Application of Meta-Heuristic Techniques for Optimal Load Shedding in Islanded Distribution Network with High Penetration of Solar PV GenerationReportar como inadecuado


Application of Meta-Heuristic Techniques for Optimal Load Shedding in Islanded Distribution Network with High Penetration of Solar PV Generation


Application of Meta-Heuristic Techniques for Optimal Load Shedding in Islanded Distribution Network with High Penetration of Solar PV Generation - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

1

Department of Electrical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia

2

Power Electronics and Renewable Energy Research Laboratory PEARL, Department of Electrical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia





*

Author to whom correspondence should be addressed.



Academic Editor: Tapas Mallick

Abstract Recently, several environmental problems are beginning to affect all aspects of life. For this reason, many governments and international agencies have expressed great interest in using more renewable energy sources RESs. However, integrating more RESs with distribution networks resulted in several critical problems vis-à-vis the frequency stability, which might lead to a complete blackout if not properly treated. Therefore, this paper proposed a new Under Frequency Load Shedding UFLS scheme for islanding distribution network. This scheme uses three meta-heuristics techniques, binary evolutionary programming BEP, Binary genetic algorithm BGA, and Binary particle swarm optimization BPSO, to determine the optimal combination of loads that needs to be shed from the islanded distribution network. Compared with existing UFLS schemes using fixed priority loads, the proposed scheme has the ability to restore the network frequency without any overshooting. Furthermore, in terms of execution time, the simulation results show that the BEP technique is fast enough to shed the optimal combination of loads compared with BGA and BPSO techniques. View Full-Text

Keywords: Distribution Generation DG; Renewable Energy Resources RESs; Under Frequency Load Shedding UFLS; Binary Evolutionary Programming BEP; Binary Genetic Algorithm BGA; Binary Particle Swarm Optimization BPSO Distribution Generation DG; Renewable Energy Resources RESs; Under Frequency Load Shedding UFLS; Binary Evolutionary Programming BEP; Binary Genetic Algorithm BGA; Binary Particle Swarm Optimization BPSO





Autor: Mohammad Dreidy 1, Hazlie Mokhlis 1,* and Saad Mekhilef 2

Fuente: http://mdpi.com/



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