Multiple Partial Discharge Source Localization in Power Cables Through Power Spectral Separation and Time-Domain Reflectometry

G. Robles, M. Shafiq and J. M. Martínez-Tarifa, “Multiple Partial Discharge Source Localization in Power Cables Through Power Spectral Separation and Time-Domain Reflectometry,” in IEEE Transactions on Instrumentation and Measurement. doi: 10.1109/TIM.2019.2896553

Open access post-print version (ie final draft post-refereeing) available (Copyright 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works).

Early access available at


Abstract— Insulated power cables are becoming increasingly popular in today’s developing distribution and transportion networks. However, due to aging, deterioration, and various operational and environmental stresses, insulation defects may appear and so the cable needs to be monitored in a timely manner to avoid unexpected failures. Many of these defects are responsible for partial discharge (PD) activity. The localization of the sources of these discharges is a highly decisive facet in the condition-based monitoring of power cables. The techniques for the localization of single-PD defects in insulated power cables are well presented in the current bibliography. However, when several simultaneous PD sources are active, the localization of the sources becomes quite complex. This paper develops an efficient technique for the separation and localization of multiple PD sources in a medium voltage cable. The experimental results are obtained with single-end-based measurements using a high-frequency current transformer in a laboratory environment. The data processing based on the spectral characteristics of the signals is carried out by using the power ratios technique in order to determine the presence of different types of PD. Once the signals are separated, the PD sources can be localized with an individualized analysis of each source through time-domain reflectometry. The proposed methodology can be very valuable to improve the location diagnostic capability of the condition-based monitoring solutions, especially for underground cables.

Keywords— Condition monitoring; partial discharges (PDs); particle swarm optimization (PSO); power cables; signal characterization; signal propagation; spectral power ratios (PRs); time-domain reflectometry (TDR).

Designing a Rogowski coil with particle swarm optimization

Guillermo Robles; Muhammad Shafiq; Juan Manuel Martínez-Tarifa, Designing a Rogowski coil with particle swarm optimization, November 2018, Proceedings of the 5th International Electronic Conference on Sensors and Applications session Physical Sensors (doi: 10.3390/ecsa-5-05721)

Open access at

Abstract—Rogowski coils are inductive sensors based on Faraday’s and Ampère’s Laws to measure currents through conductors without galvanic contact. The main advantage of Rogowski coils when compared with current transformers is the fact that the core is air so they never saturate and the upper cut-off current can be higher. These characteristics makes Rogowski coils ideal candidates to measure high amplitude pulsed currents. On the contrary, there are two main drawbacks. On the one hand, the output voltage is the derivative of the primary current so it has to be integrated to measure the original signal; and, on the other hand, the transfer function is resonant due to the capacitance and the self-inductance of the coil. The solution is the use of a passive integration with a terminating resistor at the output of the sensor that splits the two complex poles and gives a constant transfer function for a determined bandwidth. The downside is a loss of sensitivity. Since it is possible to calculate the electrical parameters of the coil based on its geometrical dimensions, the geometry can be  adapted to design sensors for different applications depending on the time characteristics of the input current. This paper proposes the design of Rogowski coils based on their geometric characteristics maximizing the gain-bandwidth product using particle swarm optimization and adapting the coil to the specific requirements of the application.

Keywords—Rogowski coils; particle swarm optimization; gain-bandwidth product; current
measurement; magnetic field measurement.


20 puestos de especialización para jóvenes ingenieros y físicos aplicados en la 4ª convocatoria del Spanish Traineeship Programme, CIEMAT-CERN

En los próximos días, se abrirá la cuarta convocatoria del Spanish Traineeship Programme, FTEC-2018, un programa de especialización tecnológica en el CERN, Ginebra, Suiza, destinado a jóvenes ingenieros y físicos aplicados.

La convocatoria tiene como objetivo incrementar la presencia de investigadores y técnicos españoles en el CERN, así como consolidar un colectivo de ingenieros y físicos especializados en tecnologías de los grandes aceleradores de partículas, detectores e infraestructuras asociadas, con la finalidad de una futura incorporación a la industria e instituciones del sector.

