Evolutionary Multi-objective Optimization in Building Retrofit Planning Problem

• Published in: Procedia engineering Vol. 145; pp. 565 - 570
• Main Authors: Son, Hyojoo, Kim, Changwan
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 2016
• Subjects: 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
• DOI: 10.1016/j.proeng.2016.04.045

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.