Evaluating a BiPV sun shading system with various software and methods
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This paper aims to explore the attractiveness of a BiPV (building integrated photovoltaic) fixed façade shading systems in view of a deep retrofit of the residential building envelope. While doing so is necessary to access the confidence and differences among optimization and simulation tools. A facade equipped with a fixed BiPV shading system is simulated with different methods, software and modelling assumptions. The output of the simulations is compared and discussed, underlining the strong and weak points of each considered method. The performance of the BiPV façade is accessed by comparison with a more traditional one without BiPV. The traditional façade is characterized by a lower WWR (window to wall ratio) compared to the BiPV one because they have the same DF (daylight factor) by design. The BiPV façade is characterized by a better behavior toward annual radiative solar gain, while the traditional façade relies on lower thermal conductivity. Both the façade solutions are the result of a performance optimization method developed at EURAC and described in the paper. The method is based on the use of genetic optimization algorithms to find the parameters, WWR tilt angle and distance from the window, that maximize target performance indicators. Aims of the study are to evaluate the BiPV impact on the façade (i.e. whether it ensures an improved annual thermal performance or only better energy balance thanks to energy production) and to compare the results obtained with different simulation methods (i.e. by evaluating the results coherency and discrepancy). The comparison between these two facades performance and the consequent BiPV impact assessment, is carried out with different methods by coupling different software tools (e.g. PVGIS + COMFEN, Archsym + postprocessing). The software tools capabilities, the relative errors and the simplifying assumptions that can be considered safe in a performance-driven design perspective are discussed in the paper. Keywords: BiPV, optimization, software, genetic algorithms, daylight, heating and cooling.