| Title |
Artificial Intelligence Framework for Smart City Microgrids: State of the art, Challenges, and Opportunities |
| ID_Doc |
37091 |
| Authors |
Khan, S; Paul, D; Momtahanyen, P; Aloqaily, M |
| Title |
Artificial Intelligence Framework for Smart City Microgrids: State of the art, Challenges, and Opportunities |
| Year |
2018 |
| Published |
|
| DOI |
|
| Abstract |
Smart city concepts have gained substantial attention over the last few years, as they apply advances in Information and Communication Technology (ICT) to enhance the quality and efficiency of services and resources. Microgrids are potentially powerful building blocks in the development of smart cities. Motivated by the opportunity, this article examines the factors leadings to the adoption of microgrids for mainstream electrical utilities grids, discusses the benefits that drive the growth, identifies the issues hindering benefit-capture of distributed energy generation inside microgrids, and provides a framework for the application of Artificial Intelligence (AI) to overcome challenges. We examine a simulation framework scenario and useful data sources that can help build AI capabilities within utilities. A brief description of the scalable BluWave-ai framework that leverages deep learning in the data centre is also provided, and AI inference at edge computing nodes and IoT sensors to optimize the benefits from microgrids at residential, neighbourhood, campus, enterprise and community levels is examined. |
| Author Keywords |
Microgrid; smart grid; smart city; net zero; solar and wind energy; artificial intelligence |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000444770700048 |
| WoS Category |
Computer Science, Theory & Methods; Engineering, Electrical & Electronic |
| Research Area |
Computer Science; Engineering |
| PDF |
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