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The influence of the airflow in a solar passive building on the indoor air quality and thermal comfort levels was investigated. The numerical study for a university library was conducted using a software that simulates the building thermal behavior with complex topology, in transient conditions, for evaluating the indoor air quality and occupants’ thermal comfort levels for typical summer and winter days. Solar radiation was used as a renewable energy source to increase simultaneously the thermal comfort and air quality levels and reduce building energy consumption. Regarding the solar passive building, consideration was given to all of the building structure envelope, shading devices and interior details, while in the solar active building active ventilation was used. To analyze the airflow that simultaneously provides the best indoor air quality and thermal comfort levels, a new integral methodology based on the minimization of the total number of uncomfortable hours was used. The results show that it was possible to determine an air change rate that ensures a good compromise between thermal comfort and indoor air quality. An optimal air change rate of two and three renewals per hour had been determined, respectively, for winter and summer conditions.

Accurate measurements of global solar radiation and atmospheric temperature, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight and portable sensor was developed, using artificial neural network models as the time-series predictor mechanisms. These have been identified with the aid of a procedure based on the multi-objective genetic algorithm. As cloudiness is the most significant factor affecting the solar radiation reaching a particular location on the Earth surface, it has great impact on the performance of predictive solar radiation models for that location. This work also represents one step towards the improvement of such models by using ground-to-sky hemispherical colour digital images as a means to estimate cloudiness by the fraction of visible sky corresponding to clouds and to clear sky. The implementation of predictive models in the prototype has been validated and the system is able to function reliably, providing measurements and four-hour forecasts of cloudiness, solar radiation and air temperature.

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