DRAG & AVERSION PARTICLE SWARM OPTIMIZATION ALGORITHM FOR REDUCTION OF REAL POWER LOSS

K. Lenin

doi:10.29121/granthaalayah.v5.i11.2017.2344

Authors

Dr.K.Lenin Professor,Department of EEE, Prasad V.Potluri Siddhartha Institute of Technology,Kanuru, Vijayawada, Andhra Pradesh -520007, India

DOI:

https://doi.org/10.29121/granthaalayah.v5.i11.2017.2344

Keywords:

Reactive Power Optimization, Real Power Loss, Particle Swarm Optimization, Drag, Aversion

Abstract [English]

This paper projects Drag & Aversion Particle Swarm Optimization (DAPSO) algorithm is applied to solve optimal reactive power problem. In DAPSO the idea of decreasing and increasing diversity operators used to control the population into the basic Particle Swarm Optimization (PSO) model. The modified model uses a diversity measure to have the algorithm alternate between exploring and exploiting behavior. The results show that both Drag & Aversion Particle Swarm Optimization (DAPSO) prevents premature convergence to enhanced level but still keeps a rapid convergence. Proposed Drag & Aversion Particle Swarm Optimization (DAPSO) has been tested in standard IEEE 118 & practical 191 bus test systems. Real power loss has been considerably reduced and voltage profiles are within the limits.

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