Abstract:

Elevated railway stations are usually large-span buildings and require skylights. Traditional skylight design methods have difficulties in solving the multi-objective problem of complex requirements in lighting and energy-saving. In order to realize the multi-objective optimization of the flat skylight of the high-speed railway station, based on the pre-design parameter settings of the flat skylight of the elevated high-speed railway station, this paper constructed a set of genetic algorithm-based multi-objective optimization methods using Rhino and Grasshopper platforms, building performance simulation tool called Ladybug, and multi-objective optimization tool called Octopus. Multi-objective optimization method for flat skylight goes through the steps of determining variables, determining optimization objectives, building models and programming, using Rhino and Grasshopper to build a simplified parametric model, importing the Ladybug tool for performance analysis, and using Octopus tool to carry out iterative multi-objective optimization according to the analysis results. The optimization process can automatically change and simulate the parameterized part of the model, and record and compare the results of each change and simulation. And finally, it finds out the parameters that best meet the set multiple objectives. Returning the parameters to the parametric model can yield the optimal model and the corresponding building performance simulation results. Furthermore, an empirical analysis was carried out by taking Guangzhou Baiyun Station as an example. According to the requirements of the main lighting standards at home and abroad, the study first set the daylighting factor and the daylighting uniformity up to the standard, the useful daylighting illuminance as significant as possible, the possibility of glare occurrence as small as possible, and the solar radiation as small as possible as the target system. Then it used the method for multi-objective optimization. The results show that compared with the original scheme, the final scheme meets the basic standard of daylighting factor and has better lighting uniformity, useful daylighting illuminance, glare occurrence possibility, and solar radiation under the lighting intensity conditions. The proposed method has a wide range of application scenarios and more flexibility and can provide references for related research.

Key words: elevated railway station, flat skylight, multi-objective optimization, Guangzhou Baiyun Station