Elsevier Digital Twin Technology and Smart Grid (Advances in Digital Twin Computing and Sensor Networks)

Digital Twin Technology and Smart Grid explores the intersection of these technologies, which are essential for the evolution of energy systems. The book explains how it utilizes intelligent wireless sensor networks, the Internet of Things, artificial intelligence, machine learning, cloud, edge, and fog-computing to monitor power consumption. It discusses how security risks and privacy challenges can be accommodated, and explains the ethical/legal implications of collecting data. As the global energy landscape moves toward greater sustainability and decentralization, digital twins present unprecedented opportunities to enhance grid efficiency, bolster resilience, and support the integration of renewable energy sources. The integration of Digital Twin (DT) technology with Smart Grids (SG) represents a groundbreaking development in energy management, making this a highly significant and timely topic. As urban areas expand and energy demands rise, the need for more efficient, sustainable, and resilient energy systems becomes critical. DT technology, with its ability to create real-time, virtual replicas of physical systems, offers unprecedented opportunities for enhancing the performance, reliability, and security of smart grids. Explains how digital twins gather real-world data to create a model of a given situation of real micro grid/power grids Discusses how the model can be utilized in making informed decisions Considers the associated technologies that support digital twins: IoT, AI, ML, and blockchain Explores how digital twins can be used in the real-world to monitor and improve services of the micro grid/power grid