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

• Published in: Applied energy 2023-04, Vol.336, p.120806, Article 120806
• Main Authors: Bre, Facundo, Lamberts, Roberto, Flores-Larsen, Silvana, Koenders, Eduardus A.B.
• Format: Article
• Language: English
• Subjects: Climate-representative locations; Energy-efficient building; Latent energy storage; Multi-objective optimization; Multiple melting temperatures; Phase change material
• ISSN: 0306-2619
• DOI: 10.1016/j.apenergy.2023.120806

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). [Display omitted] •Using PCMs with different melting temperatures in buildings is proposed.•A multi-objective optimization method to design the PCMs’ properties is introduced.•Eight climate-representative locations in the WMO Region VI (Europe) are selected.•PCMs with different melting temperatures instead of a single one is preferred.•The best performance of PCMs is attained in climates where both loads are present.