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Energies 2017, 10(7), 1013; doi:10.3390/en10071013

Optimal Power Flow Using Particle Swarm Optimization of Renewable Hybrid Distributed Generation

Electrical Engineering Department, College of Engineering, King Saud University, P.O. Box. 800, Riyadh 11421, Saudi Arabia
Electrical Engineering Department, Faculty of Energy Engineering, Aswan University, Aswan Governorate 81528, Egypt
Electrical Engineering Department, Mansoura University, Mansoura 35516, Egypt
Sustainable Energy Technology Center, King Saud University, Riyadh 11421, Saudi Arabia
Ecole Centrale de Lyon, University of Lyon, Ampere CNRS UMR 5005, 36 avenue Guy Collongue, Ecully 69134, France
Author to whom correspondence should be addressed.
Received: 16 May 2017 / Revised: 7 July 2017 / Accepted: 10 July 2017 / Published: 17 July 2017
(This article belongs to the Section Electrical Power and Energy System)
View Full-Text   |   Download PDF [2397 KB, uploaded 17 July 2017]   |  


The problem of voltage collapse in power systems due to increased loads can be solved by adding renewable energy sources like wind and photovoltaic (PV) to some bus-bars. This option can reduce the cost of the generated energy and increase the system efficiency and reliability. In this paper, a modified smart technique using particle swarm optimization (PSO) has been introduced to select the hourly optimal load flow with renewable distributed generation (DG) integration under different operating conditions in the 30-bus IEEE system. Solar PV and wind power plants have been introduced to selected buses to evaluate theirs benefits as DG. Different solar radiation and wind speeds for the Dammam site in Saudi Arabia have been used as an example to study the feasibility of renewable energy integration and its effect on power system operation. Sensitivity analysis to the load and the other input data has been carried out to predict the sensitivity of the results to any deviation in the input data of the system. The obtained results from the proposed system prove that using of renewable energy sources as a DG reduces the generation and operation cost of the overall power system. View Full-Text
Keywords: optimal power flow; renewable energy; wind energy; photovoltaic (PV); particle swarm optimization (PSO) optimal power flow; renewable energy; wind energy; photovoltaic (PV); particle swarm optimization (PSO)

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Khaled, U.; Eltamaly, A.M.; Beroual, A. Optimal Power Flow Using Particle Swarm Optimization of Renewable Hybrid Distributed Generation. Energies 2017, 10, 1013.

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