Optimal Power Flow Using Particle Swarm Optimization of Renewable Hybrid Distributed Generation
AbstractThe 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
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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.
Khaled U, Eltamaly AM, Beroual A. Optimal Power Flow Using Particle Swarm Optimization of Renewable Hybrid Distributed Generation. Energies. 2017; 10(7):1013.Chicago/Turabian Style
Khaled, Usama; Eltamaly, Ali M.; Beroual, Abderrahmane. 2017. "Optimal Power Flow Using Particle Swarm Optimization of Renewable Hybrid Distributed Generation." Energies 10, no. 7: 1013.
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