Evolutionary Multi-objective Optimization in Building Retrofit Planning Problem

Energy efficiency has been a primary subject of concern in the building sector, which consumes the largest portion of the world's total energy. Especially for existing buildings, retrofitting has been regarded as the most feasible and cost-effective method to improve energy efficiency. When pla...

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Vydané v:Procedia engineering Ročník 145; s. 565 - 570
Hlavní autori: Son, Hyojoo, Kim, Changwan
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 2016
Predmet:
Building retrofit
CO2 emissions
Energy consumption
Evolutionary multi-objective optimization
Retrofit costs
Thermal comfort
Building retrofit
Energy consumption
Thermal comfort
CO2 emissions
Retrofit costs
Evolutionary multi-objective optimization
ISSN:1877-7058, 1877-7058
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Shrnutí:Energy efficiency has been a primary subject of concern in the building sector, which consumes the largest portion of the world's total energy. Especially for existing buildings, retrofitting has been regarded as the most feasible and cost-effective method to improve energy efficiency. When planning retrofit in public buildings, the most obvious objectives are to: (1) minimize energy consumption; (2) minimize CO2 emissions; (3) minimize retrofit costs; and (4) maximize thermal comfort; and one must consider these concerns together. The aim of this study is to apply evolutionary multi-objective optimization algorithm (NSGA-III) that can handle four objectives at a time to the application of building retrofit planning. A brief description of the algorithm is given, and the algorithm is examined using a building retrofit project, as a case study. The performance of the algorithm is evaluated using three measures: average distance to true Pareto-optimal front, hypervolume, and spacing. The results show that this study could be used to find a comprehensive set of trade-off scenarios for all possible retrofits, thereby providing references for building retrofit planners. These decision makers can then select the optimal retrofit strategy to satisfy stakeholders’ preferences.
ISSN:1877-7058
1877-7058
DOI:10.1016/j.proeng.2016.04.045