Multi-objective Optimization Of Energy Consumption-cost-thermal Comfort Of Public Buildings

Based on the analysis of the building environment and social environment of public buildings,this paper summarizes the characteristics of large volume and complex elements of public buildings,and makes clear the importance and necessity of reducing energy consumption and investment cost on the premise of improving indoor thermal comfort.Therefore,based on the current situation of the construction industry,this paper proposes a multi-objective optimization problem considering the energy consumption,cost and thermal comfort of public buildings,and constructs the corresponding model to solve the problem and generate the optimal design scheme.Firstly,this paper studies the definition,types and characteristics of public buildings,analyzes the key factors that affect the energy consumption,cost and thermal comfort of public buildings,and focuses on the optimization objectives,models and algorithms selected by current researchers for multi-objective optimization of buildings.Secondly,the PMV comfort evaluation index is selected as the quantitative index of human thermal comfort,and the heat transfer coefficient of the exterior wall in the envelope is used as the optimization variable to build the multi-objective optimization model of energy consumption cost thermal comfort of public buildings.According to the complexity of the multi-objective optimization problem of public buildings,based on the analysis of the algorithm principle,the fast non dominated sorting genetic algorithm with adaptive probability adjustment mechanism is used to improve the algorithm,which ensures the search performance of the algorithm and improves the evolutionary convergence efficiency.In addition,in order to verify the effectiveness of the model and algorithm,based on the actual project,a university office building in Shandong Province is selected for case analysis,and the optimal optimization scheme and public building design scheme meeting different preferences are obtained.The improved algorithm is compared with the algorithm before improvement,and the results show that the improved algorithm performs better in solving this problem.Finally,according to the solution results and the actual situation,this paper puts forward the relevant countermeasures and suggestions of public building design.