Integrated target-driven decision-making models for newly-constructed residential buildings
: typology based evaluation and optimisation from an engineering-environmental-economic perspective

  • Yuanli MA

Student thesis: PhD Thesis


The energy consumption and carbon emissions in the building sector contribute significantly to global climate change. These effects could be alleviated by proper designs, construction, and management, particularly in regard to regulated standards. To rapidly achieve the standards of “carbon peak” and “carbon neutral”, attaining ultra-low energy buildings as an efficient path was proposed for the specific targets in China. However, because of the complex climatic condition in the hot summer and cold winter zone, there is a lack of demonstration projects and related research. This condition hinders the development of comprehensive decision-making models in such area.
Given the importance of energy conservation amidst building sustainable development, this research provides a coordinated target-driven evaluating model for assessing the design schemes on a macro scale. The model proposes a comprehensive evaluation that assesses the building from engineering, energy, and economic perspectives. Also, this research proposes a methodological approach that enables decision-makers to select the optimal design schemes by defining the energy-saving targets. The model framework consists of three methodological models: building archetypal model, design scheme integration model, and multiple-perspective evaluation model.
The efficacy of the model was demonstrated through a case study analysis of newly constructed residential buildings in Ningbo city. Firstly, 469 residential buildings from 17 small residential districts (SRDs) in Yinzhou District were selected and classified using the number of floors, building shape coefficient and construction style, the average floor area, and the window-to-wall ratio of facades as the classification indexes. The obtained 9 representative geometric building archetypes by k-means clustering were simulated in IES-VE software using indoor data obtained from questionnaire surveys to generate corresponding building energy models for each archetype. Then, according to the design concept of ultra-low energy buildings (ULEBs), the applicable passive designs and active technologies for the hot summer and cold winter zone are screened, and the sensitivity analysis to examine the influence of each design or technology on building energy consumption is conducted by using multiple linear regression method. On this basis, the results identify a combination of nine applicable design measures (including both passive designs and active technologies) aiming at achieving ultra-low energy and nearly-zero energy targets based on the “Technical Standard for Nearly Zero Energy Building (GB/T 51350-2019)”.
Jointly, every 512 groups of possible combinatorial of the nine design measures were assessed for each building archetype based on energy and economic concerns. Then, the energy-target satisfied design schemes with the lowest life cycle cost (LCC) would be determined as the optimal ones and re-simulated to obtain a holistic evaluation of the buildings’ optimal performance. The results show that the cooling and dehumidification demand are the main factors limiting the design scheme compared with the heating demand and primary energy consumption. Based on the results of the LCC assessment, the payback period of transforming a conventional building into a ULEB or an NZEB of the same archetype is nearly 3 years. On the renewable energy concern, the roof-mounted solar PV system can satisfy at least 10% energy consumption coverage for NZEB of each building archetype with a maximum payback period of approximately 10 years.
Overall, the thesis developed a methodology for macro-scale residential building development by generating an archetype-based target-driven decision-making model from a comprehensive assessment. As a result, this research fills the blank that has challenged building stakeholders from making decisions on construction investments of new residential buildings that meet the requirements of national development. Furthermore, the designated model framework can serve as a guiding toolkit for the establishment of political momentum to drive green building development.
Date of AwardJul 2023
Original languageEnglish
Awarding Institution
  • University of Nottingham
SupervisorWu Deng (Supervisor), Jing Xie (Supervisor) & Timothy Heath (Supervisor)


  • Ultra-low energy building
  • Decision-making models
  • Hot summer and cold winter zone
  • Residential building

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