内蒙古中部超低能耗农牧民居围护结构多目标优化设计OA

In order to solve the problems of unreasonable thermal insulation design,high heating energy consumption and poor indoor thermal comfort in the outer envelope of farmers and herdsmen's residences in central Inner Mongolia,the data set of ultra-low energy consumption farmers and herdsmen's residences in central Inner Mongolia was established by EnergyPlus and JEPlus software,and the BP neural network agent model was established with winter heating energy consumption and incremental cost of energy-saving design of envelope as optimization objectives and heat transfer coefficient of envelope as design variables.The BP neural network proxy model is used as the fitness function of NSGA-Ⅱ algorithm to study the multi-objective optimization of envelope.After 50 iterations,the Pareto optimal solution set is obtained,and the optimal scheme is finally selected.The results show that by optimizing the enclosure structure of typical farmers'and herdsmen's houses in central Inner Mongolia,the heating energy consumption of residential houses in winter is reduced by 3 792.49 kWh,which meets the requirements of ultra-low energy consumption buildings.The average PMV value in cold month is increased from-1.71 to-0.06,and the static investment payback period of energy-saving design is 16.26 years.