Future University In Egypt (FUE)
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Altagamoa Al Khames, Main centre of town, end of 90th Street
New Cairo
Faculty of Engineering & Technology

Mohamed Abdallah Mahmoud Shaheen

Basic information

Name : Mohamed Abdallah Mahmoud Shaheen
Title: Assistant Lecturers


Certificate Major University Year
Masters Power and Electrical Machines Engineering Faculty of Engineering - Ain Shams University 2020
Bachelor Power and Electrical Machines Engineering department Ain Shams University - Faculty Of Engineering 2016

Researches /Publications

Optimal Power Flow of Power Systems Using Hybrid Firefly and Particle Swarm Optimization Technique - 01/1

Mohamed Abdallah Mahmoud Shaheen

H. M. Hasanien


This paper presents a new endeavor of using the Hybrid Firefly and Particle Swarm Optimization (HFPSO) technique in tackling the optimal power flow (OPF) problem for electric power networks. The fuel cost optimization represents the main target considering the system constraints. The decision variable of the OPF problem is chosen to be the generators output real power. The HFPSO technique is chosen to optimize the objective function and to determine the optimal solutions of the problem. Many IEEE test systems are included in this study to assure the soundness of the introduced technique such as the IEEE 14-bus, 30-bus, and 57-bus grids. To acquire a sensible outcome, actual load curves are taken into account during the examination. Simulation results are examined then investigated. They show the appropriateness and privilege of the presented HFPSO -based OPF problem over the genetic algorithm (GA) and the particle swarm optimization (PSO).

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Optimal Power Flow of Power Systems Including Distributed Generation Units Using Sunflower Optimization Algorithm - 01/0

Mohamed Abdallah Mahmoud Shaheen

H. M. Hasanien


This article introduces a new attempt of utilizing the sunflower optimization (SFO) algorithm in solving the problem of optimal power flow (OPF) in the field of power systems. The principle target is to optimize the generating units' fuel cost under the system constraints. At initial stage, the objective function is solved to find the optimal siting of Distributed Generation (DG) units within the system under study. Then, different scenarios are performed to solve the OPF problem including and excluding DG units. The generators' real output power defines the exploration field for the OPF problem. The SFO algorithm is used to minimize the fitness function and yields the best solutions of the problem. More than one electric grid is tested to check the validity of the proposed algorithm such as the IEEE 14-bus, and 30-bus networks. Simulations included different scenarios are implemented in these two networks. To obtain a realistic result, real daily load curve is considered in this study. The results of simulations are investigated and analyzed. Results confirm the flexibility, validation, and applicability of the introduced SFO-based OPF methodology when compared with the genetic algorithm.

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