This project develops a distributed digital twin framework for smart grid data monitoring and analytics. The research focuses on simulating and emulating smart grid environments to enable real-time monitoring, intelligent data processing, and predictive analytics. By integrating distributed computing, digital twin technology, and adaptive resource management, the framework aims to improve the scalability, reliability, and efficiency of smart grid operations while supporting data-driven decision-making and proactive system maintenance.