This paper describes the Energy and Daylighting optimization of a fixed inclined panel which shades an office room with a south exposed window. The window features also user deployable internal Venetian blinds. Energy analysis takes into account the primary energy required for heating, cooling and artificial lights. Different numerical codes have been employed in order to perform the simulations required by the optimization process: Daysim estimates the artificial light consumption based on daylighting distribution, ESP-r computes heating and cooling loads and modeFRONTIER integrates the simulation codes in an automatic optimization loop. The performance of an algorithm specifically designed to deal with problems involving long simulation times (combining response surfaces and genetic algorithms) has been successfully evaluated; the algorithm has then been applied in the optimization loop. The optimized solutions are analysed in this paper, in particular three solutions have been selected: minimum primary energy consumption, minimum hours of blind deployed and an intermediate solution. The analysis compares the primary energy consumption and daylighting performance on the basis of the Useful Daylight Illuminance indicator and the time history of illuminance on predefined locations.

FAST energy and daylight optimization of an office with fixed and movable shading devices

MANZAN, MARCO;CLARICH, ALBERTO
2017-01-01

Abstract

This paper describes the Energy and Daylighting optimization of a fixed inclined panel which shades an office room with a south exposed window. The window features also user deployable internal Venetian blinds. Energy analysis takes into account the primary energy required for heating, cooling and artificial lights. Different numerical codes have been employed in order to perform the simulations required by the optimization process: Daysim estimates the artificial light consumption based on daylighting distribution, ESP-r computes heating and cooling loads and modeFRONTIER integrates the simulation codes in an automatic optimization loop. The performance of an algorithm specifically designed to deal with problems involving long simulation times (combining response surfaces and genetic algorithms) has been successfully evaluated; the algorithm has then been applied in the optimization loop. The optimized solutions are analysed in this paper, in particular three solutions have been selected: minimum primary energy consumption, minimum hours of blind deployed and an intermediate solution. The analysis compares the primary energy consumption and daylighting performance on the basis of the Useful Daylight Illuminance indicator and the time history of illuminance on predefined locations.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2891983
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