Research On Multi-objective Optimization Design Method Of Ultra-low Energy Residential Buildings In Cold Regions

Under the dual pressure of energy crisis and environmental protection,building industry actively responds to the call for energy conservation and emission reduction,and starts the exploration and practice of passive ultra-low energy buildings(hereinafter referred to as ultra-low energy buildings)to improve building energy efficiency and create a healthy and comfortable indoor environment.The complexity of ultra-low energy buildings design restricts its promotion and application.On the one hand,the design process covers many design variables,and each design variable has a series of feasible values.It takes a lot of time and effort to evaluate the value schemes of different design variables;on the other hand,multiple design objectives conflict with each other,and improve the performance of one goal often comes at the expense of others.A good design scheme should balance the relationship between building energy saving,comfort,and economy.At this stage,relevant researches focus on single-objective optimization and double-objective optimization design,which is difficult to accurately reflect the coupling relationship between design variables and multiple objectives.Taking typical residential buildings in cold regions of zhengzhou as an example,this paper studies the multi-objective optimization design method of ultra-low energy residential buildings by building a multi-objective optimization model based on PSO-NSGA-II algorithm,aiming at the primary energy demand,indoor thermal comfort and life cycle incremental cost.The main research contents are as follows:1)By sorting out the research on multi-objective optimization design of ultra-low energy residential buildings,this paper points out the shortcomings of optimization design research and the direction of further research.Next,by comparing the Chinese and German ultra-low energy building standards,analyzing five key design elements,combining with the design principles and node structure of ultra-low energy buildings,heating,cooling and lighting are selected as primary energy demand objects,and the indoor environment is built according to the recommended values.2)A set of scientific and reasonable index system is constructed by literature research method,Delphi method and questionnaire survey method.Taking a typical residential building as an example,this paper analyzes the theory of primary energy demand,indoor thermal comfort and life cycle incremental cost.Through market research and equation calculation,build an incremental cost database;The Design Builder simulation software is used to establish two sets of models of reference buildings and ultra-low energy buildings,and output building energy consumption and PMV value,so as to establish a multi-objective optimization design objective database.3)Aiming at the limitations of NSGA-II’s dependence on the initial population and slow convergence speed,the advantages of PSO’s strong memory capacity,simple structure and fast convergence speed,the PSO-NSGA-II fusion algorithm is proposed based on the fusion feasibility analysis theory.By comparing the three performance indexes of IGD,Δ and running time with the calculation results of NSGA-II,it is proved that the optimized fusion algorithm has better performance in convergence,diversity and operating efficiency,and is more suitable for multi-objective optimization design research of ultra-low energy residential buildings in cold regions.4)A multi-objective optimization model based on PSO-NSGA-II algorithm is constructed and applied.Based on the multi-objective optimization theory,the Matlab platform is used to build a multi-objective optimization model,and the PSO-NSGA-II algorithm is used as a search engine for design schemes,loaded into the ultra-low energy building multi-objective optimization design database,the optimization design scheme is generated and stored.The designer can choose the best energy saving effect,the best economic effect,the best indoor comfort and the best balance scheme according to different preferences.This paper proposes that the multi-objective optimization model based on the PSO-NSGA-II algorithm has strong applicability and generalization,which can be further extended to the optimization design of ultra-low energy buildings with different climatic characteristics and building types.The design suggestions provide a certain reference value and guidance for the design of ultra-low energy residential buildings in cold regions,and are of great significance for promoting the localization and large-scale application of ultra-low energy buildings.