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Developing Control and Measurement Algorithms for Electrical Power Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F1: Electrical Power System".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 17492

Special Issue Editor


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Guest Editor
Faculty of Electrical and Computer Engineering, Cracow University of Technology Warszawska 24, 31-155 Cracow, Poland
Interests: measurement and data analysis; mathematical modeling of measurement systems; signal processing; sensors calibration; electrical measurement of nonelectrical quantities; uncertainties in measurement; dynamic error
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Special Issue Information

Dear Colleagues,

An electrical power system is a distributed network consisting of three main aspects: generation, transmission, and distribution. Its structure includes a significant number of electrical machines and devices, power lines and stations, electricity receivers, control devices, and measurement systems.

To ensure mutual co-action and suitable levels of accuracy of the specific components of the electrical power system, appropriate algorithms for control and measurement are required. These algorithms are based on the latest scientific achievements in the fields of analog and digital signal processing, control theory, modern metrology, and artificial intelligence methods. They not only allow for proper control of the electrical power system but also the implementation and proper interpretation of measurements of both electrical and non-electrical quantities. This contributes to ensuring the reliability of the entire electrical power system, as well as the supply of electricity of appropriate quality to receivers, both individuals and entrepreneurs.

This Special Issue invites contributions on the topic of new control and measurement algorithms intended for electrical power systems. In particular, scientists are encouraged to present new solutions for electrical power systems based on the use of advanced tools and computational techniques in the fields of digital processing of electrical signals, artificial intelligence methods, and control theory, and to present the results of measurements and an analysis of the corresponding uncertainties.

To ensure a clear presentation of the proposed solutions, it is necessary to describe the corresponding state of the art, and to carry out a detailed review of the relevant literature. It is also desirable that the proposed control and measurement algorithms be validated based on experimental or simulation data. In order to emphasize the practical value of the proposed solution, a discussion of the possible real-world applications and further developments are welcome.

Prof. Dr. Krzysztof Tomczyk
Guest Editor

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Keywords

  • artificial intelligence 
  • computational algorithm 
  • control algorithm 
  • control system 
  • data analysis 
  • data acquisition 
  • decision algorithm 
  • devices for electrical power systems 
  • digital signal processing 
  • distributed computing 
  • distributed system 
  • electric power quality 
  • electrical quantity 
  • errors in electrical power systems 
  • evolutionary algorithm 
  • fuzzy logic 
  • genetic algorithm 
  • measurement algorithm 
  • measurement system 
  • measurement technique 
  • measuring instrument 
  • nonelectrical quantity 
  • optimization of electrical power system 
  • precision measurement 
  • signal distortion 
  • signal reproduction 
  • special algorithms 
  • time-frequency analysis 
  • uncertainty analysis 
  • validation of computational algorithms 
  • wavelet analysis

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Related Special Issue

Published Papers (8 papers)

