Control and Fault Diagnosis of Multi-Energy Complementary Power Generation System
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F1: Electrical Power System".
Deadline for manuscript submissions: 20 January 2026 | Viewed by 160
Special Issue Editors
Interests: joint optimization of hydropower and new energy operation; equipment status prediction and fault diagnosis
Special Issues, Collections and Topics in MDPI journals
Interests: modeling, simulation, and optimization control of renewable energy power generation systems; status monitoring, fault diagnosis, and health management of hydroelectric new energy power generation equipment; big data, deep learning, and AI applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the increasing proportion of intermittent new energy sources, such as wind and solar power, connected to the power grid, the energy supply structure has undergone significant changes. The fault characteristics of multi-energy complementary power generation systems are becoming increasingly complex. Rapid and accurate fault identification and control are among the key challenges that urgently need to be addressed.
This Special Issue aims to present the most recent advances related to the theory and/or application of the various topics and technologies related to multi-energy complementary power generation systems. All submissions within the scope of the listed keywords are welcome.
Dr. Fengjiao Wu
Dr. Bin Wang
Guest Editors
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.
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Keywords
- water–wind–solar complementary power generation system
- renewable power systems
- optimization scheduling and operation of cascade hydropower stations
- condition monitoring
- vibration trend prediction
- fault diagnosis
- joint optimization
- control strategy
- full lifecycle assessment
- deep learning
- transfer learning
- AI applications
- big data
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