DC Microgrid Enhancement via Chaos Game Optimization Algorithm

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Publicado en:Processes vol. 13, no. 7 (2025), p. 2042-2070
Autor principal: Heikal, Abdelrahman S
Otros Autores: Diaaeldin Ibrahim Mohamed, Badra, Niveen M, Attia, Mahmoud A, Badr, Ahmed O, Omar Othman A. M., EL-Ebiary, Ahmed H, Kang, Hyun-Soo
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100 1 |a Heikal, Abdelrahman S  |u Engineering Physics and Mathematics Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt; 2100977@eng.asu.edu.eg (A.S.H.); niveen_badra@eng.asu.edu.eg (N.M.B.); osman_ahmed@eng.asu.edu.eg (O.A.M.O.) 
245 1 |a DC Microgrid Enhancement via Chaos Game Optimization Algorithm 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a Microgrids are increasingly being adopted as alternatives to traditional power transmission networks, necessitating improved performance strategies. Various mathematical optimization techniques are used to determine optimal controller parameters for these systems. These optimization methods can generally be categorized into natural, biological, and engineering-based approaches. In this research, the authors evaluated and compared several optimization techniques to enhance the secondary controller of DC microgrids, focusing on reducing operating time and minimizing error rates. Optimization tools were utilized to identify the optimal gain control parameters, aiming to achieve the best possible system performance. The enhanced controller response enables quicker recovery to steady-state conditions during sudden disturbances. The root-mean-square error (RMSE) served as a performance metric, with the proposed approach achieving a 15% reduction in RMSE compared to previous models. This improvement contributes to faster response times and lower energy consumption in microgrid operation. 
610 4 |a National Institute of Standards & Technology 
653 |a Software 
653 |a Parameter identification 
653 |a Distributed generation 
653 |a Mathematical analysis 
653 |a Infrastructure 
653 |a Energy industry 
653 |a Communication 
653 |a Emissions 
653 |a Optimization techniques 
653 |a Root-mean-square errors 
653 |a Electricity generation 
653 |a Renewable resources 
653 |a Electric power 
653 |a Optimization 
653 |a Systems stability 
653 |a Energy storage 
653 |a Energy resources 
653 |a Energy consumption 
653 |a Controllers 
653 |a Cost control 
653 |a Emission standards 
653 |a Optimization algorithms 
653 |a Mathematical models 
653 |a Efficiency 
700 1 |a Diaaeldin Ibrahim Mohamed  |u Engineering Physics and Mathematics Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt; 2100977@eng.asu.edu.eg (A.S.H.); niveen_badra@eng.asu.edu.eg (N.M.B.); osman_ahmed@eng.asu.edu.eg (O.A.M.O.) 
700 1 |a Badra, Niveen M  |u Engineering Physics and Mathematics Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt; 2100977@eng.asu.edu.eg (A.S.H.); niveen_badra@eng.asu.edu.eg (N.M.B.); osman_ahmed@eng.asu.edu.eg (O.A.M.O.) 
700 1 |a Attia, Mahmoud A  |u Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt; ahmed.badr@eng.asu.edu.eg (A.O.B.); ahmed.haitham@eng.asu.edu.eg (A.H.E.-E.) 
700 1 |a Badr, Ahmed O  |u Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt; ahmed.badr@eng.asu.edu.eg (A.O.B.); ahmed.haitham@eng.asu.edu.eg (A.H.E.-E.) 
700 1 |a Omar Othman A. M.  |u Engineering Physics and Mathematics Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt; 2100977@eng.asu.edu.eg (A.S.H.); niveen_badra@eng.asu.edu.eg (N.M.B.); osman_ahmed@eng.asu.edu.eg (O.A.M.O.) 
700 1 |a EL-Ebiary, Ahmed H  |u Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt; ahmed.badr@eng.asu.edu.eg (A.O.B.); ahmed.haitham@eng.asu.edu.eg (A.H.E.-E.) 
700 1 |a Kang, Hyun-Soo  |u School of Information and Communication Engineering, College of Electrical and Computer Engineering, Chungbuk National University, Cheongju 28644, Republic of Korea 
773 0 |t Processes  |g vol. 13, no. 7 (2025), p. 2042-2070 
786 0 |d ProQuest  |t Materials Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3233241577/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
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