Sensitivity Analysis Of Building Energy Consumption And Optimization Of Thermal Performance Parameters For Passive Houses In A Severe Cold Area

In recent years,passive buildings have attracted more and more attention in the construction industry.Promoting buildings towards nearly zero energy consumption is an essential way to achieve carbon neutralization in the construction field.Severe cold areas of China are characterized by severely cold winters with the heating period lasting nearly half of the year,which leads to large heating damands.While the widespread use of solid fuels for space heating causes severe haze pollution in winter.Based on the above two regional characteristics,achieving nearly zero energy consumption in cold regions while maintaining indoor air quality exists a huge challenge.At present,the implementation of relevant standards for nearly zero energy consumption buildings is still guided by technical measures,and there lacks research on global analysis and performance optimization research.First,a post-occupancy evaluation of indoor environmental quality and heating energy consumption was conducted in the first pilot passive building.The physical parameters of indoor thermal environment and air quality were measured,in parallel with a subjective occupant survey.For comparative purposes conventional buildings in the same community were also evaluated with the same protocols.The superior envelope of the passive building could increase the indoor operative temperature.The indoor CO₂ concentration was found to be lower than that of the conventional building owe to the mechanical ventilation system.However,in the heating season,indoor PM2.5 concentration exceeded the standard due to the severe outdoor haze during the heating season,indicating that the filtration efficiency of the fresh air system for fine particles is insufficient.Besides,energy consumption for heating operation exceeds the annual heat consumption target as stipulated in China’s technical standard for ultra-low energy consumption buildings with the deviation of33.6%.Secondly,to address the problem of excessive indoor PM2.5 concentration due to insufficient filtration efficiency,the minimum design efficiency of the filter was solved by establishing a particulate matter mass balance model,combining continuously monitored indoor and outdoor PM2.5 data and air change rates.Then the influence of filter efficiency on the energy consumption of fresh air system is analyzed.The minimum PM2.5 filtration efficiency required to meet the WHO standard（25μg/m³）,China’s primary standard（35μg/m³）and secondary standard（75μg/m³）indoors was calculated using the outdoor PM2.5 concentration without guaranteeing a certain number of days（5d,10d,15d,20d）as the outdoor design concentration.Thus the selection range of the minimum design efficiency of the filter was obtained.Thirdly,in view of the large number of passive house design parameters and the uncertainty of parameter values,the positive uncertainty of building energy consumption was analyzed.Sensitivity analysis is introduced to quantify the impact of the uncertainty of design parameters on energy consumption.Standard rank regression coefficient（SRRC）based on regression and Sobol method based on variance were selected to evaluate the sensitivity of each parameter to building energy consumption.This study then proposed a simulation-based multi-objective optimization method.The artificial neural network model was set as the surrogate model.Fourthly,Energy Plus was used to build an energy simulation model for the passive building in the severe cold region,and a module on natural ventilation was added to the benchmark model Based on the above benchmark model,combined with Monte Carlo simulations,two sensitivity analysis methods,standard rank regression（SRRC）and variance-based Sobol,were applied to conduct a global sensitivity analysis of the uncertainty in the design parameters.The results show that outdoor air system design（outdoor air rate and heat recovery efficiency）has the most important effects on heating and total primary energy use.While solar heat gain coefficient and building orientation present the predominance on cooling.Building envelope parameters have a limited impact on the total energy consumption when buildings move from the fourth-step energy efficiency standard to passive house standard,but increase the cost of building construction and subsequently require global optimisation of the envelope parameters from a whole life cycle perspective.Finally,this study proposed a simulation-based multi-objective optimization method to minimize both life cycle cost and CO₂ emissions of buildings.This investigation selected insulation thickness,window type,window-to-wall ratio,overhang depth and building orientation as design variables.The study ran parametric simulations to establish a database and then used artificial neural network models to correlate the design variables and the objective functions.In the end,the multi-objective optimization algorithm NSGA-II was used to search for the optimal design solutions.In summary,this paper presents a post-evaluation of the first passive house in a severe cold region.Combining the measured data and theoretical analysis,a calculation method for the design efficiency of the filter of the fresh air system was proposed.Combining the measured data and numerical simulations,a sensitivity ranking of the factors influencing the energy consumption of passive houses in severe cold regions is obtained.Finally,the optimal Pareto solutions for the design parameters was solved from the perspective of the whole life cycle cost and carbon emission.The research provides some theoretical guidance and technical support for the indoor environmental control,low carbon and energy efficient building design of passive houses in severe cold regions.