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Sensors Technology Applied in Power Systems and Energy Management

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Electronic Sensors".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 1395

Special Issue Editors


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Guest Editor
Electronic Technology Department, Escuela Politécnica Superior, University of Seville, St. Virgen de Africa, 7, 41011 Seville, Spain
Interests: fault location; power distribution network; power delivery; underground distribution system
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Electronic Technology Department, Escuela Politécnica Superior, University of Seville, St. Virgen de Africa, 7, 41011 Seville, Spain
Interests: power systems; renewable energy; generation and demand forecasting; demand response; flexibility; smart grid
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor Assistant
Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genova, 16145 Genova, Italy
Interests: energy; electric vehicles; optimization

Special Issue Information

Dear Colleagues,

Recently, as a response to the resilience demands of modern networks, the development of renewable generation sources, and the commitment to decarbonizing our society, the smart grid paradigm is gaining more attention than ever. This is reflected in the behavior of all the agents of the power system, including power utilities and customers, who keep pursuing cleaner and more efficient energy management. Proof of this is the evolution that the networks have experienced, resulting in self-controlled microgrids, virtual power plants and, more generally, smart local energy communities, some using a decentralized approach. Furthermore, these new architectures of decentralized power infrastructures require more resilience and faster communication systems that support the demands of this network philosophy. Thus, in this scenario, new approaches in sensor deployments and new architectures for their integration are becoming an essential tool to support this network growth. Additionally, due to the wide areas occupied by this type of power grids and the variety of systems involved, the use of communication systems and protocols that allow them to guarantee the interoperability as well as the integrity and coherence of the information is also essential.

In this sense, in order to face the aforementioned challenges, we propose this Special Issue, titled “Sensor Technology Applied in Power Systems and Energy Management”. Under this title, we expect high-quality, previously unpublished papers focused on the design and use of new sensor technologies and architectures for smart grid applications, which include but are not limited to the following topics:

Advanced metering infrastructures;

Wide-area monitoring, protection, and control systems;

Demand-side management systems based on sensors;

Smart home and smart building sensors and IoT applications;

Sensor-based energy monitoring and energy disaggregation;

Forecasting and optimization for energy management;

Technical and non-technical losses estimation through sensors;

Electric vehicle as a sensor in energy management;

Energy flexibility market devices;

Monitoring systems for asset management;

Cyber-physical systems in energy applications;

Communication protocols and standard;

Transactive energy and blockchain applications for data sensor integrity.

Dr. Enrique Personal
Dr. Antonio Parejo
Guest Editors

Dr. Luca Parodi
Guest Editor Assistant

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • smart grid sensors
  • advanced metering infrastructures
  • sensor-based flexibility services
  • microgrid and virtual power plant management based on sensors
  • monitoring systems for asset management

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Published Papers (3 papers)