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Research

22 pages, 1970 KiB  
Article
Power Transformer Fault Detection: A Comparison of Standard Machine Learning and autoML Approaches
by Guillermo Santamaria-Bonfil, Gustavo Arroyo-Figueroa, Miguel A. Zuniga-Garcia, Carlos Gustavo Azcarraga Ramos and Ali Bassam
Energies 2024, 17(1), 77; https://doi.org/10.3390/en17010077 - 22 Dec 2023
Cited by 11 | Viewed by 3348
Abstract
A key component for the performance, availability, and reliability of power grids is the power transformer. Although power transformers are very reliable assets, the early detection of incipient degradation mechanisms is very important to preventing failures that may shorten their residual life. In [...] Read more.
A key component for the performance, availability, and reliability of power grids is the power transformer. Although power transformers are very reliable assets, the early detection of incipient degradation mechanisms is very important to preventing failures that may shorten their residual life. In this work, a comparative analysis of standard machine learning (ML) algorithms (such as single and ensemble classification algorithms) and automatic machine learning (autoML) classifiers is presented for the fault diagnosis of power transformers. The goal of this research is to determine whether fully automated ML approaches are better or worse than traditional ML frameworks that require a human in the loop (such as a data scientist) to identify transformer faults from dissolved gas analysis results. The methodology uses a transformer fault database (TDB) gathered from specialized databases and technical literature. Fault data were processed using the Duval pentagon diagnosis approach and user–expert knowledge. Parameters from both single and ensemble classifiers were optimized through standard machine learning procedures. The results showed that the best-suited algorithm to tackle the problem is a robust, automatic machine learning classifier model, followed by standard algorithms, such as neural networks and stacking ensembles. These results highlight the ability of a robust, automatic machine learning model to handle unbalanced power transformer fault datasets with high accuracy, requiring minimum tuning effort by electrical experts. We also emphasize that identifying the most probable transformer fault condition will reduce the time required to find and solve a fault. Full article
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14 pages, 4136 KiB  
Article
Extended Calibration of Charge Mode Accelerometers to Improve the Accuracy of Energy Systems
by Krzysztof Tomczyk
Energies 2023, 16(22), 7619; https://doi.org/10.3390/en16227619 - 17 Nov 2023
Viewed by 851
Abstract
This paper presents an extended calibration procedure for mode accelerometers, which makes it possible to compare the accuracy of sensors of this type from different manufacturers. This comparison involves determining the upper bound on dynamic error for a given quality criterion, i.e., the [...] Read more.
This paper presents an extended calibration procedure for mode accelerometers, which makes it possible to compare the accuracy of sensors of this type from different manufacturers. This comparison involves determining the upper bound on dynamic error for a given quality criterion, i.e., the integral square error and absolute error. Therefore, this article extends the standard calibration implemented in engineering practice using tests, providing a value for the upper bound on dynamic error as an additional parameter describing the accelerometer under consideration. This paper presents the theoretical basis for this type of solution, which is partly based on measurement data obtained from a standard calibration process and on the results of parametric identification. The charge mode accelerometer is considered here because this type of sensor is commonly used in the energy industry, as it can operate over a wide range of temperatures. The calculation results presented in this paper were obtained using MathCad 5.0 software, and the tests were carried out using an accelerometer of type 357B21. In the experimental part of this article (Results of Extended Calibration section), values for the upper bound of the dynamic error were determined for two error criteria and constrained simulation signals related to these errors. The impact of interference on the results of accelerometer tests was omitted in this paper. Full article
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20 pages, 1151 KiB  
Article
Output-Feedback Multi-Loop Positioning Technique via Dual Motor Synchronization Approach for Elevator System Applications
by Hyo Chan Lee, Hyeoncheol Lee, Jae Kwang Lee, Hyun Duck Choi, Kyunghwan Choi, Yonghun Kim and Seok-Kyoon Kim
Energies 2022, 15(23), 9147; https://doi.org/10.3390/en15239147 - 2 Dec 2022
Viewed by 1625
Abstract
This paper devises an output-feedback multi-loop positioning technique adopting the speed observer and multi-motor synchronizer, targeting the dual (master and slave) motor elevator system applications, providing the three contributions. First, the order-reduction observer continuously extracts the speed information from the motor position measurement, [...] Read more.
This paper devises an output-feedback multi-loop positioning technique adopting the speed observer and multi-motor synchronizer, targeting the dual (master and slave) motor elevator system applications, providing the three contributions. First, the order-reduction observer continuously extracts the speed information from the motor position measurement, independent of the system model information. Second, the order-reduction stabilizer accomplishes the speed synchronization tasks for both the master and slave motors. Third, the resultant feedback system guarantees to exponentially recover the desired first-order transfer function from the reference to the actual motor position despite the model-plant mismatches. The prototype elevator system adopting the dual motor experimentally validates the practical advantages of the proposed technique. Full article
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13 pages, 1309 KiB  
Article
Analysis of the Upper Bound of Dynamic Error Obtained during Temperature Measurements
by Krzysztof Tomczyk and Piotr Beńko
Energies 2022, 15(19), 7300; https://doi.org/10.3390/en15197300 - 4 Oct 2022
Cited by 1 | Viewed by 1347
Abstract
This paper presents an analysis of the upper bound of the dynamic error obtained during temperature measurements. This analysis was carried out for the case of the absolute error criterion and for the numerically determined excitation signals, with one and two constraints. The [...] Read more.
This paper presents an analysis of the upper bound of the dynamic error obtained during temperature measurements. This analysis was carried out for the case of the absolute error criterion and for the numerically determined excitation signals, with one and two constraints. The negative temperature coefficient (NTC) and K-type thermocouple sensors were tested, and the upper bound of the dynamic error was determined for the case of one and two constraints imposed on the input signal. The influence of the sensor modelling uncertainty on the values of the upper bound of the dynamic error has also been taken into account in this paper. Numerical calculations and the corresponding analysis were carried out using the MathCad 14 program. The solutions presented in this paper make it possible to obtain precise solutions in the field of classic calibration of temperature sensors—but, above all, they allow for a mutual comparison of the accuracy of widely used sensors in the energy industry. Full article
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17 pages, 2080 KiB  
Article
Power System Stability Enhancement Using a Novel Hybrid Algorithm Based on the Water Cycle Moth-Flame Optimization
by Ikram Boucetta, Djemai Naimi, Ahmed Salhi, Saleh Abujarad and Laid Zellouma
Energies 2022, 15(14), 5060; https://doi.org/10.3390/en15145060 - 11 Jul 2022
Cited by 7 | Viewed by 2013
Abstract
Poor control of the power grid can lead to a total system collapse, causing significant economic losses and possible damage to security and social peace. Therefore, improving power system stability, particularly transient stability, has become one of the major research topics. This paper [...] Read more.
Poor control of the power grid can lead to a total system collapse, causing significant economic losses and possible damage to security and social peace. Therefore, improving power system stability, particularly transient stability, has become one of the major research topics. This paper proposes a developed modeling approach that provides the optimal stabilizer parameters of the control devices, aiming at improving the electrical network stability by minimizing the angular speed deviation in the presence of a severe disturbance event using a novel hybrid algorithm called Water Cycle-Moth Flame Optimization (WCMFO). The main advantages of the proposed method are the speed of response and its efficient exploration and exploitation ability to attain the best solution quality. This is achieved by imposing a thermodynamic incident (an abrupt change in mechanical torque) on the well-known test model (SMIB), Single Machine Infinite Bus. To test the effectiveness of the proposed method, Power System Stabilizer (PSS), Proportional-Integral-Derivative (PID-based PSS), and Fractional Order-PID (FOPID-based PSS) are implemented to control and ensure the system’s ability to return to a stable state in the presence of this fault. The achieved experimental outcomes have proven the superiority, and efficiency of the developed approach (WCMFO) in terms of damping the oscillations and reducing the overshot, with an improvement of 44% over the Water Cycle Algorithm (WCA), Moth-Flame Optimization (MFO), and Artificial Ecosystem Optimization (AEO). It is envisaged that the proposed method could be very useful in the design of a practical high-performance power system stabilizer. Full article
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20 pages, 1203 KiB  
Article
Application of Genetic Algorithm for Inter-Turn Short Circuit Detection in Stator Winding of Induction Motor
by Marcin Tomczyk, Ryszard Mielnik, Anna Plichta, Iwona Gołdasz and Maciej Sułowicz
Energies 2021, 14(24), 8523; https://doi.org/10.3390/en14248523 - 17 Dec 2021
Cited by 4 | Viewed by 2389
Abstract
This paper presents a new method of inter-turn short-circuit detection in cage induction motors. The method is based on experimental data recorded during load changes. Measured signals were analyzed using a genetic algorithm. This algorithm was next used in the diagnostics procedure. The [...] Read more.
This paper presents a new method of inter-turn short-circuit detection in cage induction motors. The method is based on experimental data recorded during load changes. Measured signals were analyzed using a genetic algorithm. This algorithm was next used in the diagnostics procedure. The correctness of fault detection was verified during experimental tests for various configurations of inter-turn short-circuits. The tests were run for several relevant diagnostic signals that contain symptoms of faults in an examined cage induction motor. The proposed algorithm of inter-turn short-circuit detection for various levels of winding damage and for various loads of the examined motor allows one to state the usefulness of this diagnostic method in normal industry conditions of motor exploitation. Full article
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17 pages, 3328 KiB  
Article
The Precise Temperature Measurement System with Compensation of Measuring Cable Influence
by Leszek Piechowski, Adam Muc and Jan Iwaszkiewicz
Energies 2021, 14(24), 8214; https://doi.org/10.3390/en14248214 - 7 Dec 2021
Cited by 7 | Viewed by 3109
Abstract
The article presents an active bridge system that enables the solution of a significant problem consisting in ensuring correct indications of temperature values in a wide measuring range for a Pt100 temperature sensor with properties defined by the standard (EN-60751 + A2). The [...] Read more.
The article presents an active bridge system that enables the solution of a significant problem consisting in ensuring correct indications of temperature values in a wide measuring range for a Pt100 temperature sensor with properties defined by the standard (EN-60751 + A2). The presented active bridge system combines the properties of the measuring amplifier with the stabilization of the current value in the branch in which the Pt100 sensor was placed. The article focuses on the comparison of the temperature measurement in a typical resistance bridge and the measurement made in the developed active bridge, which has also become the subject of a patent. For the performed tests, in which the correctness of the temperature measurement system operation was verified, and on the basis of the obtained results, the quality of temperature measurements was compared in a wide range of changes. Full article
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Graphical abstract