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Online condition monitoring of MV cable feeders using Rogowski coil sensors for PD measurements

M. Shafiq, K. Kauhaniemi, G. Robles, M. Isa, L. Kumpulainen, “Online condition monitoring of MV cable feeders using Rogowski coil sensors for PD measurements”, Electric Power Systems Research, Volume 167, February 2019, Pages 150-162, ISSN 0378-7796,

Abstract— Condition monitoring is a highly effective prognostic tool for incipient insulation degradation to avoid sudden failures of electrical components and to keep the power network in operation. Improved operational performance of the sensors and effective measurement techniques could enable the development of a robust monitoring system. This paper addresses two main aspects of condition monitoring: an enhanced design of an induction sensor that has the capability of measuring partial discharge (PD) signals emerging simultaneously from medium voltage cables and transformers, and an integrated monitoring system that enables the monitoring of a wider part of the cable feeder. Having described the conventional practices along with the authors’ own experiences and research on non-intrusive solutions, this paper proposes an optimum design of a Rogowski coil that can measure the PD signals from medium voltage cables, its accessories, and the distribution transformers. The proposed PD monitoring scheme is implemented using the directional sensitivity capability of Rogowski coils and a suitable sensor installation scheme that leads to the development of an integrated monitoring model for the components of a MV cable feeder. Furthermore, the paper presents forethought regarding huge amount of PD data from various sensors using a simplified and practical approach. In the perspective of today’s changing grid, the presented idea of integrated monitoring practices provide a concept towards automated condition monitoring.

Keywords—Condition monitoring; Rogowski coil; Dielectric insulation; Partial discharge; Medium voltage cable; Transformer.

Partial Discharge Signal Propagation in Medium Voltage Branched Cable Feeder

M. Shafiq, K. Kauhaniemi, G. Robles, G. A. Hussain and L. Kumpulainen, “Partial discharge signal propagation in medium voltage branched cable feeder,” in IEEE Electrical Insulation Magazine, vol. 34, no. 6, pp. 18-29, November-December 2018.

doi: 10.1109/MEI.2018.8507714

Abstract— Rising global and regional electricity use is accelerating the need to upgrade networks. The adoption of sustainable ways of energy generation (renewables energy resources) is the top priority of today’s grid, and these resources are predominantly embedded within the distribution networks that are mostly connected by medium voltage (MV) cables. Driven by urbanization trends, negative land value impacts, public safety, environmental aesthetics, and network reliability, the resistance to overhead lines in distribution networks is gradually increasing in many countries. Either choosing the proactive path considering the operational superiority of underground cables compared with overhead lines or following the ongoing legislative policies, the use of cables has been increasing rapidly over the past 30 years. This trend is likely to accelerate.

Keywords— Power cables; Partial discharges; Power cable insulation; Cable shielding; Current measurement; Voltage measurement; Medium voltage; Condition monitoring; Cables; Branch; Joint; Diagnostic; Sensor},


Energy harvesting and NFC tag (LTC3108 -> STM32L433 -> M24SR)

The idea behind this work was to test the capabilities of using a near-field communication (NFC) tag to store the information acquired through an analogue input of a microprocessor powered by an energy harvesting source.

The setup includes these components:

  • Peltier cell
  • Energy harvesting system
  • Microprocessor
  • Dynamic NFC/RFID tag IC
  • Temperature sensor

Energy harvesting system

The capabilities of Peltier cells to harvest energy from differences of temperature between its two sides has already been studied in other posts starting with this link, so I will not develop this part of the work here.

The energy harvesting system used in this project is now based on the outstanding Linear Technologies (now part of Analog Devices) Ultralow Voltage Step-Up Converter and Power Manager LTC3108. This device can work with four selectable output voltages: 2.35 V, 3.3 V, 4. V or 5 V to power wireless transmitters or sensors and a low dropout voltage regulator output (VLDO) to power an external microprocessor. According to its datasheet it can start harvesting energy from voltages as low as 20 mV which is precisely indicated for applications that use thermo-electric generator (TEG) such as Peltier cells. The energy is stored in a bank of supercapacitors connected to two outputs of the LTC3108. Two 1 F supercapacitors in series are connected to VOUT and charged when VAUX has reached 2.5 V. Another two 1 F supercapacitors are connected to VSTORE supporting VOUT and preventing an unexpected drop of voltage due to a high power demand by the load. A picture of the setup for this integrated circuit (IC) is:

Continue reading Energy harvesting and NFC tag (LTC3108 -> STM32L433 -> M24SR)

Special Issue “UHF and RF Sensor Technology for Partial Discharge Detection”

