Urban energy sustainability and resiliency are paramount in addressing the challenges of modern urbanization. This paper introduces a novel framework that seamlessly integrates smart agriculture practices with an effective renewable resource allocation strategy to optimize energy utilization in urban and suburban areas. The optimization models employ a Multifactorial Evolutionary Algorithm, providing a dynamic and adaptive approach to fine-tune system parameters. The results, presented through numeric tables and colorful figures, showcase optimized agricultural production levels, renewable resource utilization, and the impact of specific factors and parameters on algorithmic performance. Notably, the study reveals the intricate balance achieved through the integration of smart agriculture and renewable energy, offering actionable insights for sustainable urban development. The visualizations not only enhance result comprehension but also serve as powerful tools for effective communication. This research contributes to the evolving discourse on urban energy sustainability, providing a systematic approach for future investigations at the intersection of agriculture, renewable energy, and optimization algorithms.