Proposal and evaluation of typical illuminance year (TIY) generation procedures from illuminance or irradiance data for daylight assessment in the long term
When assessing the long-term daylight availability or the performance of natural lighting systems in a given location, it is necessary to have representative data of local daylight conditions. The use of a daylight test reference year (TRY) becomes a good option in these cases. This paper proposes a...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Universidad Pública de Navarra |
| Repositorio: | Academica-e. Repositorio Institucional de la Universidad Pública de Navarra |
| OAI Identifier: | oai:academica-e.unavarra.es:2454/39432 |
| Acceso en línea: | https://hdl.handle.net/2454/39432 |
| Access Level: | acceso abierto |
| Palabra clave: | Typical Illuminance year Luminous efficacy models Daylight |
| Sumario: | When assessing the long-term daylight availability or the performance of natural lighting systems in a given location, it is necessary to have representative data of local daylight conditions. The use of a daylight test reference year (TRY) becomes a good option in these cases. This paper proposes and evaluates a procedure for the generation of a typical illuminance year (TIY) considering illuminance as the only variable for selecting the typical periods that make up the reference year. Two versions of TIY are presented, one composed of 12 typical months selected from the series of observations and another composed of 365 typical days. Each of these versions is used to obtain a global illuminance TIY (TGIY) and a diffuse illuminance TIY (TDIY) from a 27-year dataset corresponding to the Vaulx-en-Velin station (France). Furthermore, 12 luminous efficacy models have been evaluated in order to obtain a TIY from a TRY generated from irradiance data when no illuminance data are available. Thus, a global luminous efficacy model and a diffuse model are selected after benchmarking different models, considering both their original coefficients and those adjusted to local conditions. The results reveal that the monthly version of the TGIY and the daily version of the TDIY show the best overall fit to the long-term dataset. TIYs obtained from illuminance data are also observed to be statistically indistinguishable from those obtained after applying a luminous efficacy model to an irradiance-based TRY. |
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