Building envelope design: Multi-objective optimization to minimize energy consumption, global cost and thermal discomfort. Application to different Italian climatic zones

被引:184
作者
Ascione, Fabrizio [1 ]
Bianco, Nicola [1 ]
Mauro, Gerardo Maria [2 ]
Napolitano, Davide Ferdinando [3 ]
机构
[1] Univ Napoli Federico II, DII Dept Ind Engn, Piazzale Tecchio 80, I-80125 Naples, Italy
[2] Univ Sannio, DING Dept Engn, Piazza Roma 21, I-82100 Benevento, Italy
[3] Univ Bergamo, Via Salvecchio 19, I-24129 Bergamo, Italy
关键词
Building envelope; Building energy optimization; Multi-objective genetic algorithm; Cost-optimal analysis; Nearly zero energy buildings; Thermal comfort; PERFORMANCE; RETROFIT; EFFICIENCY; COMFORT; IMPACT; MODEL; BIM; METHODOLOGY; RENOVATION; OPTIMALITY;
D O I
10.1016/j.energy.2019.02.182
中图分类号
O414.1 [热力学];
学科分类号
摘要
The paper proposes a multi-objective optimization approach to address the energy design of the building envelope. A genetic algorithm (GA) is implemented by means of the coupling between MATLAB (R) and EnergyPlus to minimize primary energy consumption (PEC), energy-related global cost (GC) and discomfort hours (DH). The design variables concern the set point temperatures, the radiative properties of plasters, the thermo-physical properties of envelope components, the window type, the building orientation. The GA performs a Pareto optimization and finally two optimal solutions are recommended: the nZEB (nearly zero energy building) optimal solution, which minimizes PEC, and the cost-optimal solution, which minimizes GC. These solutions provide the optimal design strategies for the public and private stakeholders, respectively, which represent the main actors involved in building design. The approach is applied for the design of a new typical Italian residential building. Four locations are considered to investigate the typical Italian climates. The outcomes can give precious indications to rebuild the Italian residential stock with a view to energy-efficiency and cost-optimality, given that the optimal solutions provide low values of PEC - between 62.0 and 91.9 kWh(p)/m(2)a - and of GC - between 456 and 665 (sic)/m(2) - depending on the location. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页码:359 / 374
页数:16
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