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Electronics
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Computational Intelligence Application in Electrical Engineering
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Computational Intelligence Application in Electrical Engineering

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 15041

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Dr. Marinko Barukčić

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Guest Editor
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, J.J.Strossmayer University Osijek, Trpimirova 2B, 31 000 Osijek, Croatia
Interests: computational intelligence techniques in power systems; power system modeling; and electromagnetic field analysis
Prof. Dr. Nebojša Raičević

E-Mail Website
Guest Editor
Faculty of Electronic Engineering, University of Niš, Aleksandra Medvedeva 14, 18000 Niš, Serbia
Interests: numerical methods in electromagnetic; hybrid boundary elements method; FEM; FDM; FDTD; optimization methods; power cable and cable accessories design; permanent magnets determination and design; skin effect
Prof. Dr. Vasilija Šarac

E-Mail Website
Guest Editor
Faculty of Electrical Engineering, University Goce Delchev, 2000 Štip, North Macedonia
Interests: modeling; simulation and optimization techniques in electrical machines and power electronics

Special Issue Information

Dear colleagues,

Computational intelligence (as a subset of artificial intelligence) has recently found increasing application in various fields of science (and beyond) and, thus, in electrical engineering. Thanks to the developments of computer hardware and computational intelligence (sometimes called soft computing) methods and techniques, computational intelligence enables solving current problems in areas of electrical engineering, such as smart grid, robotics, and industry 4.0. Moreover, it provides a new (improved) approach to solving some “classic” problems.

The main techniques of computational intelligence include fuzzy inference systems, artificial neural networks, and nature-based optimizations methods, which are widely used today in all fields of electrical engineering and for different purposes such as in modeling, control, and estimation of electrical machines, networks, electronic devices, electromagnetic calculations, and more. The application of computational intelligence methods in various segments of electrical engineering enables the successful handling of a large amount of data, uncertainties, and lack of information present in modern electrical systems and devices.

Computational intelligence techniques enable problem-solving in the case of a limited amount of measured data, more realistic modeling of physical systems, application of new control and estimation methods, and problems that cannot be solved in a classical, analytical way. Furthermore, computational intelligence methods allow the simultaneous use of several different computer tools in the so-called co-simulation setup for the implementation of simulations and calculations of complex modeled systems.

This Special Issue aims to give opportunities for presenting computational intelligence application in a wide spectrum of electrical engineering fields, from power systems and electrical machines to electronics, electromagnetic fields, and electromagnetic compatibility (EMC) calculations. Therefore, researchers are welcome to submit details of their research in the areas of modeling, estimation, optimization, control, and simulation in electrical engineering using computational intelligence techniques and methods.

Dr. Marinko Barukčić
Prof. Dr. Nebojša Raičević
Prof. Dr. Vasilija Šarac
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com 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 submissions that pass pre-check are 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. Electronics is an international peer-reviewed open access semimonthly 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 2400 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

  • computational intelligence
  • co-simulation
  • electromagnetic fields
  • electromagnetic compatibility
  • estimation
  • machine control
  • metaheuristic optimization
  • modeling
  • power system
  • simulation

Published Papers (8 papers)

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Editorial

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2 pages, 157 KiB  
Editorial
Computational Intelligence Application in Electrical Engineering
by Marinko Barukčić, Vasilija Šarac and Nebojša Raičević
Electronics 2022, 11(12), 1883; https://doi.org/10.3390/electronics11121883 - 15 Jun 2022
Viewed by 1165
Abstract
Nowadays, scientists and practitioners in the field of electrical engineering observe the increasing application of information technology, computers, and computing techniques [...] Full article
(This article belongs to the Special Issue Computational Intelligence Application in Electrical Engineering)

