Design Optimization of a Composite Solar Wall Integrating a PCM in a Individual House: Heating Demand and Thermal Comfort Considerations
Thermal energy storage (TES), which features an innovative technology, can enhance energy efficiency in the building sector and reduce CO<sub>2</sub> emissions. Due to their high heat storage capacity, phase change materials (PCMs) have impressed many researchers. This paper investigates...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-10-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/21/5640 |
| _version_ | 1797549550186004480 |
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| author | Enghok Leang Pierre Tittelein Laurent Zalewski Stéphane Lassue |
| author_facet | Enghok Leang Pierre Tittelein Laurent Zalewski Stéphane Lassue |
| author_sort | Enghok Leang |
| collection | DOAJ |
| description | Thermal energy storage (TES), which features an innovative technology, can enhance energy efficiency in the building sector and reduce CO<sub>2</sub> emissions. Due to their high heat storage capacity, phase change materials (PCMs) have impressed many researchers. This paper investigates the energy performance of an individual house integrating a solar Trombe wall containing PCM with respect to heating demand and thermal comfort applications. The thermal energy performance of the design house was simulated using Dymola/Modelica, the thermal building simulation tool, whereby the optimization of objective functions as regards heating demand and thermal comfort was executed using GenOpt, the generic optimization software. Optimization of the solar Trombe wall focuses on the feasibility to find the optimal PCM parameters when running GenOpt, which consist of latent heat, melting temperature, PCM thickness and thermal conductivity, in order to minimize both the annual energy consumption for heating and the number of hours of thermal discomfort. The parametric study was first conducted for each PCM parameter so as to not only observe its effect on the identified energy performance, but also ensure the absence of errors in simulation runs before performing the optimization. The ‘Coordinate Search’ Generalized Pattern Search (GPS) algorithm was applied to minimize the objective function, whereas the ‘Weighted Sum Approach’ was used to solve the multi-objective function problem. Results showed that the higher the latent heat, the lower the heating demand and the greater the thermal comfort. The results of these parametric studies show that for the effect of the parameter on heating, demand is quite limited (1–2 kWh·m<inline-formula><math display="inline"><semantics><msup><mrow></mrow><mrow><mo>−</mo><mn>2</mn></mrow></msup></semantics></math></inline-formula>·year<inline-formula><math display="inline"><semantics><msup><mrow></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></semantics></math></inline-formula>) whereas the effect on thermal comfort is more significant. The optimal PCM melting temperature is higher for warmer climates; it is also higher for the studied case applying the optimization method to minimize the objective function by assigning the number of hours of thermal discomfort (from 32.8 <inline-formula><math display="inline"><semantics><mrow><msup><mrow></mrow><mo>∘</mo></msup><mi mathvariant="normal">C</mi></mrow></semantics></math></inline-formula> to 35.9 <inline-formula><math display="inline"><semantics><mrow><msup><mrow></mrow><mo>∘</mo></msup><mi mathvariant="normal">C</mi></mrow></semantics></math></inline-formula>, depending on weather) than it is when applying the optimization method to reduce the objective function by assigning heating demand (from 31.5 <inline-formula><math display="inline"><semantics><mrow><msup><mrow></mrow><mo>∘</mo></msup><mi mathvariant="normal">C</mi></mrow></semantics></math></inline-formula> to 32.9 <inline-formula><math display="inline"><semantics><mrow><msup><mrow></mrow><mo>∘</mo></msup><mi mathvariant="normal">C</mi></mrow></semantics></math></inline-formula>, again depending on weather). |
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| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T15:17:13Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-cbbfa0c4342940ce9b40af7784684fe52023-11-20T18:52:50ZengMDPI AGEnergies1996-10732020-10-011321564010.3390/en13215640Design Optimization of a Composite Solar Wall Integrating a PCM in a Individual House: Heating Demand and Thermal Comfort ConsiderationsEnghok Leang0Pierre Tittelein1Laurent Zalewski2Stéphane Lassue3Laboratoire de Génie Civil et géo-Environnement (LGCgE), Université d’Artois, ULR 4515, F-62400 Béthune, FranceLaboratoire de Génie Civil et géo-Environnement (LGCgE), Université d’Artois, ULR 4515, F-62400 Béthune, FranceLaboratoire de Génie Civil et géo-Environnement (LGCgE), Université d’Artois, ULR 4515, F-62400 Béthune, FranceLaboratoire