Research On Multi-objective Optimization Of Shading Louver System Based On Genetic Algorithm

With economic development and urban renewal construction,the number of office buildings is gradually increasing,and people’s requirements for the overall performance of buildings are also increasing.Under the guidance of the concept of green sustainable design,office buildings are required to meet the requirements of a good indoor light and thermal environment while achieving energy saving.The multi-objective optimization method can efficiently arrive at a reasonable design plan,which is of great significance in the building design stage and energy-saving renovation.First,the paper elaborates the relevant theory of multi-objective optimization of the exterior shading louver system of office buildings,and selects the comprehensive energy consumption of the building throughout the year,the percentage of useful daylight illumination UDI_100-2000 and indoor thermal comfort PMV as the evaluation indicators of building performance.Secondly,a visual analysis of the meteorological conditions in Guangzhou area was carried out,and the necessity of exterior shading design for office buildings under the local climate characteristics was obtained.Then,the office building was parametrically modeled on the Grasshopper platform,and the Ladybug&Honeybee weather and building performance analysis plug-in combined with Energy Plus,Daysim,and Radiance were used to analyze the building energy consumption and light and thermal performance of the office building standard room model.Then,the orthogonal experiment method is used to study the influence degree and trend of the various parameters of the louver system on the three building performance indicators,and the louver system parameters with significant influence are selected as the optimization variables of the multi-objective optimization design.Finally,the distance from the louver to the glass,the width and spacing of the louver and the deflection angle are used as optimization variables.The comprehensive energy consumption of the building,the percentage of useful daylight illumination UDI_100-2000 and the indoor thermal comfort PMV are used as the optimization goals,which are set in the Octopus multi-objective optimization platform.HypE Reduction and HypE Mutation algorithm mechanisms build a multi-objective genetic algorithm optimization model.After 90generations of optimization operation,the Pareto front solution set was obtained,the convergence and distribution performance of the understanding set were verified,and 7weights were assigned to the non-dominated solution set,and 10 exterior shading louver design control strategies were obtained.The comparative analysis of comprehensive energy consumption and light and thermal performance of buildings on a monthly basis and on a typical weather day by hour proves the rationality of the optimization design of the exterior shading louver system based on genetic algorithm and the significant improvement in building energy saving,natural lighting and indoor thermal comfort performance effect.A genetic algorithm-based multi-objective optimization strategy was designed on the Grasshopper parametric platform in this study,which integrates the establishment of building model,building performance simulation analysis and multi-objective optimization calculations on the same platform,avoiding the error of data interaction between traditional platforms as well as repeated modeling,it provides new ideas and theoretical references for office building performance simulation and design optimization of exterior shading louver systems.