A bi-objective optimization approach for selection of passive energy alternatives in retrofit projects under cost uncertainty

被引:0
|
作者
Amiri Fard F. [1 ]
Nasiri F. [1 ]
机构
[1] Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, QC, Canada
来源
Energy and Built Environment | 2020年 / 1卷 / 01期
关键词
Building retrofit; Construction technologies; Cost uncertainty; Fuzzy set theory; Multi-Objective Optimization; Passive energy measures;
D O I
10.1016/j.enbenv.2019.11.005
中图分类号
学科分类号
摘要
Improving energy performance of buildings is of particular importance in new construction and existing buildings. Building refurbishment is considered a practical pathway towards energy efficiency as the replacement of older buildings is at a slow pace. There are various ways of incorporating energy conservation measures in buildings through refurbishment projects. As such, we have to choose among various passive or active measures. In this study, we develop an integrated assessment model to direct energy management decisions in retrofit projects. Our focus will be on alternative passive measures that can be included in refurbishment projects to reduce overall energy consumption in buildings. We identify the relative priority of these alternatives with respect to their non-monetary (qualitative) benefits and issues using an analytic network process. Then, the above priorities will form a utility function that will be optimized along with the energy demand and retrofit costs using a multi-objective optimization model. We also explore various approaches to formulate the uncertainties that may arise in cost estimations and incorporate them into the optimization model. The applicability and authenticity of the proposed model is demonstrated through an illustrative case study application. The results reveal that the choice of the optimization approach for a retrofit project shall be done with respect to the extent of variations (uncertainties) in expected utilities (benefits) and costs for the alternative passive technologies. © 2019 Southwest Jiaotong University
引用
收藏
页码:77 / 86
页数:9
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