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Synergy of adaptive super-twisting method (ASTM) and game-theory algorithm (GTA) for dynamic stability improvement of interconnected grids
Faculty
Engineering
Year:
2021
Type of Publication:
ZU Hosted
Pages:
Authors:
Ahmed Mohamed Othman Abdelmaksoud
Staff Zu Site
Abstract In Staff Site
Journal:
Electric Power Systems Research Elsevier
Volume:
Keywords :
Synergy , adaptive super-twisting method (ASTM) , game-theory algorithm
Abstract:
In this research work, a proposed technique of adaptive super-twisting method (ASTM) and game-theory algorithm (GTA) is presented. The proposed technique is applied to improve the dynamic stability of UPFC-based tidal energy resource. The impact of UPFC-based tidal energy resource on the power network is significantly recognized to support the demands supply and to enhance the dynamic performance. UPFC is able to control and enhance the power flow, voltage profile, power angle profile, and transmission lines loadability. The proposed technique has been optimally tuned to control the operational parameters of UPFC-based tidal energy resource. Both scenarios of single machine connected to infinite-bus grid, and multi-machine system are considered. The dynamic modelling of underlined system is done by d–q axis reference modelling. The analysis of steady-state stability is represented by the dynamic response specifications with stability discussion to evaluate the system performance. The simulations, including modelling, analysis and results, are carried out to confirm the entire stability of underlined systems. It has been confirmed the superb characteristics of proposed technique on interconnected UPFC-based tidal energy resource to power systems. The results of concerned scenarios have been emphasized that the proposed technique outperforms other well-established techniques. It is consolidated that UPFC-based tidal energy resource with proposed technique achieves significant performance and strengthened response. Therefore, the proposed solution can be offered as a favourable technique for enhancing the dynamic performance of power systems
Author Related Publications
Ahmed Mohamed Othman Abdelmaksoud, "Performance optimisation for novel green plug-energy economizer in micro-grids based on recent heuristic algorithm", IET Institution of Engineering and Technology IET Digital Library, 2016
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Ahmed Mohamed Othman Abdelmaksoud, "Optimal capacitor placement by Enhanced Bacterial Foraging Optimization (EBFO) with accurate thermal re-rating of critical cables", Elsevier, 2016
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Ahmed Mohamed Othman Abdelmaksoud, "Enhanced Backtracking Search Algorithm for Optimal Coordination of Directional Over-current Relays Including Distributed Generation", Taylor & Francis Group, 2016
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Ahmed Mohamed Othman Abdelmaksoud, "Optimal reconfiguration comprising voltage stability aspect using enhanced binary particle swarm optimization algorithm", Taylor & Francis, 2015
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Ahmed Mohamed Othman Abdelmaksoud, "Control Design for AC/DC Microgrid for Residential Home Cluster", Intelligent Control & Automation, 2015
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