Research

Jump to: Editorial, Review

20 pages, 4511 KiB  
Article
Optimization of Fuzzy Controller for Predictive Current Control of Induction Machine
by Toni Varga, Tin Benšić, Marinko Barukčić and Vedrana Jerković Štil
Electronics 2022, 11(10), 1553; https://doi.org/10.3390/electronics11101553 - 12 May 2022
Cited by 3 | Viewed by 1570
Abstract
An optimization procedure for type 1 Takagi–Sugeno Fuzzy Logic Controller (FLC) parameter tuning is shown in this paper. Ant colony optimization is used to obtain the optimal controller parameters, and only a small amount of post-optimization parameter adjustment is needed. The choice of [...] Read more.
An optimization procedure for type 1 Takagi–Sugeno Fuzzy Logic Controller (FLC) parameter tuning is shown in this paper. Ant colony optimization is used to obtain the optimal controller parameters, and only a small amount of post-optimization parameter adjustment is needed. The choice of controller parameters is explained, along with the methodology behind the criterion for objective function value calculation. The optimized controller is implemented as an outer-loop speed controller for Predictive Current Control (PCC) of an induction machine. The performance of the proposed control method is compared with that of several other model predictive control methods. The results show a 55% decrease in speed tracking error and 74% decrease in torque overshoot. Full article
(This article belongs to the Special Issue Computational Intelligence Application in Electrical Engineering)
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22 pages, 10155 KiB  
Article
Parametric Analysis for Performance Optimization of Line-Start Synchronous Motor with Interior Asymmetric Permanent Magnet Array Rotor Topology
by Vasilija Sarac, Dragan Minovski and Peter Janiga
Electronics 2022, 11(4), 531; https://doi.org/10.3390/electronics11040531 - 10 Feb 2022
Cited by 6 | Viewed by 1548
Abstract
Line-start synchronous motors have attracted researchers’ interest as suitable replacements of asynchronous motors due to their high efficiency, which has been provoked by strict regulations regarding applicable efficiency classes of motors in the EU market. The research becomes even more challenging as it [...] Read more.
Line-start synchronous motors have attracted researchers’ interest as suitable replacements of asynchronous motors due to their high efficiency, which has been provoked by strict regulations regarding applicable efficiency classes of motors in the EU market. The research becomes even more challenging as it takes into consideration the diverse rotor topologies with different magnet locations for this type of motor. The rotor configuration with an interior asymmetric permanent magnet (PM) array rotor was chosen for analysis and optimization in this paper as this specific configuration is particularly challenging in terms of placing the magnets with adequate dimensions into the existing rotor of the asynchronous motor with a squirrel cage winding, in order simultaneously to obtain good operational characteristics such as high efficiency and power factor, good overloading capability and low material consumption. Therefore, an optometric analysis is performed in order to find the best configuration of the air gap length, magnet thickness, magnet width and number of conductors per slot, along with modifications of the rotor slot. The motor outer dimensions remained unchanged compared with the starting model of the line-start motor derived from the asynchronous motor, which is a product of the company Končar. The optimized model obtained higher efficiency, power factor and overloading capability than the starting model, along with good starting and synchronization capabilities. Full article
(This article belongs to the Special Issue Computational Intelligence Application in Electrical Engineering)
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20 pages, 14447 KiB  
Article
Exploiting the S-Iteration Process for Solving Power Flow Problems: Novel Algorithms and Comprehensive Analysis
by Marcos Tostado-Véliz, Salah Kamel, Ibrahim B. M. Taha and Francisco Jurado
Electronics 2021, 10(23), 3011; https://doi.org/10.3390/electronics10233011 - 02 Dec 2021
Cited by 2 | Viewed by 1349
Abstract
In recent studies, the competitiveness of the Newton-S-Iteration-Process (Newton-SIP) techniques to efficiently solve the Power Flow (PF) problems in both well and ill-conditioned systems has been highlighted, concluding that these methods may be suitable for industrial applications. This paper aims to tackle some [...] Read more.
In recent studies, the competitiveness of the Newton-S-Iteration-Process (Newton-SIP) techniques to efficiently solve the Power Flow (PF) problems in both well and ill-conditioned systems has been highlighted, concluding that these methods may be suitable for industrial applications. This paper aims to tackle some of the open topics brought for this kind of techniques. Different PF techniques are proposed based on the most recently developed Newton-SIP methods. In addition, convergence analysis and a comparative study of four different Newton-SIP methods PF techniques are presented. To check the features of considered PF techniques, several numerical experiments are carried out. Results show that the considered Newton-SIP techniques can achieve up to an eighth order of convergence and typically are more efficient and robust than the Newton–Raphson (NR) technique. Finally, it is shown that the overall performance of the considered PF techniques is strongly influenced by the values of parameters involved in the iterative procedure. Full article
(This article belongs to the Special Issue Computational Intelligence Application in Electrical Engineering)
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11 pages, 7689 KiB  
Article
Uncertainty Costs Optimization of Residential Solar Generators Considering Intraday Markets
by Julian Garcia-Guarin, David Alvarez and Sergio Rivera
Electronics 2021, 10(22), 2826; https://doi.org/10.3390/electronics10222826 - 17 Nov 2021
Cited by 3 | Viewed by 1253
Abstract
The uncertainty of solar generation and the bull market are unavoidable in energy dispatch. The purpose of this research is to validate an uncertainty cost function of residential photovoltaic energy in a real microgrid by varying the number of auctions in intraday markets. [...] Read more.
The uncertainty of solar generation and the bull market are unavoidable in energy dispatch. The purpose of this research is to validate an uncertainty cost function of residential photovoltaic energy in a real microgrid by varying the number of auctions in intraday markets. Therefore, the following procedure is proposed. First, the variability of photovoltaic generation is quantified through Monte Carlo simulations. Second, a statistical function calculates the variability costs of photovoltaic generation. Third, the uncertainty costs are estimated by varying intraday auction markets. Other complementary services are added to the network, such as battery exchange stations for electric vehicles, demand response loads, market power restrictions, and energy storage systems, which are estimated as total costs in an index ranking. The total costs are optimized in a benchmark microgrid and take complimentary services as a black box. Only the uncertainty costs of residential solar generators are discriminated. The main findings were that (1) the uncertainty costs have an error of less than 0.0168% compared to the Monte Carlo simulations and that (2) the uncertainty costs of solar generation are reduced with a decreasing trend to a more significant number of auction markets in intraday markets. Full article
(This article belongs to the Special Issue Computational Intelligence Application in Electrical Engineering)
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23 pages, 4465 KiB  
Article
An Adaptive Protection Scheme for Coordination of Distance and Directional Overcurrent Relays in Distribution Systems Based on a Modified School-Based Optimizer
by Mohamed Abdelhamid, Salah Kamel, Ahmed Korashy, Marcos Tostado-Véliz, Fahd A Banakhr and Mohamed I. Mosaad
Electronics 2021, 10(21), 2628; https://doi.org/10.3390/electronics10212628 - 27 Oct 2021
Cited by 11 | Viewed by 1904
Abstract
This paper presents an adaptive protection scheme (APS) for solving the coordination problem that deals with coordination directional overcurrent relays (DOCRs) and distance relays second zone time, in relation to coordination with DOCRs. The coordination problem becomes more complex with the impact of [...] Read more.
This paper presents an adaptive protection scheme (APS) for solving the coordination problem that deals with coordination directional overcurrent relays (DOCRs) and distance relays second zone time, in relation to coordination with DOCRs. The coordination problem becomes more complex with the impact of renewable energy sources (RES) when added to the distribution grid. This leads to a change in the grid topology, caused by the on/off states of the distribution generators (DG). The frequency of topological changes in distribution grids poses a challenge to the power system’s protection components. The change in the state of DGs leads to malfunction in reliability and miscoordination between protection relays, since that causes a direct effect to the short circuit currents. This paper used the school-based optimization (SBO) algorithm, which simulates the educational process, in order to deal with coordination problems. That algorithm is modified (MSBO) by modified both learning and teaching processes. The IEEE 8-bus test system and IEEE 14-bus distribution network are used to validate the proposed coordination system’s effectiveness when dealing with the coordination process between distance and DOCRs, at both the near- and far-end in the typical topological grid and with DGs in working order. Full article
(This article belongs to the Special Issue Computational Intelligence Application in Electrical Engineering)
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25 pages, 6092 KiB  
Article
Co-Simulation Framework for Optimal Allocation and Power Management of DGs in Power Distribution Networks Based on Computational Intelligence Techniques
by Marinko Barukčić, Toni Varga, Vedrana Jerković Štil and Tin Benšić
Electronics 2021, 10(14), 1648; https://doi.org/10.3390/electronics10141648 - 10 Jul 2021
Cited by 6 | Viewed by 1710
Abstract
The paper researches the impact of the input data resolution on the solution of optimal allocation and power management of controllable and non-controllable renewable energy sources distributed generation in the distribution power system. Computational intelligence techniques and co-simulation approach are used, aiming at [...] Read more.
The paper researches the impact of the input data resolution on the solution of optimal allocation and power management of controllable and non-controllable renewable energy sources distributed generation in the distribution power system. Computational intelligence techniques and co-simulation approach are used, aiming at more realistic system modeling and solving the complex optimization problem. The optimization problem considers the optimal allocation of all distributed generations and the optimal power control of controllable distributed generations. The co-simulation setup employs a tool for power system analysis and a metaheuristic optimizer to solve the optimization problem. Three different resolutions of input data (generation and load profiles) are used: hourly, daily, and monthly averages over one year. An artificial neural network is used to estimate the optimal output of controllable distributed generations and thus significantly decrease the dimensionality of the optimization problem. The proposed procedure is applied on a 13 node test feeder proposed by the Institute of Electrical and Electronics Engineers. The obtained results show a huge impact of the input data resolution on the optimal allocation of distributed generations. Applying the proposed approach, the energy losses are decreased by over 50–70% by the optimal allocation and control of distributed generations depending on the tested network. Full article
(This article belongs to the Special Issue Computational Intelligence Application in Electrical Engineering)
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Review

