Advancements in the Internet of Things (IoT) and the Industrial Internet of Things (IIoT) technologies are revolutionizing monitoring and management of transmission infrastructure. For example, surge arresters, as critical components in protecting overhead transmission from lightning and switching overvoltages, can now benefit from intelligent embedded monitoring systems that provide real-time measurements and analytics. Moreover, integrating IIoT-based sensors with communication networks has made it possible to continuously track lightning current flowing through line surge arresters (LSA) and transmission towers. This enables early detection of abnormal conditions and improved system reliability.

This edited contribution to INMR from Dr. Selma Grebović at the Faculty of Electrical Engineering in the University of Sarajevo and Dr. Silvia Sinčić of the Croatian Transmission System Operator, proposes advanced design of measurement systems that leverage IIoT technologies. These systems combine precision sensors, robust communication modules and cloud-based analytics to enhance system protection, increase equipment lifetime and improve grid resilience.

Performance of overhead transmission lines is influenced by lightning activity, which is a primary cause of outages and power system disturbances. To design efficient protection strategies, it is essential to understand the characteristics of lightning currents, including parameters such as peak current, front duration, tail duration, maximum current steepness, charge transfer and specific energy. Improved lightning performance of OHLs can be achieved through measures such as enhancing tower grounding systems, increasing critical flashover voltage, applying grounding wires and installing line surge arresters (LSAs). Among these, LSAs are particularly attractive due to their cost-effectiveness, ease of installation and proven ability to reduce lightning caused flashover.

Monitoring lightning currents flowing through LSAs and transmission towers is crucial to obtain insight into lightning parameters, thereby validating flashover rate calculations (e.g. as with EMTP-type software) and specifying the discharge capabilities of arresters. Lightning location systems also provide data such as stroke time, 2D GPS co-ordinates, amplitude and lightning type. Yet they are unable to capture detailed current waveform – especially front and tail times that are essential for insulation co-ordination studies as well as understanding energy stress on arresters.

Fortunately, advances in electronics, communication networks and Industrial Internet of Things technologies open the possibility to develop embedded monitoring systems that operate in real time. These allow continuous measurement and transmission of high-resolution data from LSAs and towers, enabling advanced data-driven analysis, predictive maintenance and improved decision-making. While systems to measure lightning currents have been implemented in countries such as Japan, Switzerland, Canada and Austria, most are installed on tall telecom towers rather than on OHLs. This limits their applicability to transmission systems.

System Components & Laboratory Tests

A. System Components
The real-time lightning current measurement system developed consists of a sensor unit, recording unit, power supply, communication as well as storage, software and user interface (see Fig. 1).

A Rogowski coil is used to measure current through the surge arrester (10 kA/1 V ratio, bandwidth up to 8.3 GHz). The acquisition unit – a high-resolution oscilloscope with adjustable range (±80 V) and up to 1 GSa/s sampling rate – records lightning parameters such as peak, front time, tail time, polarity and multiplicity. A GPS/GNSS receiver with PPS output ensures precise time synchronization. Data is transferred via USB 3.0 to a computer (Windows 10, 8 GB RAM, SSD) and uploaded to the cloud via LAN, Wi-Fi, or 4G. While laboratory tests use local power, field installations can rely on solar batteries.

Custom software manages data acquisition, processing and transferring to cloud storage in .csv format. Pre-trigger recording ensures complete waveform capture, including all strokes in a flash. Manual control (trigger, PPS, GPS, record/send) is available for testing, while automated uploads and file deletion help manage storage space. The system launches automatically after power-on, thus enabling remote operation.

B. Laboratory Testing
Before field installation, all functionalities of the system were verified in a HV laboratory. Tests were performed using an impulse current generator producing standard lightning current waveshape (8/20 µs) with amplitudes up to 10 kA for both polarities. The system was compared against a conventional laboratory measurement set-up (50 MSa/s oscilloscope, low-inductive shunt R = 31.8 mΩ). The test object was a distribution surge arrester (SPD) with maximum discharge current of 40 kA, nominal discharge current of 15 kA and voltage protection level of 1.2 kV.

Lightning First Stroke Test
The initial experiment generated a single low-peak 8/20 µs impulse to verify proper triggering, acquisition and server communication. Once successful, multiple impulses with varying peaks were produced to confirm that all waveforms were correctly captured and transmitted via mobile network. Acquired shapes matched generated ones thereby validating accuracy and reliability.

