| 摘要: |
| 双碳目标的大背景下，严寒地区因特殊
的气候条件，碳排放问题较为突出，且寒地近
零能耗建筑热工性能优化空间有限。为研究严
寒地区近零能耗建筑进一步降低碳排放的可
能，以及建筑参数与碳排放等性能之间的关系，
以中德节能中心为例，依托Rhino+Grasshopper
平台，整体考虑建筑的产能端和用能端，按建筑
参数层级不同，基于RBFOpt算法分形态、立面
两个阶段进行多目标优化，并利用Simlab对建
筑参数进行全局敏感性分析。结果表明：在近
零能耗建筑围护结构热工性能已达限值的前提
下，经过多目标优化，最优方案单位面积碳排放
下降了4.75%，产能消费比提高了8.2%。证明多
阶段多目标优化方法对于提升严寒地区近零能
耗建筑性能、降低碳排放是有效的。另外，对于建筑碳排放敏感程度较高的两个参数是面宽进深
比和天窗面积比。产能消费端协同的多阶段多目标优化方法可以为严寒地区近零能耗建筑设计与
优化提供一定的借鉴参考。 |
| 关键词: 多目标优化 近零能耗建筑 严寒地区 建筑形态 RBFOpt算法 碳中和 |
| DOI：10.13791/j.cnki.hsfwest.20240113 |
| 分类号: |
| 基金项目:国家自然科学基金面上项目（52378027） |
|
| Multi-objective optimization of nearly zero energy building shape in cold regions withcarbon neutrality orientation |
|
SUN Jiayi,LI Sui,DONG Yixin
|
| Abstract: |
| In the context of dual-carbon target, the requirements of building performance are further
improved. Whether the society can further improve building performance and reduce carbon
emissions on the basis of nearly zero-energy building standards has become an urgent problem to be
solved in the construction industry.
China has a vast territory and a rich terrain form, which leads to the large differences in
regional climate characteristics in different regions. Under the influence of regional climate, there
are obvious differences in building carbon emission characteristics and low carbon energy saving
potential and paths in different regions. Among them, due to the special climate conditions, affected
by winter heating problems and other factors, the carbon emission problem is more prominent, which
is worth paying attention. With the steady progress of the direction of low-carbon energy saving
in the construction field and the continuous update of technology, the thermal performance of the
envelope of nearly zero energy consumption buildings in cold areas has basically approached or
reached the limit. The potential of energy saving and carbon reduction to further improve the thermal
performance of the envelope is limited, and it is easy to cause the waste of resources. Therefore, it is
an effective means to optimize the form and facade parameters of building energy to supply building
energy, which is to reduce the carbon emission of buildings with nearly zero energy consumption in
cold areas.
Multi-objective optimization methods based on simulation are relatively mature in the
construction field. However, in the current research content, more building energy and renewable
energy technology capacity as two independent parts, but there is no overall consideration between
the two, resulting in the difficulty of achieving the expected low-carbon energy saving effect in
practical application. In the current research, when the building parameters are optimized, the
hierarchical scale of the building parameters is not often considered enough, and the building
parameters of different levels are often optimized in coordination. However, in the early stage
of the scheme design, the coordinated optimization of different levels of parameters will limit
the architect’s thinking on the facade composition and body design to a certain extent, restrict
the architect’s thinking, and is not conducive to the comparative analysis and discussion of the
parameters in the later stage.
In order to study the possibility of further reducing carbon emission in near-zero energy
consumption buildings in cold areas, and the relationship between the parameters of all building
levels and carbon emission, comfort and other performance. This paper takes the Sino-German
Energy Conservation Demonstration Center of Shenyang Jianzhu University as an example, relying
on the Rhino + Grasshopper parametric platform, considers the renewable energy production
end and energy use end of the building as a whole, divides the parameters into morphological parameters and facade parameters according to the different levels of building parameters, and constructs the corresponding target function according to
the characteristics of the near zero energy consumption building. Based on the RBFOpt algorithm, the multi-objective optimization experiment is carried
out in two stages. After obtaining the Pareto frontier solution set, the objective function is given weight and weighted processing, and the optimal scheme
under the current weight allocation is made comprehensively. Finally, Simlab was used for the global sensitivity analysis of the building parameters, ranking
the parameters according to their sensitivity. The results show that: on the premise that the thermal performance of the near-zero energy consumption
building envelope has reached the limit, after the multi-stage multi-target optimization experiment and TOPSIS comprehensive evaluation method, the
carbon emission per unit area of the optimal scheme is 18.779 kgCO2/m2
, 4.75% lower than the current situation, and the production capacity consumption
ratio is 1.042, up 8.2% compared with the current situation. It proves that the multi-stage and multi-target optimization method is effective for improving
the performance of near-zero energy consumption buildings in cold areas and reducing carbon emissions. The multi-stage and multi-objective optimization
method has less calculation cost and higher accuracy of the results, which is more in line with the generation logic of the building scheme. In addition, the
recommended values and intervals of each building parameter variable are given according to the experimental results. In addition, the sensitivity of building
parameter variables at different levels to building performance targets such as carbon emission is explored. For building carbon emission, the two parameters
with higher sensitivity are the surface width and depth ratio and skylight area ratio. For the capacity consumption ratio, the most sensitive parameter is the
building orientation and skylight area ratio. For indoor comfort, the most sensitive parameter is the south and west window-wall ratio.
The multi-stage multi-objective optimization method and technical path of production capacity consumption end collaboration proposed in this paper
can be used as the method blueprint, providing some reference for the design and optimization of various types of nearly zero energy consumption buildings
in cold areas and other climate areas. |
| Key words: multi-objective optimization nearly zero energy building severe cold regions building shape RBFOpt algorithm carbon neutral |
