乡村既有住宅低碳化改造多目标优化评价方法

A Multi-objective Optimisation Evaluation Method for the Low-carbon Renovation of Rural Houses

以乡村既有住宅环境影响、环境质量、改造成本效益多元性能优化为目标,构建基于Rhino-Grasshopper可视化编程平台的低碳化改造多目标优化评价方法及其数学模型,完整框架包括评价基准、评价方法和技术支撑三部分。该评价方法具有较强的可操作性,评价模型生成的改造措施最优解可为乡村既有住宅低碳化改造设计及管理提供科学量化的决策依据。

Existing rural houses are characteristic of high quantity,extensive floor occupation,serious energy waste and the urgent need for improving indoor quality.The willingness to pay for reconstruction is very low due to limitations in economics and environmental consciousness.A multi-objective optimisation evaluation method for low-carbon transformation of existing rural houses was proposed in this study to assess environmental influences,environmental quality,transformation cost-benefit efficiencies of rural houses to meet the 3,060 dual-carbon targets in the construction field.The research framework of the multi-objective optimisation evaluation method for the low-carbon renovation of existing rural houses is composed of evaluation criteria,evaluation method and technical support.’Evaluation criteria’refer to the construction and verification of the standard information model of existing rural houses.‘Evaluation method’is divided into three steps:variable sensitivity analysis,multi-objective optimisation and empowerment decision-making.The global sensitivity analysis of multiple groups of optimisation variables in three dimensions of rural planning,building ontology and technical equipment was carried out.Independent and collaborative contributions and influences of each variable to the optimisation goal were compared through the partial correlation coefficient(PCC)and standard rank regression coefficient(SRRC)method,enabling screening of high-sensitivity optimisation variables.On this basis,three sub-objective functions of life-cycle carbon emission,indoor thermal comfort in a year and increased global cost for reconstruction of existing rural houses were established by using the multi-objective optimisation algorithm as the basic mathematical model.Moreover,comprehensive optimisation was carried out.The Pareto optimal solution set was further screened by TOPSIS comprehensive evaluation method,and the final renovation scheme was gained through distance sequencing.’Technical support’is to realise the automatic optimisation and convenient interaction of the evaluation model based on the Rhino-Grasshopper visual programming platform.In this process,the EnergyPlus building thermal performance simulation tool was applied via Honeybee.The SPEA2 evolution algorithm of Octopus was used as the core of the multi-objective optimisation algorithm,and R and Python was applied in the compilation of sensitivity analysis of variables and empowerment decision operation module.Typical buildings of existing rural houses in Tianjin and Hebei Provinces were selected through hierarchical sampling.Based on the above multi-objective optimisation evaluation model for the low-carbon renovation of existing rural houses,variable sensitivity analysis,multi-objective performance optimisation and screening of the final renovation scheme for the chosen samples were conducted from the perspective of six reconstruction measures.These included standard thermal insulation material type of buildings,external insulation layer thickness,roof insulation layer thickness,type of external windows,indoor ceiling and height.Results demonstrated that after the renovation of the 140 mm wall+roof EPS insulation layer,double hollow windows with three pieces of glasses,and 3.1m high indoor ceiling,the life-cycle carbon emission,indoor thermal comfort and global cost of’coal-to-gas’rural houses were optimised by 92.87%,12.85%and 47.18%,respectively.After the renovation of the 140 mm wall,160 mm roof XPS insulation layer,double hollow windows with three pieces of glasses and 3.0 m high indoor ceiling,the life-cycle carbon emission,indoor thermal comfort and global cost of’coal-to-electricity’rural houses were optimised by 93.51%,14.55%and 71.36%,respectively.With the increasing proportion of green electricity in the power grid and the construction of distributed photovoltaic systems in rural houses under the 3,060 dual-carbon targets,the’coal-toelectricity’rural houses can continue to improve the life-cycle carbon emissions to realise zero carbon emission compared to the’coal-to-gas’rural houses.The multi-objective optimisation evaluation method for the low-carbon renovation of existing rural houses and the relevant evaluation model can assess the importance and global influences of the single low-carbon renovation measure for existing rural houses easily and accurately.Moreover,the optimal strategy combination could be chosen with consideration for environmental influences,environmental quality and renovation cost-efficiency multi-objective optimisation.This can improve the cost performance of renovation schemes and realise effective control and scientific management of scheme design and decision-making stages.