Design Optimization of a Composite Solar Wall Integrating a PCM in a Individual House: Heating Demand and Thermal Comfort Considerations

Abstract

Thermal energy storage (TES), which features an innovative technology, can enhance energy efficiency in the building sector and reduce CO2 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−2.year−1) 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 ∘C to 35.9 ∘C, depending on weather) than it is when applying the optimization method to reduce the objective function by assigning heating demand (from 31.5 ∘C to 32.9 ∘C, again depending on weather).

Thermal Performance Assessment of Walls Made of Three Types of Sustainable Concrete Blocks by Means of FEM and Validated through an Extensive Measurement Campaign

“…This is accomplished by preserving and protecting the natural resources around the project site. Since it is not practical to experimentally measure the thermal properties of all the components and construction systems, it is advisable to use advanced and accurate methods to reliably predict their thermal performance [3]. From reducing carbon footprints by using renewable energy, using on-site water treatment plants to minimize waste, to recycling and building with renewable or waste materials, like bricks, there are still many ways in which sustainability of the building construction can be improved [4].…”

The Influence of Glazing on the Functioning of a Trombe Wall Containing a Phase Change Material

“…The introduction of phase change material into the masonry elements significantly reduced temperature fluctuations on the inner surface of the tested barrier. In articles [27,28], phase change material in the form of microcapsules was incorporated into the structure of the cement mortar layer. Additionally, behind the accumulation layer and the air gap layer, an insulating layer with ventilation openings was placed.…”

“…In the case of a phase change material, its parameters play an important role. The higher the latent heat of the PCM, the lower the demand for thermal energy and, at the same time, the better the thermal comfort in the room [28].…”

Design and Fabrication of Solar Thermal Energy Storage System Using Potash Alum as a PCM

“…Nems and Puertas [23] experimentally studied a dual PCM for heat storage, they made a I-D model for dual PCM and validated their results using experimental results. Leang et al [24] performed design and optimization of composite walls by integrating a PCM in their design. Their study concluded that the higher the latent heat, the lower the heating demand and greater the thermal comfort of the interior of the house.…”