25 pages, 9629 KiB  
Article
Is It Possible to Obtain Benefits by Reducing the Contribution of the Digital Signal Processing Techniques to the Control of the Active Power Filter?
by Andrzej Szromba
Energies 2021, 14(19), 6031; https://doi.org/10.3390/en14196031 - 22 Sep 2021
Cited by 2 | Viewed by 1586
Abstract
This paper presents a simple yet efficient control method for active power filters that can be used to improve power quality. Applying this method can open the way towards limiting the hardware and computational expenditure, which are needed for control of the active [...] Read more.
This paper presents a simple yet efficient control method for active power filters that can be used to improve power quality. Applying this method can open the way towards limiting the hardware and computational expenditure, which are needed for control of the active filter, while maintaining its required performance. The method is based on the indirect approach of obtaining reference signals combined with the closed-loop current control technique. Monitoring of changes of energy stored in reactance elements of the active filter is the base for obtaining reference signals for compensation. The active filter can perform classical compensation and, additionally, can perform some extra functionality for managing of active power in the system. In particular, it can stabilize the supplying source power, enable energy exchange between loads connected on DC and AC sides of the active filter, and—in a case of generating loads—enable their energy storage and redistribution amongst consuming loads. The presented method can be useful for voltage-source as current-source inverter based active filters, and for DC systems as well as for AC single- or three-phase ones. Full article
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