Digital twin models for optimization and global projection of building-integrated solar chimney

Abstract

Current research on solar chimneys has focused on developing regression-based empirical models, which might not be correct enough compared to the soft computing tools i.e., techniques of artificial intelligence. Current research has also published the search algorithm-based single-objective optimization of solar chimneys, whereas the latest genetic algorithm-based multi-objective optimization can be more useful for decision-making purposes. Current research has also not focused on the macro or global impact of the usage of solar chimneys in context with the energy, economic, environmental, social, and political framework of the world. This research fills these gaps by the development of a digital twin model of the solar chimney using a multivariate regression model based on the least square method and an artificial intelligence (AI) method based on multilayer perceptron artificial neural network (MLP-ANN) and their comparison. A multiobjective optimization study along with the application of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is applied to optimize the geometric dimensions of the solar chimney considering four different climatic zones using an elitist non-dominated sorting genetic algorithm (NSGA-II) to maximize the number of air changes per hour, energy efficiency, and specific environmental influence. The results have shown that the statistical performance indicators like the coefficient of regression, etc., are higher for the MLP-ANN technique as compared to the multivariate regression method, thus, the AI technique is preferred. Comparison of optimization results with the base case condition has shown that the number of air changes can be improved between ∼71% and 87%. The global projection has demonstrated that the integration of solar chimneys in low-income countries with high air-conditioners installation rates must be necessary. It is also recommended to use solar chimneys in high-income countries for the renovation of the existing built environment to decrease the energy intensity of the building sector.