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).
Highlights
Buildings are responsible for roughly 40% of European regulations (EU) energy consumption and 36% of its CO2 emissions [1]; it is the single largest energy consumer category in Europe
A solar Trombe wall that integrates a phase change material (PCM), which is the focus of the present study, is a passive design technique that may be considered as an efficiency measures (EEMs)
The reviews regarding the optimization of thermal building design have been discussed in previous papers, including: a review of computational optimization methods applied to renewable and sustainable energy [6,7]; a review of the optimization of passive solar design strategies concerning the more commonly used thermal building simulation tools, with optimal solutions to a multi-objective design [8]; a review of simulation-based optimization approaches and commonly used algorithms applied to building performance analysis [5,9]; a literature review of papers on improving the energy performance of residential buildings [10]; a review paper on simulation-based optimization in building envelope design based on the most widespread algorithms and well-known optimization software tools [11,12]; and a review dedicated to the energy performance optimization of existing buildings [13]
Summary
Buildings are responsible for roughly 40% of EU energy consumption and 36% of its CO2 emissions [1]; it is the single largest energy consumer category in Europe. A package of energy efficiency measures (EEMs), under the guidelines of European regulations (EU) [2,3], has established various building measures to mitigate consumption, including building envelope improvements, passive techniques, building system modifications as well as measures based on sustainable energy. Parametric studies can be conducted; with this method, varied inputs of each variable expose the impact on the objective functions, while all other variables are held constant This methodology is frequently time-consuming since it requires iterative repetition with other variables to achieve a dual purpose: observe the objective results; and recognize that its results will only be an incomplete improvement due to complex and nonlinear interactions of input variables on simulation results [4]. The reviews regarding the optimization of thermal building design have been discussed in previous papers, including: a review of computational optimization methods applied to renewable and sustainable energy [6,7]; a review of the optimization of passive solar design strategies concerning the more commonly used thermal building simulation tools, with optimal solutions to a multi-objective design [8]; a review of simulation-based optimization approaches and commonly used algorithms applied to building performance analysis [5,9]; a literature review of papers on improving the energy performance of residential buildings [10]; a review paper on simulation-based optimization in building envelope design based on the most widespread algorithms and well-known optimization software tools [11,12]; and a review dedicated to the energy performance optimization of existing buildings [13]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
