Cognitive Digital Twins for the Microgrid: A Real-World Study for Intelligent Energy Management and Optimization

Digital twin (DT) technology is a promising solution for achieving optimized microgrid control with enhanced efficiency, reliability, and sustainability. In this article, we focus on a real-world microgrid in Singapore and develop a cognitive DT. Our DT consists of a client, located near the physical microgrid for real-time control, and a cloud-based server for running computationally intensive algorithms for energy management and optimization. We design and implement communication architectures to ensure seamless and real-time communication. The functionality and performance of our DT are validated through different microgrid-operational scenarios. The results show that our DT outperforms comparison algorithms significantly and approximates the theoretical optimal with merely a 0.24% difference in operation cost. Overall, we demonstrate the effectiveness of our DT in enabling real-time optimization and management of microgrid operations, paving the way for technology adoption in smart grids to achieve improved grid resilience and efficiency.