Deep Learning Applications in Optimization and Control of Power Transmission and Distribution
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".
Deadline for manuscript submissions: 15 October 2024 | Viewed by 112
Special Issue Editors
Interests: optimization, control and machine learning applied to complex networked systems; reliability, resilience and real-time control of energy systems
Interests: statistical electrical load modeling and control of distributed energy resources in power systems
Interests: power system; renewable integration; AI and machine learning; simulation; stability and control
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the growth in the amounts of data collected in power systems due to the introduction of higher-resolution sensors at various levels of the system and the push toward automation and intelligent data-driven decision making, deep learning-based AI methods have received significant interest in recent years. The ability of deep learning to consume large quantities of high-resolution data and develop high-fidelity accurate models can be used to make fast and efficient decisions applicable to all levels of power systems, from forecasting to planning to real-time decision making. However, several challenges remain, especially in relation to providing guarantees for the safe and reliable operation of the power system, as well as developing modeling that are explainable to network operators. Furthermore, different challenges in adopting deep learning exist at the transmission and distribution levels.
This Special Issue aims to develop explainable deep learning models for the safe operation of power systems at the transmission and distribution levels.
Dr. Nawaf Nazir
Dr. Adil Khurram
Dr. Qiuhua Huang
Guest Editors
Manuscript Submission Information
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Keywords
- deep learning
- power transmission
- power distribution
- optimization and control of power systems