Special Issue Information


Dear Colleagues,

Condition monitoring (CM) of high-voltage (HV) insulation systems is essential for establishing a correct diagnosis regarding the health of these costly and safety-critical industrial assets, as well as for implementing practical condition-based-maintenance (CBM) regimes. The assets being monitored may include rotating machines, power transformers, HV cables and accessories, air-insulated-substations (AIS), gas-insulated-switchgear (GIS) and overhead lines. Recent advances have seen widespread development of non-contact electromagnetic wave sensors for detecting and locating partial discharges and electrical arcs. These sensors play an important role in periodic testing, continuous monitoring or ‘fingerprinting’ of RF emissions from HV equipment. Practical applications of UHF and other RF techniques are leading to the development of new sensors and associated solutions for signal acquisition, processing, analysis and interpretation, which in turn require new approaches to decision making about the condition of assets being monitored.

The aim of this Special Issue is to report on recent advances relating to the following themes: (1) non-contact electromagnetic sensors (RF, UHF, near field, electric, magnetic, etc.) used for detecting signals emitted by insulation defects either internally, or external to the equipment in question; (2) practical methods for integrating these sensors into real equipment for use in condition monitoring; (3) case studies and examples of implementation of the techniques in an industrial or laboratory setting; (4) sensor models to support the design process or for predicting their response (using data-driven modeling approaches, for example); and (5) bridging the gap between condition monitoring research and subsequent decision making using these technologies, possibly in combination with other monitoring parameters.

Prof. Dr. Ricardo Albarracín
Prof. Dr. Martin D. Judd
Prof. Dr. Guillermo Robles
Prof. Dr. Pavlos Lazaridis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Sensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs).

A combined algorithm approach for PD location estimation using RF antennas

J. M. Fresno, G. Robles, J. M. Martínez-Tarifa and B. G. Stewart, “A combined algorithm approach for PD location estimation using RF antennas,” 2017 IEEE Electrical Insulation Conference (EIC), Baltimore, MD, USA, 2017, pp. 384-387.
doi: 10.1109/EIC.2017.8004695

Abstract— To locate the positions of partial discharge sources in free space at least four RF antennas are arranged in a suitable
spatial geometry to detect the radiated electromagnet energy from the discharge. The time-difference-of-arrival (TDOA) between the signals from each antenna are then used within multi-lateration equations to determine the position of the source. The iterative Hyperbolic Least Squares (HLS) method and the non-iterative Maximum Likelihood Estimator (MLE) method are two common techniques used in the literature to solve the multi-lateration equations. This paper investigates the ability of combining MLE and HLS to improve location accuracy and maintain fast location computation time. To this end HLS, MLE and the combined MLEHLS method are evaluated in terms of location accuracy and computation performance for three spatial antenna configurations, namely Square, Pyramidal and Trapezoidal arrangements. The location accuracies for each method are evaluated for theoretical TDOA values and also for the case when a finite sampling rate of 10G samples-per-second is considered; the latter is implemented through appropriate rounding up of TDOA values by one sample time. It is shown that MLE-HLS produces improved location accuracy compared with HLS and MLE for both theoretical and finite sampled TDOA values. In addition, it is shown that MLE-HLS improves significantly the computation time over the iterative HLS method.

Keywords— Antenna theory; Mathematical model; Maximum likelihood estimation; Partial discharges; Position measurement; location algorithms; partial discharges; radio-frequency localization

Characterization of Peltier cells for energy harvesting applications (III)

As demonstrated in the former post, the equivalent voltage source of the cell depends on the temperature difference of the surfaces and takes a value of V_o = 0.0245 \cdot \Delta T and the internal series resistor is R_s = 2.24~\Omega. Therefore, there would be different power outputs considering the resistor load and the temperature difference. The next plot shows the delivered power to a set of loads and four temperature differences \Delta T =[5,~10,~15,~20] degree Celsius. The maximum power given by the cell is delivered to a load that equals the internal resistor, R_s=R_L and takes a value of:

P_{max}=\frac{V_o^2}{4R_L}&s=1 W


If a difference of temperatures of 20 ºC is achieved the voltage at the load would be 245 mV and it would draw a current of 109.4 mA, the maximum power would reach 26.8 mW when connecting a load of 2.24~\Omega. Of course, all these data are hypothetical since the assumptions are in the most optimistic side considering that R_s=R_L. Even under these circumstances a voltage booster would be needed to increase the voltage to a level according to the requirements of the MCU. For instance, the ultralow power STM32L432 ARM Cortex M4 requires at least a power supply of 1.71 V. There are two options to increase the voltage, using voltage multipliers or using DC-DC converters.

