Condition Monitoring and Diagnostic Methods for Power Equipment in New Energy Power Systems

Topic Information

Dear Colleagues,

With the continuous development of new energy power systems, the power system has gradually become a complex system that contains tens of thousands of primary and secondary power equipment. In order to ensure the safe and stable operation of the system, condition monitoring, assessment, detection and diagnosis of various equipment are particularly important. In contrast to the traditional power system, power systems that use new energy include the uncertain characteristics of new energy, which makes the operating conditions of power equipment more complex and changeable, and brings great challenges to its safe and stable operation.

In addition, with the access of distributed power generation and the increase in the number of electric vehicles, the load characteristics of power equipment become more and more variable, and the harmonic, random fluctuation and impulsive characteristics become more evident. All these aspects have a certain impact on the safe and stable operation of power equipment. In order to ensure the high and reliable operation of the new energy power system, it is necessary to focus on the monitoring, diagnosis, detection and evaluation of the power equipment, especially large-scale primary equipment, such as cables, insulators and transformers, to ensure the safety and reliability of the entire system.

This Topic aims to integrate and present the most recent advances that address the challenges in the fields of condition monitoring, assessment, fault diagnosis, defect inspection and life management of critical power equipment, such as cables, insulators, transformers, etc. Topics of interest for the publication include, but are not limited to, the following:

• Advanced condition monitoring of insulators/cable systems
• Visualization analysis and condition assessment of insulators/cable systems
• Life cycle assessment and remaining useful life estimation for power equipment
• Data/model-driven-based approaches for fault diagnosis of electrical equipment
• Non-intrusive inspection or non-destructive detection methods for high-voltage assets
• Fault mechanism modelling and analysis of power equipment
• Health assessment and management approaches for power equipment
• Reliability calculation and assessment of power equipment

Dr. Shuaibing Li
Prof. Dr. Guoqiang Gao
Dr. Guochang Li
Dr. Yi Cui
Dr. Jiefeng Liu
Dr. Guangya Zhu
Dr. Jin Li
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Coatings coatings	2.9	5.0	2011	13.7 Days	CHF 2600	Submit
Electronics electronics	2.6	5.3	2012	16.8 Days	CHF 2400	Submit
Energies energies	3.0	6.2	2008	17.5 Days	CHF 2600	Submit
Sensors sensors	3.4	7.3	2001	16.8 Days	CHF 2600	Submit
Telecom telecom	2.1	4.8	2020	22.7 Days	CHF 1200	Submit

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Published Papers (30 papers)