Modeling, Analysis and Control of Power System Distribution Networks
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F2: Distributed Energy System".
Deadline for manuscript submissions: closed (20 February 2023) | Viewed by 19740
Special Issue Editors
Interests: network science and its application in power systems
Special Issue Information
Dear Colleagues,
The application of existing technologies in the power system has broad prospects for development. In addition, there remains a strong need for technological innovations (such as electric vehicles) to meet the requirements of the ever-increasing new loads as well as the high demand for power quality and power supply reliability. In the future, distribution networks will use high-speed broadband for communication between substations, utilize intelligent electronic devices for adaptive control and protection, and apply energy management systems to monitor the operation condition. Intelligent systems are also involved in the mitigation of the potential power quality issues, which consequently improves power supply reliability. Therefore, the emerging technologies and their application in the distribution network should be further studied, for example, advanced distribution network automation, feeder voltage/reactive power control, advanced sensor technology, intelligent universal transformer, multifunction solid state switch technology, fault prediction and location technology, advanced metering infrastructure, local energy network controller, distributed power generation and energy storage equipment, and cybersecurity. With these advanced technologies and the integration of artificial intelligence and big data analysis techniques, the digitally transparent distribution network is expected to become a reality.
This Special Issue aims to inspire original research on the emerging technologies in related fields to promote the application of new techniques in distribution networks. Theoretical and/or empirical studies are welcome. Contributions in the form of regular research articles on deep learning-based power demand prediction, data-driven topology identification for distribution networks, line loss calculation and anomaly analysis, and cybersecurity are of interest.
Dr. Li Ding
Dr. Zhengmin Kong
Guest Editors
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Keywords
- distribution networks
- topology identification
- line loss
- security enhancement
- sensor technology
- artificial intelligence
- intelligence algorithm
- smart device
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