the differences of each daylight algorithm. According to a review , simulated daylighting results of the EnergyPlus and Daysim programs have divergences. It is necessary to study the divergence between the simulation results, and the measurement of lighting energy consumption, with the application of a photosensor dimming control system. There are few articles about lighting energy consumption measurement, especially in terms of comparison between measurement and simulation results under real weather conditions in Korea. Therefore, from this study, we need to evaluate the prediction accuracy of lighting energy consumption. Also, it is important to evaluate the prediction of the interior illuminances in daylighting simulation, because they are closely related to the lighting energy consumption.
نتیجه گیری انگلیسی
In the measured period (2011/06/04–2011/10/20), the sky types of overcast sky and intermediate sky are mostly observed from June to August, and clear sky is mostly observed from September to October. Clear sky is about 20.1%, overcast sky is about 29.2% and intermediate sky is about 50.6%, according to the sky clearness by Fakra. Exterior global horizontal illuminances simulated by EnergyPlus and Daysim are about 7% smaller than the measurement, and we can consider that the simulated results by EnergyPlus and Daysim are very similar to the measured exterior global horizontal illuminance. Some conclusions that can be drawn from this study include: (1) The measured diffuse irradiance is corrected with a shadow ring correction model developed by Muneer and Zhang, and the corrected diffuse irradiance is increased by 2–3% over the measured diffuse irradiance. (2) Comparison of the split-flux and the radiosity method in EnergyPlus was performed in different geometry conditions, such as a simple geometry (single skin facade) and a complex geometry (double skin facade). As a result, the split-flux method is better for evaluating the interior illuminance and the lighting energy consumption in a double skin facade. (3) As the work plane illuminance simulated by EnergyPlus is based on the split-flux method, the result is larger than the measurement. The MBE was found to range between 81.5% and 463.4%, and the largest MBE occurred at the point of 5 m depth. The Cv(RMSE) was found to range between 285% and 877%. (4) The Daysim program calculates the interior illuminance based on the ray-tracing method, and the smallest MBE is 4.8% at the depth of 1 m. It is similar to the measurement, and we can consider that the interior illuminance was enhanced when we used Daysim, rather than using EnergyPlus only. (5) The average value of the lighting power fraction using EnergyPlus is 0.53 (65.4% of the measurements), and the average value of the lighting power fraction using Daysim is 0.73 (90% of the measurement). The Daysim lighting power fraction is more similar to the measurement, than the EnergyPlus simulation result. (6) Simulated lighting energy consumption differs from the measurement, because of the interior illuminance calculation algorithms in the simulation programs. The lighting energy consumption is about 87.0 Wh by measurement, and about 56.9 Wh by the EnergyPlus simulation. There is a difference of −34.6% in the simulation results. While the EnergyPlus program is a worldwide simulation tool for the prediction of a building's total energy consumption, and has many benefits, it has a limitation in the daylighting calculation algorithms.