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Research

19 pages, 1879 KiB  
Article
Fault Detection in MV Switchgears Through Unsupervised Learning of Temperature Conditions
by Grazia Iadarola, Alessandro Mingotti, Virginia Negri and Susanna Spinsante
Sensors 2025, 25(15), 4818; https://doi.org/10.3390/s25154818 - 5 Aug 2025
Viewed by 179
Abstract
This paper presents a distributed measurement system intended to effectively monitor the health status of switchgears under varying temperature conditions. In particular, thermocouples are deployed as temperature sensors for the continuous monitoring of a medium-voltage (MV) switchgear. Then, by integrating a low-cost microcontroller [...] Read more.
This paper presents a distributed measurement system intended to effectively monitor the health status of switchgears under varying temperature conditions. In particular, thermocouples are deployed as temperature sensors for the continuous monitoring of a medium-voltage (MV) switchgear. Then, by integrating a low-cost microcontroller unit, the proposed system can implement previously trained unsupervised learning techniques for health status evaluation. This approach enables the early detection of potential faults by identifying anomalous temperature patterns, thus supporting predictive maintenance and extending the lifespan of switchgears. The results show strong clustering performance with low execution times, highlighting the suitability of the method for resource-constrained hardware. Furthermore, onboard temperature processing eliminates the need for data transmission to remote servers, reducing latency and communication overhead while improving system responsiveness. The paper includes a numerical analysis on synthetic data as well as a validation on real measurements. Overall, the presented distributed measurement system offers a scalable and cost-effective solution to enhance the reliability and safety of MV switchgears. Full article
(This article belongs to the Special Issue Sensors Technology Applied in Power Systems and Energy Management)
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14 pages, 2796 KiB  
Article
Obtaining Rotational Stiffness of Wind Turbine Foundation from Acceleration and Wind Speed SCADA Data
by Jiazhi Dai, Mario Rotea and Nasser Kehtarnavaz
Sensors 2025, 25(15), 4756; https://doi.org/10.3390/s25154756 - 1 Aug 2025
Viewed by 302
Abstract
Monitoring the health of wind turbine foundations is essential for ensuring their operational safety. This paper presents a cost-effective approach to obtain rotational stiffness of wind turbine foundations by using only acceleration and wind speed data that are part of SCADA data, thus [...] Read more.
Monitoring the health of wind turbine foundations is essential for ensuring their operational safety. This paper presents a cost-effective approach to obtain rotational stiffness of wind turbine foundations by using only acceleration and wind speed data that are part of SCADA data, thus lowering the use of moment and tilt sensors that are currently being used for obtaining foundation stiffness. First, a convolutional neural network model is applied to map acceleration and wind speed data within a moving window to corresponding moment and tilt values. Rotational stiffness of the foundation is then estimated by fitting a line in the moment-tilt plane. The results obtained indicate that such a mapping model can provide stiffness values that are within 7% of ground truth stiffness values on average. Second, the developed mapping model is re-trained by using synthetic acceleration and wind speed data that are generated by an autoencoder generative AI network. The results obtained indicate that although the exact amount of stiffness drop cannot be determined, the drops themselves can be detected. This mapping model can be used not only to lower the cost associated with obtaining foundation rotational stiffness but also to sound an alarm when a foundation starts deteriorating. Full article
(This article belongs to the Special Issue Sensors Technology Applied in Power Systems and Energy Management)
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15 pages, 8092 KiB  
Article
Autonomous Lightning Strike Detection and Counting System Using Rogowski Coil Current Measurement
by Arthur F. Andrade, Giovanny M. B. Galdino, Ronimack T. Souza, Newton S. S. M. Fonseca, Antonio F. Leite Neto, Edson G. Costa and Eden L. Carvalho Junior
Sensors 2025, 25(8), 2563; https://doi.org/10.3390/s25082563 - 18 Apr 2025
Viewed by 633
Abstract
Lightning strikes are a leading cause of outages on overhead transmission lines, significantly compromising power system reliability. Consequently, monitoring lightning activity is critical to mitigate its impact on lines with high outage rates. This study presents an autonomous lightning strike counter system utilizing [...] Read more.
Lightning strikes are a leading cause of outages on overhead transmission lines, significantly compromising power system reliability. Consequently, monitoring lightning activity is critical to mitigate its impact on lines with high outage rates. This study presents an autonomous lightning strike counter system utilizing a split-core Rogowski coil for non-invasive current measurement on transmission towers. The system combines the Rogowski coil with an active integrator circuit to reconstruct the incident current waveform from the coil voltage signal. A microcontroller-based processing unit records strike occurrences and classifies them by amplitude using predefined thresholds. Laboratory tests were carried out to evaluate the performance of the Rogowski coil and integrator circuit, validating the system accuracy in detecting current pulses associated with lightning strikes. Underway field tests will assess the sensor’s reliability during long-term autonomous operation on 345-kV transmission towers. The results demonstrate that the proposed system represents a practical and cost-effective solution for lightning monitoring in remote areas, contributing to enhanced data collection for engineering studies and improved reliability of electrical infrastructure. Full article
(This article belongs to the Special Issue Sensors Technology Applied in Power Systems and Energy Management)
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