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Format: MS WORD
| Chapters: 1-5
| Pages: 85
LINE LOSSES MINIMIZATION IN ELECTRICAL POWER NETWORK USING PARTICLE SWARM OPTIMIZATION
ABSTRACT
This study examines how line losses can be minimized using particle swarm optimization. Three research objective were formulated to give direction towards this work, this study describes theoretical and practical issues concerning line losses minimization in electric power networks using Particle Swarm Optimization. The study utilized FACTS devices such as STATCOM for voltage control and active power losses optimization. The idea and development with applying STATCOM for the optimization is presented. The behavior of a PSO swarm is not well understood in terms of how it affects actual optimization performance, especially for higher-dimensional search spaces and optimization problems that maybe discontinuous, noisy and time-varying. To counter these, there is need to adopt the use of the accelerated particle swarm optimization (APSO) which is standardized and easy to understand by even lay persons PSO is a vast field and this has led to the development of numerous variants for basic PSO algorithm. Therefore there is a need for the use of a well-known, strictly-defined standard algorithm that provides a valuable point of comparison which can be used throughout the field of research to test new advances. The latest standard PSO 2011 (SPSO 2011) is highly recommended.
ABSTRACT
This study examines how line losses can be minimized using particle swarm optimization. Three research objective were formulated to give direction towards this work, this study describes theoretical and practical issues concerning line losses minimization in electric power networks using Particle Swarm Optimization. The study utilized FACTS devices such as STATCOM for voltage control and active power losses optimization. The idea and development with applying STATCOM for the optimization is presented. The behavior of a PSO swarm is not well understood in terms of how it affects actual optimization performance, especially for higher-dimensional search spaces and optimization problems that maybe discontinuous, noisy and time-varying. To counter these, there is need to adopt the use of the accelerated particle swarm optimization (APSO) which is standardized and easy to understand by even lay persons PSO is a vast field and this has led to the development of numerous variants for basic PSO algorithm. Therefore there is a need for the use of a well-known, strictly-defined standard algorithm that provides a valuable point of comparison which can be used throughout the field of research to test new advances. The latest standard PSO 2011 (SPSO 2011) is highly recommended.
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