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38 pages, 2123 KiB  
Review
A Survey on Computational Intelligence Applications in Distribution Network Optimization
by Marko Vukobratović, Predrag Marić, Goran Horvat, Zoran Balkić and Stjepan Sučić
Electronics 2021, 10(11), 1247; https://doi.org/10.3390/electronics10111247 - 24 May 2021
Cited by 3 | Viewed by 2492
Abstract
This paper aims to present carefully selected scientific papers that have pushed the boundaries in the application of advanced computational intelligence–based methods in power engineering, mainly in optimal power system management. Contemporary development of the Smart Grid and detailed framework for power grid [...] Read more.
This paper aims to present carefully selected scientific papers that have pushed the boundaries in the application of advanced computational intelligence–based methods in power engineering, mainly in optimal power system management. Contemporary development of the Smart Grid and detailed framework for power grid digitalization enabled the real and efficient application of advanced optimization algorithms presented in this paper. Papers that are not directly related to Smart Grid management are also considered, since they solve the partial challenges of planning and development with metaheuristic procedures, and according to the authors, they are highly applicable and represent a fundamental starting point for wider application. This paper covers papers and research whose results are reproducible and can be realized in production-grade software. The emphasis of the paper is on the considerate and impartial way of providing a concise overview of the methods for solving technical challenges within the accepted Smart Grid architecture. The paper is the result of many years of research and commitment to this field and represents the foundation for present research and development. Full article
(This article belongs to the Special Issue Computational Intelligence Application in Electrical Engineering)
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