Computational Intelligence Application in Electrical Engineering
1
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
2
Faculty of Electrical Engineering, University Goce Delchev, 2000 Stip, North Macedonia
3
Faculty of Electronic Engineering, University of Nis, Aleksandra Medvedeva 14, 18000 Nis, Serbia
*
Author to whom correspondence should be addressed.
Electronics 2022, 11(12), 1883; https://doi.org/10.3390/electronics11121883
Submission received: 10 June 2022
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Accepted: 14 June 2022
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Published: 15 June 2022
(This article belongs to the Special Issue Computational Intelligence Application in Electrical Engineering)
Nowadays, scientists and practitioners in the field of electrical engineering observe the increasing application of information technology, computers, and computing techniques. Modern concepts such as smart power grids and smart industries require a multidisciplinary approach and a close connection and synergistic application of IT and computer hardware and software in all areas of electrical engineering. In addition, the application of advanced computational tools is essential for the simulation and modeling of complex electrical systems and devices. The application of computational tools based on numerical mathematical methods has enabled practical calculations in the field of electromagnetic field theory with more realistic models of the devices.
The Special Issue “Computational Intelligence Application in Electrical Engineering” aims to promote the techniques and procedures of computational intelligence for modeling, optimization, simulation, and computation in various fields of electrical engineering. Thanks to the authors’ interest in this Special Issue, seven research and review articles were published out of the ten submitted papers.
In the review article [1], the authors provide an overview of the application of computational intelligence methods in power engineering, in particular, the application of computational intelligence in the field of power grids. The article addresses various goals of applying computational intelligence in the area of smart power grids, such as optimal scheduling of distributed generation and optimization of smart power grid management. The remaining published articles are original research papers.
The authors of [2] have proposed a co-simulation approach to solve the very complex optimization problem of optimal allocation of distributed generation assets and power control of controllable distributed generation assets. The optimization problem is of black-box type, and an artificial neural network is proposed for the distribution of the output power of the distributed generation units.
Paper [3] presents the application of a metaheuristic optimization method for optimal coordination of directional overcurrent relays and distance relays in the second zone. The authors developed a modified school-based optimization method as an improvement to the basic version of this optimizer.
In [4], the uncertainty in the scheduling of electricity distribution generation is presented considering the electricity market. The modeling and impact of different uncertainties (in the intensity of primary energy sources as well as in the energy price) at the intraday market level was developed and proposed here.
The improved method for power flow calculations in power systems was developed in [5]. The proposed method uses the Newton- S-Iteration Process and shows advantages over classical power flow methods especially for ill-conditioned systems.
The authors of [6] have developed a procedure for the analysis and optimization of a synchronous motor with line start and asymmetric permanent magnet arrangement in the rotor. The method includes a finite element analysis of the motor using a simulation program. The optimization method is based on a parametric analysis of the steady state and transients of the motor.
The last published article (in chronological order) [7] in the Special Issue deals with the optimal control of induction motors. In the article, the application of a fuzzy controller for the predictive current control of an induction motor was developed. It also presents the optimization of the parameters of the fuzzy controller using a co-simulation approach and a metaheuristic optimization method.
We would like to thank all the authors for their interest and contributions to this Special Issue. We thank the reviewers who contributed to the quality of the presentation of the articles with their constructive comments and suggestions. We thank the editorial board of the journal Electronics for the invitation and the opportunity to edit this special issue. A big thank to the editorial board for taking care of the whole process and making sure that everything was ready on time. Our special thanks to Ms. Hebbe Tian, the assistant editor of the Special Issue, for her kindness and timely completion of all the steps in this Special Issue.
Funding
This research received no external funding.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Vukobratović, M.; Marić, P.; Horvat, G.; Balkić, Z.; Sučić, S. A Survey on Computational Intelligence Applications in Distribution Network Optimization. Electronics 2021, 10, 1247. [Google Scholar] [CrossRef]
- Barukčić, M.; Varga, T.; Štil, V.J.; Benšić, T. Co-Simulation Framework for Optimal Allocation and Power Management of DGs in Power Distribution Networks Based on Computational Intelligence Techniques. Electronics 2021, 10, 1648. [Google Scholar] [CrossRef]
- Abdelhamid, M.; Kamel, S.; Korashy, A.; Tostado-Véliz, M.; Banakhr, F.A.; Mosaad, M.I. An Adaptive Protection Scheme for Coordination of Distance and Directional Overcurrent Relays in Distribution Systems Based on a Modified School-Based Optimizer. Electronics 2021, 10, 2628. [Google Scholar] [CrossRef]
- Garcia-Guarin, J.; Alvarez, D.; Rivera, S. Uncertainty Costs Optimization of Residential Solar Generators Considering Intraday Markets. Electronics 2021, 10, 2826. [Google Scholar] [CrossRef]
- Tostado-Véliz, M.; Kamel, S.; Taha, I.B.M.; Jurado, F. Exploiting the S-Iteration Process for Solving Power Flow Problems: Novel Algorithms and Comprehensive Analysis. Electronics 2021, 10, 3011. [Google Scholar] [CrossRef]
- Sarac, V.; Minovski, D.; Janiga, P. Parametric Analysis for Performance Optimization of Line-Start Synchronous Motor with Interior Asymmetric Permanent Magnet Array Rotor Topology. Electronics 2022, 11, 531. [Google Scholar] [CrossRef]
- Varga, T.; Benšić, T.; Barukčić, M.; Štil, V.J. Optimization of Fuzzy Controller for Predictive Current Control of Induction Machine. Electronics 2022, 11, 1553. [Google Scholar] [CrossRef]
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MDPI and ACS Style
Barukčić, M.; Šarac, V.; Raičević, N. Computational Intelligence Application in Electrical Engineering. Electronics 2022, 11, 1883. https://doi.org/10.3390/electronics11121883
AMA Style
Barukčić M, Šarac V, Raičević N. Computational Intelligence Application in Electrical Engineering. Electronics. 2022; 11(12):1883. https://doi.org/10.3390/electronics11121883
Chicago/Turabian StyleBarukčić, Marinko, Vasilija Šarac, and Nebojša Raičević. 2022. "Computational Intelligence Application in Electrical Engineering" Electronics 11, no. 12: 1883. https://doi.org/10.3390/electronics11121883
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