The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Artificial Intelligence Techniques in Smart Grid and Renewable Energy Systems—Some Example Applications
Abstract
Artificial intelligence (AI) techniques, such as expert systems (ESs), fuzzy logic (FL), and artificial neural networks (ANNs or NNWs) have brought an advancing frontier in power electronics and power engineering. These techniques provide powerful tools for design, simulation, control, estimation, fault diagnostics, and fault-tolerant control in modern smart grid (SG) and renewable energy systems (RESs). The AI technology has gone through fast evolution during last several decades, and their applications have increased rapidly in modern industrial systems. This special issue will remain incomplete without some discussion on AI applications in SG and RESs. The paper will discuss some novel application examples of AI in these areas. These applications are automated design of modern wind generation system and its health monitoring in the operating condition, fault pattern identification of an SG subsystem, and control of SG based on real-time simulator. The concepts of these application examples can be expanded to formulate many other applications. In the beginning of the paper, the basic features of AI that are relevant to these applications have been briefly reviewed.
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Citations
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Power Electronics, Smart Grid, and Renewable Energy Systems
Bose, B. K. (2017) · Proceedings of the IEEE · doi:10.1109/jproc.2017.2745621 · Cited by 242
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Cited by
Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities
Ahmad, T., Zhang, D., Huang, C., Zhang, H., Dai, N., Song, Y., & Chen, H. (2021) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2021.125834 · Cited by 1,258
An Overview of Artificial Intelligence Applications for Power Electronics
Zhao, S., Blaabjerg, F., & Wang, H. (2021) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2020.3024914 · Cited by 947
Yigitcanlar, T., Desouza, K., Butler, L., & Roozkhosh, F. (2020) · Energies · doi:10.3390/en13061473 · Cited by 555
Hannan, M. A., Ker, P. J., Lipu, M. S. H., Choi, Z. H., Rahman, M. S. A., Muttaqi, K. M., & Blaabjerg, F. (2020) · IEEE Access · doi:10.1109/access.2020.2967345 · Cited by 339
Shi, Z., Yao, W., Li, Z., Zeng, L., Zhao, Y., Zhang, R., Tang, Y., & Wen, J. (2020) · Applied Energy · doi:10.1016/j.apenergy.2020.115733 · Cited by 327
Metadata
- Authors
- Bose, B. K.
- Venue
- Proceedings of the IEEE
- Published
- 2017-11
- Volume
- 105
- Issue
- 11
- Pages
- 2262-2273
- ISSN
- 0018-9219 (ISSN-L)
- 1558-2256
- OpenAlex
- W2767172243
- Cited by
- 296
- References
- 1
- FWCI
- 5.93
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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