Multi-objective Optimization Research On Energy-saving Design Of Rural Prefabricated Houses

In the context of the current global realization of low-carbon development,building energy efficiency is of great practical significance for China’s construction industry to reach the goal of carbon neutrality and achieve sustainable development.The energy-saving design of rural prefabricated houses is an important step to promote the construction of low-carbon farm houses and create a low-carbon countryside.However,in engineering practice,there are many problems:energy-saving strategies are mostly implemented with qualitative instructions,and quantitative research on building performance is insufficient;energy-saving design is faced with multiple opposing objectives of energy,economy and environment;and there is a lack of effective and rapid design optimization tools for a large number of energy-saving design alternatives.Therefore,how to achieve multi-objective comprehensive optimization in the energy-efficient design of rural prefabricated houses has become an urgent problem to be solved.In order to improve the comprehensive energy,economic and environmental performance of rural prefabricated houses in energy-saving design,the author constructs a multi-objective optimization model for the energy-saving design of rural prefabricated houses.The model is designed to gradually achieve the integrated optimum of the three performance objectives by adjusting the values of the design parameters and searching for the optimal Pareto-minimized solution and the corresponding target values with the objective functions of energy consumption,cost and carbon emission.First,the author analyzed the energy-saving design strategies of rural houses,screened out 16 design parameters and determined the range of values,and established a library of energy-saving design optimization strategies covering1.89×10^{1 3} design cases;then,This paper determined the three performance objectives of energy consumption,cost and carbon emission,and selected CVBEC,LCC and LCCO₂ by analyzing the life cycle characteristics of rural prefabricated houses.By analyzing the characteristics of rural prefabricated houses at each stage of their life cycle,the author select the three measurement indexes of CVBEC,LCC and LCCO₂,and construct the objective function with them.On this basis,this paper compares the existing domestic and foreign energy-saving design optimization processes and designs algorithms,and formulates the optimization process of"data set generation-surrogate model construction-multi-objective optimization"to develop the tool.First,the BIM model of the initial design scheme is established,and the energy consumption modeling and parametric simulation are performed in Design Builder and JEPlus,and the performance target values of energy consumption,cost and carbon emission for different design schemes are calculated in the developed Excel program to establish the dataset;then,the design parameters are used as input variables,and CVBEC,LCC and LCCO₂ are used as output variables.Finally,a coupling strategy between ANN and NSGA-II algorithm is constructed,and the ANN model is called repeatedly to search for the Pareto optimal solution and the corresponding performance target values.In addition,this paper also develops a Revit plug-in for automatic generation of the bill of materials of prefabricated parts and a MATLAB program for multi-objective optimization solution of coupled ANN and NSGA-II algorithm based on visual programming and mathematical programming according to the tool requirements.The proposed method was applied in a case study of an assembled house project in rural Beijing to verify the validity and applicability of the established model and algorithm,and to obtain the optimal solution for energy-efficient design and the corresponding performance target performance.The main contributions obtained from this study include.（1）A multi-objective optimization model of energy consumption,cost and carbon emission for energy-efficient design of rural prefabricated houses was established.The model covers 16 energy-saving design parameters and a total of1.89×10^{1 3} energy-saving design solutions.（2）The constructed algorithm model avoids the problem of low computational efficiency caused by the direct coupling of simulation tools and optimization algorithms in the traditional optimization process by establishing an ANN model instead of simulation-based data set generation methods for finding optimization,and improves the optimization efficiency.The optimization process proposed in this paper realizes the data flow between multiple platform tools and reduces the difficulty of interdisciplinary energy-saving design implemented by engineering designers.（3）For the optimization results of the case study,firstly,the characteristics of the design parameters taken for the optimal design solution are derived and reasoned;secondly,it is found that the cost of using the assembled construction mode is about1125 RMB/m² higher than that of the traditional rural housing in Beijing;again,the expansion of the installation scale of the photovoltaic power generation system leads to the reduction of all three target values and the obtained optimal solution has a reduced fossil fuel use ratio.This paper proposes a multi-objective optimization model and method for the energy-efficient design of rural prefabricated houses,which provides a reference for the improvement of energy-efficient design optimization methods for different climate zones and building types in China.