The goal of this research is to optimize renewable energy utilization in Swedish residential buildings using advanced optimization algorithms. By integrating mathematical modeling, machine learning, and big data processing, this study aims to enhance renewable energy consumption while ensuring economic benefits and user comfort. The project involves energy consumption analysis, renewable energy forecasting, and optimization-based decision-making to develop efficient energy management strategies. The expected outcome is a data-driven energy management framework that promotes sustainability, maximizes renewable energy utilization, and provides cost-effective solutions for residential users in Sweden.