Recent advancements in smart technologies tender the use of artificial technologies in the energy... more Recent advancements in smart technologies tender the use of artificial technologies in the energy systems more practical. The focus of this paper is on designing an innovative smart energy system with the aid of cloud computing. It aims to address certain primary issues in energy demand forecasting, load balancing, and automation in decentralized control management systems. A proposed system which utilizes hybrid architecture based on integrated predictive analytics and control distributed automation and decision systems, across multiple diverse energy resources, demonstrates transformative control automation and predictive control capabilities, using edge artificial intelligence, such energy clouds, and federated control. The artificial intelligence system provides edge control within federated control architecture on the energy cloud, the system analytics predictive control and control functions which offer automated decision-making. The decisions made in the automation of several energy assets boost the system predictive control capabilities. The enhanced predictive control capabilities offer reduction in operational energy systems, operational cost and carbon, and overall system carbon footprint the operational energy system efficiency. The cloud artificial intelligence systems bring transformative changes to the operational energy system efficiency, operational cost, and overall system carbon footprint. It paves the way toward a new, self-governing paradigm for smart and autonomous ecosystems sustainable energy systems.
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Papers by Arman Hossain