de Génie Civil et géo-Environnement (LGCgE), Université d’Artois, ULR 4515, F-62400 Béthune, FranceThermal energy storage (TES), which features an innovative technology, can enhance energy efficiency in the building sector and reduce CO<sub>2</sub> emissions. Due to their high heat storage capacity, phase change materials (PCMs) have impressed many researchers. This paper investigates the energy performance of an individual house integrating a solar Trombe wall containing PCM with respect to heating demand and thermal comfort applications. The thermal energy performance of the design house was simulated using Dymola/Modelica, the thermal building simulation tool, whereby the optimization of objective functions as regards heating demand and thermal comfort was executed using GenOpt, the generic optimization software. Optimization of the solar Trombe wall focuses on the feasibility to find the optimal PCM parameters when running GenOpt, which consist of latent heat, melting temperature, PCM thickness and thermal conductivity, in order to minimize both the annual energy consumption for heating and the number of hours of thermal discomfort. The parametric study was first conducted for each PCM parameter so as to not only observe its effect on the identified energy performance, but also ensure the absence of errors in simulation runs before performing the optimization. The ‘Coordinate Search’ Generalized Pattern Search (GPS) algorithm was applied to minimize the objective function, whereas the ‘Weighted Sum Approach’ was used to solve the multi-objective function problem. Results showed that the higher the latent heat, the lower the heating demand and the greater the thermal comfort. The results of these parametric studies show that for the effect of the parameter on heating, demand is quite limited (1–2 kWh·m<inline-formula><math display="inline"><semantics><msup><mrow></mrow><mrow><mo>−</mo><mn>2</mn></mrow></msup></semantics></math></inline-formula>·year<inline-formula><math display="inline"><semantics><msup><mrow></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></semantics></math></inline-formula>) whereas the effect on thermal comfort is more significant. The optimal PCM melting temperature is higher for warmer climates; it is also higher for the studied case applying the optimization method to minimize the objective function by assigning the number of hours of thermal discomfort (from 32.8 <inline-formula><math display="inline"><semantics><mrow><msup><mrow></mrow><mo>∘</mo></msup><mi mathvariant="normal">C</mi></mrow></semantics></math></inline-formula> to 35.9 <inline-formula><math display="inline"><semantics><mrow><msup><mrow></mrow><mo>∘</mo></msup><mi mathvariant="normal">C</mi></mrow></semantics></math></inline-formula>, depending on weather) than it is when applying the optimization method to reduce the objective function by assigning heating demand (from 31.5 <inline-formula><math display="inline"><semantics><mrow><msup><mrow></mrow><mo>∘</mo></msup><mi mathvariant="normal">C</mi></mrow></semantics></math></inline-formula> to 32.9 <inline-formula><math display="inline"><semantics><mrow><msup><mrow></mrow><mo>∘</mo></msup><mi mathvariant="normal">C</mi></mrow></semantics></math></inline-formula>, again depending on weather).https://www.mdpi.com/1996-1073/13/21/5640individual housesolar composite Trombe wallphase change materialDymola/ModelicaGenOpt |
| spellingShingle | Enghok Leang Pierre Tittelein Laurent Zalewski Stéphane Lassue Design Optimization of a Composite Solar Wall Integrating a PCM in a Individual House: Heating Demand and Thermal Comfort Considerations Energies individual house solar composite Trombe wall phase change material Dymola/Modelica GenOpt |
| title | Design Optimization of a Composite Solar Wall Integrating a PCM in a Individual House: Heating Demand and Thermal Comfort Considerations |
| title_full | Design Optimization of a Composite Solar Wall Integrating a PCM in a Individual House: Heating Demand and Thermal Comfort Considerations |
| title_fullStr | Design Optimization of a Composite Solar Wall Integrating a PCM in a Individual House: Heating Demand and Thermal Comfort Considerations |
| title_full_unstemmed | Design Optimization of a Composite Solar Wall Integrating a PCM in a Individual House: Heating Demand and Thermal Comfort Considerations |
| title_short | Design Optimization of a Composite Solar Wall Integrating a PCM in a Individual House: Heating Demand and Thermal Comfort Considerations |
| title_sort | design optimization of a composite solar wall integrating a pcm in a individual house heating demand and thermal comfort considerations |
| topic | individual house solar composite Trombe wall phase change material Dymola/Modelica GenOpt |
| url | https://www.mdpi.com/1996-1073/13/21/5640 |
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