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Optimal reconfiguration for vulnerable radial smart grids under uncertain operating conditions
Faculty
Engineering
Year:
2021
Type of Publication:
ZU Hosted
Pages:
Authors:
Ahmed Mohamed Helmy Elsadiek
Staff Zu Site
Abstract In Staff Site
Journal:
Computers & Electrical Engineering Elsevier Ltd.
Volume:
Keywords :
Optimal reconfiguration , vulnerable radial smart grids
Abstract:
Modern smart grid prospects necessitate handling abnormal operating conditions besides conventional demands for improving power systems capabilities. Uncertain load and generation, and line outages during contingency conditions of electric power systems should be properly and efficiently dealt with. Lately, lockdown situations because of COVID-19 pandemic have greatly influenced energy demands in many areas in the World. Vulnerable operation of power networks, especially in either isolated microgrids or large-scale smart grids can be significantly avoided through proposing optimal reconfigurable network. In this paper, employing the distribution network (DN) reconfiguration is deeply studied for achieving fault-tolerance and fast recovery to reliable configurable DN in smart grids. Since radiality is among crucial properties of DN topology, searching for feasible configuration of DN is NP-hard optimization problem. Therefore, the recent Manta Ray Foraging Optimization (MRFO) is considered for solving such DN optimization instance. Performance of MRFO is examined against two common optimizers: the Particle Swarm Optimization (PSO) and the Grey Wolf Optimization (GWO). Different operating conditions for both the IEEE 33-bus and IEEE 85-bus systems are analysed using these optimization techniques. The goal is to search for feasible reconfigured DN with the minimum power losses and the optimal enhanced voltage profile. Simulation results reveal that the proposed MRFO approach provides efficient and outstanding behaviour in various operation scenarios. The efficiency and the robustness of the proposed MRFO approach are verified, the power loss reduction ratio ranges between 21% and 41% in different studied scenarios and adequate voltage profile enhancement is achieved.
Author Related Publications
Ahmed Mohamed Helmy Elsadiek, "Efficient and Sustainable Reconfiguration of Distribution Networks via Metaheuristic Optimization", IEEE, 2022
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Ahmed Mohamed Helmy Elsadiek, "LCMFO: An Improved Moth-Flame Algorithm for Combinatorial Optimization Problems", International Journal of Engineering and Technology, 2018
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Ahmed Mohamed Helmy Elsadiek, "Adaptive Sine Cosine Optimization Algorithm Integrated with Particle Swarm for Pairwise Local Sequence Alignment.", Elsevier, 2018
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Ahmed Mohamed Helmy Elsadiek, "Pairwise Global Sequence Alignment Using Sine-Cosine Optimization Algorithm.", Springer, Cham., 2018
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Ahmed Mohamed Helmy Elsadiek, "Two Layer Hybrid Scheme of IMO and PSO for Optimization of Local Aligner: COVID-19 as a Case Study", Springer, 2021
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Department Related Publications
Mira Magdy Sobhy Suliman, "COMPARISON BETWEEN HAAR WAVELET TRANSFORM, DCT AND A PROPOSED COLUMN-MEAN-METHOD BASED IRIS ENCODERS", جامعة الزقازيق-المجلة العلمية, 2014
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Ahmed Mohamed Helmy Elsadiek, "Efficient and Sustainable Reconfiguration of Distribution Networks via Metaheuristic Optimization", IEEE, 2022
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Sarah Khalil Mohamed Ibrahim, "Study of Climate Change Detection in North-East Africa Using Machine Learning and Satellite Data", IEEE, 2021
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Ibrahiem Elsayed Mohamed Zedan, "Improved subspace identication with prior information using constrained least-squares", IET, 2011
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