Advanced Sensing Strategies for Monitoring of Power Equipment

Submission Deadline: 30 May 2023 Submit to Special Issue

Guest Editors

Jianhong Zhou, Xihua University, China.

Jun Jiang, Nanjing University of Aeronautics and Astronautics, China.

Wei Dai, Guangxi University, China.


The grid modernization tendency to smart grids is requiring the measurement of state variables for allowing the proper management and diagnostics of key T&D power equipment. Non-invasive tests, preferably done on-line, to determine the status of equipment would reduce outages and faults, increase reliability, and reduce investment, operation and maintenance costs. The use of advanced sensing strategies for monitoring power equipment is still the core in power system to get access to the health status and operation information. It provides the main collection source of massive data for condition-based-maintenance (CBM) regimes in field application. Therefore, the technical level of smart sensing systems and intelligent processing of data for taking decisions, directly determines the construction process of cyber-physical integration in the power Internet of Things (IoT).


Topics of interest include, but not limited to:

• Innovations on instrumentation, measurement and techniques used in advances strategies for condition monitoring of power equipment

• Methods for monitoring equipment aging and evaluating equipment lifespan

• Simulation and modelling of electrical insulation weaknesses to estimate equipment remaining life

• Electrical transient measurement and location of equipment failures

• Multi-source data analysis and comprehensive diagnosis of sensing systems

• Power equipment status recognition and fault diagnosis technology based on artificial intelligence schemes and deep learning

• New developments in asset management


Papers will be selected from 2023 the 7th International Conference on Power Energy Systems and Applications (ICoPESA),, Nanjing, China | February 24-26, 2023


Condition monitoring, Power Equipment, Electrical insulation, fault diagnosis, advanced sensing

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