As a major energy consumer and CO2 emitter, buildings have an undeniably important role to play in cutting carbon emissions and combating climate change. Over the recent decades, green buildings have gained increasing attention and popularity from various stakeholders in the construction industry. Green building design practice builds upon the conventional building design practice but adds the concerns of environmental impacts and occupants’ well-being in the design philosophy.
Many researchers advocate utilizing optimization for green building design due to its capability in obtaining improved design solutions and providing building designers a better understanding of the design space. A comprehensive and in-depth review on previous relevant optimization models has revealed the following two limitations which might undermine their application in practice. Firstly, the focus of optimization in most of these models was on the reduction of cost and energy consumption while occupants’ comfort level in terms of indoor environmental quality was seldom considered. Secondly, for those models which have set comfort level of indoor environmental quality as a design objective, only thermal comfort was taken into account and thus they failed to address other essential factors governing indoor environmental quality such as visual comfort and indoor air quality.
Aiming at addressing the limitations of previous related studies, this research has developed an improved optimization model for green building design with a more comprehensive set of design objectives, namely minimization of cost, minimization of energy consumption, and maximization of occupants’ comfort level in terms of indoor environmental quality. The importance of the three design objectives and the necessity for including them in the model were verified through a series of semi-structured interviews with respondents from different stakeholder groups in relation to green building design and construction. The three design objectives are evaluated in the developed model in terms of (i) cost according to life cycle cost; (ii) energy consumption analyzed by a widely-adopted building energy performance simulation program – EnergyPlus; and (iii) comfort level of indoor environmental quality by adopting an empirical-based multivariate-logistic regression model identified from literatures. Non-dominated Sorting Genetic Algorithm II, a powerful multi-objective optimization technique, was selected as the optimization engine in the developed model. The developed model was then implemented into to a prototype tool in the MATLAB environment which can be utilized by building designers to determine the appropriate design solutions. Through a hypothetical office building design problem, the applicability of the model was demonstrated. Finally, the developed model was validated through demonstration and face-to-face discussion with experts. / published_or_final_version / Civil Engineering / Master / Master of Philosophy
| Identifer | oai:union.ndltd.org:HKU/oai:hub.hku.hk:10722/181487 |
| Date | January 2012 |
| Creators | Wu, Hao, 吴昊 |
| Contributors | Ng, TST |
| Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
| Source Sets | Hong Kong University Theses |
| Language | English |
| Detected Language | English |
| Type | PG_Thesis |
| Source | http://hub.hku.hk/bib/B49618155 |
| Rights | The author retains all proprietary rights, (such as patent rights) and the right to use in future works., Creative Commons: Attribution 3.0 Hong Kong License |
| Relation | HKU Theses Online (HKUTO) |
Page generated in 0.0022 seconds