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Statistical Evaluation of Dimmable Interior Lighting System Consumption Using Daylight

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Book cover Intelligent Systems for Computer Modelling

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 423))

Abstract

From the power engineers point of view, at the present time, the necessity to predict the consumption of lighting systems becomes more and more urgent at the time of the project phase. The reason is to compare the projects from different investors and especially to compare the projects with regulated (dimmed) lighting systems (these are regulated at a constant level of illumination) with the projects of unregulated lighting. In that case, the designer has to be able to determine the payback of regulated lighting system in comparison with classic unregulated lighting systems. Nowadays, it is possible to calculate the potential savings. The calculating is determined by the LENI (Lighting Energy Numeric Indicator), according to EN 15193, which is based upon the analytical estimate of potential savings calculated on the base of empirically derived coefficients for standardized rooms, standardized operations, etc. However, this model is not based on real specific situations. Therefore, the team of VSB-TU Ostrava developed a predictive model, which is based on the daylight dynamics in specific lighting conditions. The long-term measurements were carried out to verify whether the model´s results correspond to the real facts. The statistical evaluation of the model´s conclusions and the real measured rates was carried out as well.

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References

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Acknowledgment

This article was prepared with the support of the project “Transmission of control signals in lighting systems” SP2015/182, by institution of VSB-TU Ostrava.

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Correspondence to Tomáš Novák .

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Novák, T., Bos, P., Šumpich, J., Sokanský, K. (2016). Statistical Evaluation of Dimmable Interior Lighting System Consumption Using Daylight. In: Stýskala, V., Kolosov, D., Snášel, V., Karakeyev, T., Abraham, A. (eds) Intelligent Systems for Computer Modelling . Advances in Intelligent Systems and Computing, vol 423. Springer, Cham. https://doi.org/10.1007/978-3-319-27644-1_16

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  • DOI: https://doi.org/10.1007/978-3-319-27644-1_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27642-7

  • Online ISBN: 978-3-319-27644-1

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