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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:
Hytham Saad Mohamed Ramadan
Staff Zu Site
Abstract In Staff Site
Journal:
Computers & Electrical Engineering ELSEVIER-Computers & Electrical Engineering
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
Hytham Saad Mohamed Ramadan, "Efficient and Sustainable Reconfiguration of Distribution Networks via Metaheuristic Optimization", IEEE, 2022
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Hytham Saad Mohamed Ramadan, "Efficient experimental energy management operating for FC/battery/SC vehicles via hybrid Artificial Neural Networks-Passivity Based Control", ELSEVIER, 2021
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Hytham Saad Mohamed Ramadan, "Hydrogen storage technologies for stationary and mobile applications: Review, analysis and perspectives", ELSEVIER, 2021
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Hytham Saad Mohamed Ramadan, "Efficient metaheuristic utopia-based multi-objective solutions of optimal battery-mix storage for microgrids", ELSEVIER, 2021
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Hytham Saad Mohamed Ramadan, "Optimal reconfiguration for vulnerable radial smart grids under uncertain operating conditions", ELSEVIER, 2021
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Department Related Publications
Mahdy Mohamed Mahdy Mohamed Elareny, "Mahdi M. M. El - Arini Environmental Economic Dispatching Based on Artificial Networks", لايوجد, 1900
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Mahdy Mohamed Mahdy Mohamed Elareny, "Mahdi M. M. El - Arini An Efficient Second Order Fast Load Flow Method in Rectangular Coordinates", لايوجد, 1900
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