Multi-objective optimization of latent energy storage in buildings by using phase change materials with different melting temperatures

被引:13
|
作者
Bre, Facundo [1 ,2 ]
Lamberts, Roberto [3 ]
Flores-Larsen, Silvana [4 ,5 ]
Koenders, Eduardus A. B. [1 ]
机构
[1] Tech Univ Darmstadt, Inst Werkstoffe Bauwesen, D-64287 Darmstadt, Germany
[2] Consejo Nacl Invest Cient & Tecn, Ctr Invest Metodos Computac CIMEC, UNL, Predio Dr Alberto Cassano, Colectora Ruta Nacl 168, RA-3000 Paraje El Pozo, Santa Fe, Argentina
[3] Fed Univ Santa Catarina UFSC, Dept Civil Engn, Lab Energy Efficiency Bldg LabEEE, Florianopolis, Brazil
[4] Consejo Nacl Invest Cient & Tecn, INENCO Inst Invest Energia Convenc, Av Bolivia 5150, Salta, Argentina
[5] Univ Nacl Salta, Av Bolivia 5150, Salta, Argentina
关键词
Energy-efficient building; Latent energy storage; Phase change material; Multiple melting temperatures; Multi-objective optimization; Climate-representative locations; PERFORMANCE; PCM; EFFICIENCY; IMPROVE;
D O I
10.1016/j.apenergy.2023.120806
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Technologies based on phase change materials (PCMs) are promising solutions to reduce energy consumption in buildings and related greenhouse gas emissions. However, the performance of passive PCMs in buildings is highly dependent on the melting temperatures employed, as well as the climate where the building is located. Therefore, the present contribution describes an optimization-based method to design passive latent energy storage in buildings by using PCMs with different melting temperatures. To achieve this goal, a multi -objective genetic algorithm is coupled with the building energy models developed in EnergyPlus to find the best trade-off between annual heating and cooling loads. A small office is chosen as a case study to evaluate the energy performance of the buildings incorporating the proposed PCM approach. Three different PCM layers are added to the ceilings and the external and internal walls of the building, and their parametric models are developed in EnergyPlus to optimize the melting temperature and thickness of each PCM layer simultaneously. Moreover, a method to select climate-representative locations according to the ASHRAE 169-2020 climate classification and within the WMO Region VI (Europe) is proposed and applied, resulting in eight well-representative locations. An optimization-based design is carried out for each selected location and the performances of the optimized building designs are systematically compared to the ones of the baseline models. The optimization results achieved show that regardless of the climate zone analyzed, using several PCMs with different melting temperatures instead of a single one, is preferred. Moreover, the best performance of PCMs is attained in climate zones where both the heating and cooling loads are present. Thus, the highest saving regarding the annual total loads of 11.7% is achieved in zone 5A (Cold), while the lowest one of 2.3% is obtained in zone 1B (Very hot).
引用
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页数:18
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