This review critically examines the integration of Artificial Intelligence (AI) and Deep Reinforcement Learning (DRL) into smart microgrid platforms, focusing on their role in optimizing sustainable e...
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State-of-the-art frameworks and tools are built into innovative grid technologies to model different structures and forms of microgrids and their dynamic behaviors. Smart grids'' dynamic models were
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The concept of microgrids (MGs) as compact power systems, incorporating distributed energy resources, generating units, storage systems, and loads, is widely acknowledged in the
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A primary limitation of DRL approaches in smart microgrids is their computational complexity and the extensive training times associated with developing effective control policies.
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The smart grid can be summarised as the combination of DERs integration and optimal control techniques. Microgrid deployment is the conceptual platform that makes the implementation of
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First Chapter provides a comprehensive overview of microgrid concepts, functional features, and benefits, followed by examples of applications around the world as well as possible future directions.
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This book provides a comprehensive survey on the available studies on control, management, and optimization strategies in AC and DC microgrids. It focuses on design of a laboratory-scale microgrid
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While DOE has made significant progress in supporting microgrid deployments, there remain research gaps for both remote microgrid, and microgrids for critical infrastructure, which are being addressed
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This report captures and shares experiences and lessons from the Miramar assessment, conceptual design, solicitation, engineering design, and construction process as well as from other
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Abstract Smart MicroGrids (SMGs) can be seen as a promising option when it comes to addressing the urgent need for sustainable transition in electric systems from the current fossil fuel-based
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