Multi-objective Optimization Of Building Energy Efficiency Based On Genetic Algorithms

With the energy crisis and environmental problems become increasingly prominent,energy conservation has become an important issue in the world.The building energy consumption is an important aspect of China's energy consumption,while the total amount of building energy consumption which has become a huge burden on China's national economy is also rising,so it is necessary to do building energy conservation work.On the other hand,with economic development and the improvement of people's living standard,the living and working environment in China have been greatly improved.However,if a better indoor thermal environment is gotten at the expense of air-conditioning energy consumption,then building energy efficiency will be reduced.In this paper,the study is done from the viewpoint of reducing energy consumption and improving thermal comfort.The research methods and contents are as follows:First of all,the study summarizes the main factors that affect the building energy consumption,including the building shape coefficient,the building orientation and the envelope structure performance,by reviewing the literature of building energy efficiency and thermal comfort.The performance of retaining structure is an important factor in building energy saving,and it is also a major factor affecting the thermal comfort of the human body and the environment for energy exchange.Therefore,the effects of retaining structure were studied in detail.Secondly,on the basis of theoretical analysis and previous research on building energy efficiency and thermal comfort,the study summarizes the functional relationship between building energy consumption and retaining structure,thermal comfort and retaining structure.In consideration of the retaining structure cost,the multi-objective optimization was studied by using genetic algorithm.Thirdly,this study analyzes the theory of multi-objective optimization and genetic algorithm principles,selects heat transfer coefficient of exterior wall and window as optimization variables,With the goal of low energy consumption,low cost and better thermal comfort,the optimization model is established,and the optimization program was worked out and optimized by MATLAB.Finally,based on actual engineering project,applying the principle of genetic algorithm and operating optimization of procedure,the lowest value of heat transfer coefficient of exterior wall and window are found out which can minimize the energy consumption,the cost of building envelope and achieve the optimal thermal.