Communication Test
This test evaluated data transmission performance over different networks with emphasis on mobile connectivity. Data transfer time between acquisition unit and computer was also monitored, thus confirming stable operation.

Test Results
Recorded waveforms (see Fig. 2) showed minor noise from the spark gap, which can be filtered using FFT, STFT or WT techniques. Noise was significantly reduced when the system was enclosed in a metal housing. Measured current peaks of ~6.3 kA and ~8.3 kA matched reference measurements from the shunt and laboratory oscilloscope. Direct surge current recordings inside the oscilloscope enclosure (see Fig. 3) showed no noise.

From Fig. 3, which shows directly measured surge currents, it is evident that there is no noise in the recorded signal due to the enclosure of the laboratory oscilloscope.

Laboratory tests demonstrated agreement in amplitude and waveform between the system and conventional measurements. Also, robust cloud data transfer and network communication were confirmed. As such, the system was validated for deployment under field conditions.

Strategic Implementation

A 110 kV overhead line tower on the Croatian island of Brač was selected for installation of the lightning current measurement system. The location was selected because it is in an area with high ground stroke density, ensuring a sufficient number of lightning events during the operating period. Prior to installation of LSAs, overhead lines on Brač experienced numerous lightning-related outages. While most were transient faults cleared by the auto-reclosure function of the relay protection system, there were cases of prolonged power supply interruption along with significant damage to primary or secondary substation equipment. Fig. 4 provides an example of lightning activity recorded by the Lightning Location System (LLS) during a one-hour period. For lightning performance calculations in this area, a keraunic level of approx. 40 thunderstorm days per year is typical.

Optimal placement of LSAs across the towers and phases was determined using EMT simulations for different configurations. Overhead lines in Croatia are equipped with shield wire, which is standard protection in the country’s transmission network. Other measures that could improve overvoltage performance, such as reducing tower grounding impedance or increasing critical flashover voltage (CFO) of insulator strings, were not considered feasible for lines operating in this environment.

After LSA installation, the number of events recorded by the relay protection system dropped significantly. Efficiency of LSA configuration in relation to lightning activity was evaluated by analyzing operational events and LLS data. Fig. 5 shows location of the tower selected for this study.

To enable detailed analysis of lightning transient current distribution through the tower and for all three phases, the lightning current measurement system was installed on the 110 kV tower equipped with LSAs on every phase.

System Installation

Installation of the system on a transmission tower posed a challenge and required development of a special design. Intricacies of the structure as well as need for precise positioning required a thorough planning phase to ensure effective deployment. Careful consideration and innovative design were crucial. For example, the Rogowski coil used to measure current through the tower was positioned between bottom and middle console. Fig. 6 which also shows method of installation of the coil around the tower. It was necessary to secure two screws into the structure along with corresponding brackets through which the coil had to be threaded.

Fig. 7 provides a representation of the procedure to affix the Rogowski coil onto the tower, in conjunction with its associated support structure. The screw employed to secure the structure onto the tower served a dual purpose by also acting as the point of connection for fastening the cable from the surge arrester to the tower structure. This intricate set-up ensured that every current flowing through the arrester would also have to pass through the Rogowski coil. Utilizing the screw as both fastener and connection point guaranteed unimpeded flow of current through the coil, thereby optimizing current measurement.

Fig. 8 depicts key components of the system, housed within a cabinet installed on the tower as well as the manner with which they were interconnected. These included fuses for solar power supply, charging controller, inverter, and batteries. The cabinet also contained coil integrators connected to an acquisition device. This acquisition device established connection with a computer which links to both a GPS device and USB dongle for communication via mobile internet. Corresponding antennas were connected to both GPS receiver and USB dongle to ensure optimal function of these devices.

First Results

The system was installed in May 2024 and has since been operating continuously. Two events are described below. Since installation there have been no disruptions or operational issues. The system has operated stably and reliably, with the solar-battery power supply proving effective in ensuring uninterrupted performance. No communication issues have been encountered and remote access to the system has worked consistently with no failures. This has allowed seamless monitoring and control from a distance.

Moreover, the mobile internet connection has provided continuous, reliable service, while maintaining an impressive speed that supports transmission of data. Stable network performance has been crucial for real-time operation and monitoring, further contributing to the system’s overall reliability and effectiveness.