Voltage multipliers

These circuits use a combination of diodes and capacitors that allows to duplicate the voltage at the input in every stage. A common setup is the Cockcroft-Walton configuration as the shown in this paper to multiply the voltage obtained from events that create pulses that can reach peaks of 1 V or more. In the case of one or two Peltier cells connected in series, this circuit is out of the question since the Schottky diodes with the lowest forward voltage drop are close to 250 mV so they would consume the voltage provided by the cell or cells.


Voltage boosters

Voltage boosters or DC-DC step-up converters would be the most feasible solution. The working principle is easy. The inductance L is charged closing switch S storing a magnetic field. This field will maintain the current flowing towards load R when S is opened. Since the inductance is giving energy to the load the voltage at L is effectively reversed and added to v_i(t) increasing the voltage at the output, v_o(t). The switching should be done fast to avoid a total magnetic discharge of the coil when S is open and a total depletion of capacitor C when S is closed. The diode D prevents the capacitor from discharging through S.Booster.png

This idea has been implemented in integrated circuits (IC) that scavenge small quantities of energy from the source, in our case the Pletier cell, to drive the switch and are able to increase the voltage at the output upto 3.3 V or 5 V depending on the MCU connected. Some examples of these IC and their behavior under real conditions are shown in the next post.



Characterization of Peltier cells for energy harvesting applications (II)

With the setup described in the last post, the temperature of one of the surfaces of the cells can be controlled with an electrical current, the other surface is cooled passively with a heatsink. The resistors and the two temperature sensors are connected to the same voltage source taking advantage of the wide range of voltages supported by the LM35. The outputs of the LM35 are connected directly to two multimeters to measure the differences of temperature achieved between the two surfaces. Now, the process is easy: the resistors are heated with different currents and the output voltages of the cell and the temperatures are registered. This will solve the voltage source of the equivalent electric circuit of the cell in open circuit or the Thévenin voltage. The results are represented in the next Figure showing a perfect linearity between temperature and voltage.


I_s = [0.49~0.59~0.69~0.79] A
V_s = [12.3~14.6~17.3~20] V

V_o = [62.4~140.5~252.5~414~580~775] mV

T_h = [24.8~30.2~38.4~55.0~66.5~82.7] degree Celsius
T_c = [22.5~24.5~28.0~38.0~42.9~51.0] degree Celsius

Where, I_s and V_s are the current and voltage applied by the power supply to the resistors, respectively; V_o is the output of the cell and T_h and T_c are the temperatures of the hot and cold sides of the cell, respectively. The plot shows that V_o = 0.0245 \cdot \Delta T with the slope in V / ºC.

The next test will determine the equivalent series resistance, R_s, of the cell loading it with a known resistor, R_L = 13.5~\Omega. In this case, the current given by the cell provokes a voltage drop in the internal resistor R_s so the voltage applied to R_L, V_L, is smaller than the open circuit voltage, V_o > V_L.  A new set of measurements is conducted injecting the same current to the heating resistors to determine this voltage and, then, the internal resistance of the cell:

V_L = [51.9~121.1~ 211.7~ 344.1~ 486~ 639] mV

T_h = [27.6~ 33.2~ 40.7~ 53.0~ 65.0~ 79.3] degree Celsius
T_c = [25.5~ 27.7~ 30.7~ 36.7~ 41.9~ 48.6] degree Celsius


The blue plot represents the voltage in open circuit, V_o, and the red plot the voltage at the load, V_L. Dividing this voltage by the load resistor yields the current given by the cell, I_L. Therefore, the internal resistor is calculated applying Ohm’s Law knowing that the voltage drop is V_o - V_L and the current is I_L. This is done for several points along the experimental results in the plot giving a constant value for the resistor, R_s = 2.24~\Omega. The same process is repeated for another cell of the same type and the result for R_s differ from the first cell giving R_s = 4.75~\Omega. Even when the former internal resistor is double the latter one, the results have been re-checked and confirmed and are in agreement to other results found in the literature.

Once the cell has been characterized, it is possible to determine the current that it will give to a known load. The next step is to devise a method to store the energy delivered by the cell or to explore the possibility of boosting the voltage to drive an MCU (microcontroller unit) directly. This will be explained in the next post.