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Numerous metrics and indices have been proposed for the assessment of thermal perception and comfort. Commonly used indices based on the estimate of the heat flow between the human and its environment includes the well-known Fanger's method, also known as the PMV-PPD thermal comfort model. Recently this thermodynamic approach has been expanded with the application of the second law of thermodynamics. In this paper, an exergy-based analysis of the relation between the human and its environment is presented. Heat and mass flow rate due to convection, radiation, evaporation and respiration are calculated and expressed in terms of exergy loss. This value is used in the modified Fanger's thermal comfort model, where the heat balance equation is replaced by the exergy loss. The paper builds upon prior studies on determination of internal and external exergy losses by revised and newly defined formulas taking into account clothing and indoor conditions. The results quantitatively show that thermal energy load in the original Fanger's PMV model could be substituted by exergy loss and it corresponds to a certain level of subjective assessed thermal comfort level. [ABSTRACT FROM AUTHOR]

Abstract The building's balance point temperature represents the outdoor temperature at which no auxiliary energy is needed to ensure thermal comfort. Its estimation presents the main challenge of applying the degree day method for space cooling applications, since in addition to building thermal characteristics it also depends on internal and external heat gains. In this paper, a new approach for determining the instantaneous balance point temperature, based on an optimization-based grey-box modelling procedure, is presented. The developed grey-box model is built on an assumed functional dependency between the building thermal load and the power demand of its HVAC system. Its application requires only the use of basic building geometric parameters apart from the cooling electricity demand and corresponding meteorological data, which are utilized to estimate the model parameters using a derivate-free optimization procedure. Additionally, a new technique for visualizing and analyzing the behavior of the obtained instantaneous balance point temperature is introduced. The proposed methodology is verified on a set of artificially generated data, achieving an average prediction error of 5.2%, and its applicability demonstrated on a sample of real tertiary sector buildings. The results indicate that the presented methodology can be used to deduce building and corresponding HVAC system characteristics. Highlights • An approach for determining the instantaneous balance point temperature is proposed. • The approach is based on an optimization-based grey-box modelling procedure. • The approach is verified on artificial data and tested on data from real buildings. • A visualization technique for analysing the balance point temperature is introduced. [ABSTRACT FROM AUTHOR]