A. Lightning Current Recording

The measurement system recorded a lightning event on July 20, 2024 at 11:27:08.918147. The current was measured using a Rogowski coil placed around the tower, along with 3 additional Rogowski coils measuring currents through surge arresters installed on the bottom, middle and top phases of the 110 kV transmission line tower. Fig. 9 (left) shows currents measured through the tower, while currents measured through the arresters are presented on the right. Current amplitudes were: 3 kA through the arrester on the bottom phase, 1 kA through the arrester on the middle phase, and 0.9 kA through the arrester on the upper phase. Such distribution of current amplitude is to be expected in the case of a lightning stroke, since it reflects the effect of coupling between phases and sky wire.

According to CIGRE Brochure 839 (2021), the voltage which develops across the insulator string due to the lightning stroke includes two components: transient voltage due to the lightning stroke and power frequency voltage which exists on the phase conductor at time of the stroke. Voltage amplitude across the insulator string can be affected by parameters such as tower surge impedance, tower footing resistance, influence of electromagnetic coupling and value of the phase voltage at time of the lightning strike.

Electromagnetic coupling factor takes account of the influence of the voltage induced on the phase conductor due to electric and magnetic coupling (which acts to reduce voltage on the insulation) and depends on mutual distance between phase and shield wire, i.e. it becomes smaller with growing mutual distance between phase and shield wire. Therefore, overvoltage amplitude is highest on the insulator string on the bottom phase, which is farthest from the shield wire.

Comparison was made between the event recorded and captured by the measurement system and data from the Lightning Location System (LLS). LLS software provides, along with data on time and date of the lightning stroke, GPS coordinates (2D), lightning current amplitude, lightning type (inter-cloud /IC or cloud-to-ground/CG), height (for inter-cloud lightning) and 2D statistical error. The system recorded the event on July 20, 2024, at 11:27:08.918147 with current amplitude of -17.8 kA. Meanwhile, the LLS registered a negative stroke with a current of -18.2 kA, occurring on July 20, 2024, at 11:27:08.860. It seems clear that both systems recorded the same event since time and amplitude matched remarkably well. Fig. 10 presents the list of lightning strokes recorded by LLS which spatially correlate with the overhead line’s corridor. Fig. 11 shows the LLS software’s geographic representation of the lightning strokes recorded on June 20, 2024.

The event was not registered by the overhead line’s relay protection system. Therefore, it could be concluded that the stroke did not cause a line outage and that the LSAs had performed their function.

B. Switching Transient Current Recording

Since the system first became operational, it has recorded one additional event. On June 21, 2024, a major power outage affected Bosnia and Herzegovina, Montenegro, Croatia and Albania. During the process of restoring the grid, the SCADA system logged reactivation of the transmission line where the measurement system was installed at 14:53:41 on June 21, 2024 (see Fig. 12). At the same time of day, the measurement system recorded activation of the arrester installed on the top phase of the tower at 14:53:40 (see Fig. 13). From this, it was concluded that both systems had registered the same event given that there was excellent time correlation.

The new measurement system, although specifically designed for recording lightning events (e.g. the event from July 20, 2024 as in Fig. 9), demonstrated its robustness and effectiveness by capturing a switching transient during grid restoration on June 21, 2024 (see Fig. 13). These demonstrate the system’s versatility in detecting various types of transient phenomena.

Conclusions

Advancements in monitoring line surge arresters (LSA) and lightning currents on overhead transmission lines highlight the role of modern embedded monitoring systems (EMS) and Industrial Internet of Things (IIoT) technologies in improving power system protection and resilience. A system developed for this goal successfully measured lightning current waveforms through LSAs and towers, providing high-resolution data essential for analysis of electromagnetic transient phenomena and validation of simulation tools. Laboratory testing confirmed accuracy and reliability of this approach to measurement and demonstrated its suitability for field installation.

Strategic implementation of these systems, supported by data from lightning locating systems (LLS), enables better understanding of lightning parameters, facilitates predictive maintenance and reduces risk of equipment damage. Integration of IIoT-based communication and cloud platforms ensures real-time data transmission and analytics, while offering operators a tool to optimize system operation and extend life of critical components.

Future work will focus on deploying more monitoring devices to establish a comprehensive dataset for advanced analysis. Once sufficient data has been collected, application of artificial intelligence and machine learning techniques will allow predictive analytics, anomaly detection, and automated decision-making. This will pave the way toward intelligent, self-healing grids. Continued development of these types of monitoring systems will contribute to enhanced grid reliability, improved insulation coordination while mitigating impact of lightning.

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