Advances in Computation and Mathematics in Electrical and Electronic Engineering

A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Mathematical Analysis".

Deadline for manuscript submissions: closed (30 December 2023) | Viewed by 5076

Special Issue Editors


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Guest Editor
Departamento de Engenharia de Energia e Automação Elétricas, Escola Politécnica da Universidade de São Paulo, Sao Paulo 05508-900, Brazil
Interests: electromagnetics; finite element analysis; finite difference methods; transmission line matrix methods; electromagnetic propagation; magnetic circuits; neural networks; power system analysis computing; data mining; electrokinetics; electromagnetic compatibility

E-Mail Website
Guest Editor
Departamento de Engenharia de Energia e Automação Elétricas, Escola Politécnica da Universidade de São Paulo, Sao Paulo 05508-900, Brazil
Interests: electromagnetics; finite element analysis; finite difference methods; transmission line matrix methods; electromagnetic propagation; magnetic circuits; neural networks; power system analysis computing; data mining; electrokinetics; electromagnetic compatibility

Special Issue Information

Dear Colleagues,  

The application of computational and mathematical advances in electrical engineering is considered one of the greatest challenges of science in this century.

The complexity issued from high non-linearity, new materials’ properties, multiphysical problems, and the multiplicity of multiphysical problems has demanded unlimited creativity from researchers.

This Special Issue of Axioms intends to showcase new paths that are emerging from academic environments that have accepted the challenge of modeling the most complex phenomena present in the electromagnetic devices of our times.

Thus, we invite you to submit the results of your research in this Special Issue that will mark a new phase in the simulation techniques of electromagnetic phenomena.

Prof. Dr. José R. Cardoso
Dr. Rooney R. A. Coelho
Guest Editors

Manuscript Submission Information

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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

  • finite element method
  • electromagnetic fields
  • eddy currents
  • magnetic fields
  • permanent magnets
  • optimization
  • mathematical models
  • computer simulation
  • numerical methods
  • electric machinery

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Published Papers (2 papers)

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Research

15 pages, 275 KiB  
Article
γ-Dual Codes over Finite Commutative Chain Rings
by Hai Q. Dinh, Hiep L. Thi and Roengchai Tansuchat
Axioms 2024, 13(10), 655; https://doi.org/10.3390/axioms13100655 - 24 Sep 2024
Viewed by 415
Abstract
In this article, the notion of γ-dual codes over finite chain rings is introduced as an extension of dual codes over finite chain rings. Various characteristics and properties of γ-dual codes over finite chain rings are explored. We provide both necessary [...] Read more.
In this article, the notion of γ-dual codes over finite chain rings is introduced as an extension of dual codes over finite chain rings. Various characteristics and properties of γ-dual codes over finite chain rings are explored. We provide both necessary and sufficient conditions for the existence of γ-self-dual codes over finite chain rings. Additionally, we investigate the γ-dual of skew ϕ-α-constacyclic codes over finite chain rings. Full article
25 pages, 8257 KiB  
Article
Efficient Optimization Algorithm-Based Demand-Side Management Program for Smart Grid Residential Load
by Ali M. Jasim, Basil H. Jasim, Bogdan-Constantin Neagu and Bilal Naji Alhasnawi
Axioms 2023, 12(1), 33; https://doi.org/10.3390/axioms12010033 - 27 Dec 2022
Cited by 27 | Viewed by 4148
Abstract
Incorporating demand-side management (DSM) into residential energy guarantees dynamic electricity management in the residential domain by allowing consumers to make early-informed decisions about their energy consumption. As a result, power companies can reduce peak demanded power and adjust load patterns rather than having [...] Read more.
Incorporating demand-side management (DSM) into residential energy guarantees dynamic electricity management in the residential domain by allowing consumers to make early-informed decisions about their energy consumption. As a result, power companies can reduce peak demanded power and adjust load patterns rather than having to build new production and transmission units. Consequently, reliability is enhanced, net operating costs are reduced, and carbon emissions are mitigated. DSM can be enhanced by incorporating a variety of optimization techniques to handle large-scale appliances with a wide range of power ratings. In this study, recent efficient algorithms such as the binary orientation search algorithm (BOSA), cockroach swarm optimization (CSO), and the sparrow search algorithm (SSA) were applied to DSM methodology for a residential community with a primary focus on decreasing peak energy consumption. Algorithm-based optimal DSM will ultimately increase the efficiency of the smart grid while simultaneously lowering the cost of electricity consumption. The proposed DSM methodology makes use of a load-shifting technique in this regard. In the proposed system, on-site renewable energy resources are used to avoid peaking of power plants and reduce electricity costs. The energy Internet-based ThingSpeak platform is adopted for real-time monitoring of overall energy expenditure and peak consumption. Peak demand, electricity cost, computation time, and robustness tests are compared to the genetic algorithm (GA). According to simulation results, the algorithms produce extremely similar results, but BOSA has a lower standard deviation (0.8) compared to the other algorithms (1.7 for SSA and 1.3 for CSOA), making it more robust and superior, in addition to minimizing cost (5438.98 cents of USD (mean value) and 16.3% savings). Full article
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