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Multi-Objective Optimization-Oriented Energy-Saving Structure Optimization Of Enclosure Structure Of Grassland Dwellings In Western Inner Mongolia

Posted on:2020-01-29Degree:MasterType:Thesis
Country:ChinaCandidate:Q ShangFull Text:PDF
GTID:2392330590481760Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
Most of the grassland dwellings in western Inner Mongolia are self-built,and the design of enclosure structure is not standard,which leads to the poor thermal performance of grassland dwellings.In this paper,the energy saving optimization design of enclosure structure is used to balance the solar energy utilization rate,building heating energy consumption,indoor thermal comfort and the engineering cost of enclosure structure.The study on the optimization of energy saving structure of grassland residential buildings in western Inner Mongolia provides the basis and reference for the energy saving optimization of grassland dwellings in Inner Mongolia pastoral areas.In this paper,the basic situation of grassland dwellings is obtained by questionnaire and field investigation,so as to establish the basic model of grassland dwellings.First,the energy consumption simulation software is used to improve the solar energy utilization rate of grassland houses through the optimal orientation and window and wall area ratio.Secondly,the heat transfer coefficients of the outer door,outer window,exterior wall,roof,floor and inner partition wall of grassland folk house are changed,and the values of heating energy consumption and indoor thermal comfort of the building are obtained by using Designbuilder software to simulate the heat transfer coefficient of the outer door,outer window,external wall,roof,floor and inner partition wall.At the same time,the engineering cost of each enclosure structure is calculated by Glodon,and the multi-objective optimization model is established by using the method of multivariate nonlinear fitting.Then,the multi-objective optimization model is optimized by NSGA-II algorithm,and the Pareto optimal solution is obtained.The data envelopment analysis(DEA)method is used to analyze the effectiveness of Pareto optimal solution,and the effective solution is obtained.Finally,according to the effective solution,the energy saving optimization structure of grassland residential enclosure structure is worked out.Based on the optimization of energy saving structure of grassland residential enclosure in western Inner Mongolia,the following results are obtained.The main results are as follows:(1)the best orientation of grassland dwellings in Wulat Houqi area is 2.5 degrees south east,south,west and north.The window wall area ratios are 0,0.45,0,0.05,respectively.(2)the optimization models of three objectives and the heat transfer coefficients of each enclosure structure are established,and the optimization model is tested and the error analysis is carried out.The R~2 values of the three optimization models are 0.960,0.959 2 and0.912 8,respectively,indicating that the fitting of the model is good.The heat transfer coefficient of each part of the enclosure structure is redesigned,and the error analysis between the simulation results and the model results is carried out.The difference between the simulation results and the model results is very small,which shows that the model is credible.(3)the NSGA-II algorithm is used to optimize the optimization model,and the Pareto optimal solution of the heat transfer coefficient of each enclosure structure is obtained.After that,the data envelopment analysis method is used to analyze the scheme 3 and scheme 9 are effective schemes.In summary,through the optimization of energy-saving structure of grassland residential enclosure in western Inner Mongolia,it provides the train of thought and basis for the research of energy-saving transformation of grassland folk house with relatively poor energy saving.
Keywords/Search Tags:Grassland dwellings, Heat transfer coefficient of enclosure structure, Building heating energy consumption, Indoor thermal comfort, Nonlinear regression fitting
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