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Multi-objective energy and daylight optimization of amorphous shading devices in buildings
Ist Teil von
Solar energy, 2019-06, Vol.185, p.100-111
Ort / Verlag
New York: Elsevier Ltd
Erscheinungsjahr
2019
Link zum Volltext
Quelle
Elsevier ScienceDirect Journals Complete
Beschreibungen/Notizen
•A novel shading design enhanced by multi-objective optimization is presented.•The amorphous shading device reduced total energy consumption of an office room up to 14%.•Minimization of total energy consumption and maximization of UDI are the objective functions.•We use surrogate modeling by making regression analysis of each daylight point.•Performances of two Pareto fronts are compared using Hyper Volume indicator.
As integrated components of the building envelopes, shading devices are the elements designed for stopping excessive amount of direct and indirect sunlight passing through and for avoiding undesirable admission of light into glazed buildings. Shading devices also reduce the operational cost of active systems, mostly heating and cooling, by providing considerable energy saving without completely blocking the daylight. However, the conventional shading device types in real world applications and even the ones presented in the literature stick to non-amorphous shapes providing limited improvement of the energy performance with negligible rates. Considering the lack of amorphous solutions in the literature, we propose novel design alternatives of energy-efficient shading device with panels in amorphous forms generated by parametric modeling and performance evaluation-based optimization in contrast with the conventionally designed structures. Initially, a performance evaluation-based optimization model was developed by employing evolutionary multi-objective optimization algorithms to overcome the complexity of the design process. Moreover, minimization of TEC (Total Energy Consumption) and maximization of the UDI (Useful Daylight Illuminance) are defined as the main objective functions to be optimized by non-dominated sorting genetic algorithm (NSGA II) and self-adaptive continuous genetic algorithm with differential evolution (JcGA-DE) in the shading model. According to the numerical results of the annual energy consumption, we managed to reach considerable energy saving up to 14%, while keeping the daylight availability above 50%.