One common use of energy harvesting systems is in those places where the access to conventional sources of energy is difficult due to availability, space constraints, environmental hazards or sealed equipment. This article explores the possibilities of piezoelectrics to extract electrical energy and store it in capacitors to supply power of ultra-low power microprocessors.
The piezoelectric under test is a Lead Zirconate Titanate PZT-5J with reference S128-H5FR-1808YB manufactured by MIDE. The tests I am going to conduct are aimed at a specific application in which the piezo has to extract energy at 100 Hz with an acceleration as low as 2 ms or 0.2 g.
From right to left, the setup consists of a signal generator, signal conditioner and amplifier (top), signal amplifier (bottom), oscilloscope and vibrator or shaker with the piezoelectric (behind the oscilloscope).
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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, vol. 68, no. 12, pp. 4703-4711, Dec. 2019, doi: 10.1109/TIM.2019.2896553.
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Early access available at http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8653470&isnumber=4407674
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).
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 https://sciforum.net/paper/view/conference/5721
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.
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.
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.
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},