Affiliation:
1. Department of Electrical and Computer Engineering, Montana State University, Bozeman, MT 59717, USA
Abstract
Advances in machine learning and artificial intelligence (AI) techniques bring new opportunities to numerous intractable tasks for operation and control in modern electric distribution systems. Nevertheless, AI applications for such grids as cyber-physical systems encounter multifaceted challenges, e.g., high requirements for the quality and quantity of training data, data efficiency, physical inconsistency, interpretability, and privacy concerns. This paper provides a systematic overview of the state-of-the-art AI methodologies in the post-pandemic era, represented by transfer learning, deep attention mechanism, graph learning, and their combination with reinforcement learning and physics-guided neural networks. Dedicated research efforts on harnessing such recent advances, including power flow, state estimation, voltage control, topology identification, and line parameter calibration, are categorized and investigated in detail. Revolving around the characteristics of distribution system operation and integration of distributed energy resources, this paper also illuminates prospects and challenges typified by the privacy, explainability, and interpretability of such AI applications in smart grids. Finally, this paper attempts to shed light on the deeper and broader prospects in the realm of smart distribution grids by interoperating them with smart building and transportation electrification
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Reference97 articles.
1. (2023, April 09). Cyber-Physical Systems (CPS), Available online: https://beta.nsf.gov/funding/opportunities/cyber-physical-systems-cps.
2. Rajkumar, R., Lee, I., Sha, L., and Stankovic, J. (2010, January 13–18). Cyber-physical systems: The next computing revolution. Proceedings of the 47th Design Automation Conference, Anaheim, CA, USA.
3. Zhao, H., Liu, H., Gu, Y., Han, L., Zhao, W., and Du, Y. (2021, January 23–25). Overview of Architecture and Planning of Cyber Physical Distribution System. Proceedings of the 2021 IEEE Sustainable Power and Energy Conference (iSPEC), Nanjing, China.
4. Smart Transmission Grid Applications and Their Supporting Infrastructure;Bose;IEEE Trans. Smart Grid,2010
5. Artificial Intelligence Based Distribution System Management and Control;Nirmal;J. Electron.,2020
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献