Low carbon and environmental preservation of residential buildings: MOESOM

Abstract

Introduction: The crucial transition toward carbon neutrality is developing and adopting low-carbon buildings and communities to achieve the recycling and reuse of resources and to minimize the damage to the natural environment by humans. Energy saving for residential buildings is essential for enhancing cost-effectiveness and redundant energy drain. Considering the increasing attention to energy conservation and the accessibility of sustainable energy sources, common energy-saving solutions expose inherent inadequacies limiting their effectiveness. The ineffectual use of traditional energy sources can result in waste, greater operating costs, and excessive energy consumption in residential structures.Methods: Hence, a Multi-Objective Energy-Saving Optimization Method (MOESOM) has been proposed to optimize energy use and conservation in residential buildings in southern Anhui, China. The proposed approach examines lower operational costs and carbon emissions by using green energy sources and encouraging effective energy consumption habits. The suggested Multi-Objective Energy-Saving Optimization Method technique offers insight into energy saving by utilizing green energy sources and confining energy uses. The multi-objective turns around energy saving and resource usage for decreasing operational costs and averting carbon emissions. Thus, the suggested technique is verified utilizing the Osprey Optimization Algorithm (OOA); the detailed goal is recognized utilizing the multiple objectives described. Based on the progress of low-carbon emissions and energy saving, the number of iterations for augmenting Osprey agents is identified. This agent-based optimization is executed if the novel augmented agent fulfills any of the trailing progression. The emission control level and energy-saving factor are assessed considering the variance between new and old agent progression. This encourages the various objectives to be fulfilled under similar criteria balancing their outcomes.Results and discussion: The output from different Osprey agents is induced for consecutive objectives and optimization factors. Then, the system ensures 8.97% energy savings and 8.04% high objectives compared to the other methods.