Unit Commitment by Adaptive Particle Swarm Optimization (特集:平成18年〔電気学会〕電力・エネルギー部門大会) Unit Commitment by Adaptive Particle Swarm Optimization
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This paper presents an Adaptive Particle Swarm Optimization (APSO) for Unit Commitment (UC) problem. APSO reliably and accurately tracks a continuously changing solution. By analyzing the social model of standard PSO for the UC problem of variable size and load demand, adaptive criteria are applied on PSO parameters and the global best particle (knowledge) based on the diversity of fitness. In this proposed method, PSO parameters are automatically adjusted using Gaussian modification. To increase the knowledge, the global best particle is updated instead of a fixed one in each generation. To avoid the method to be frozen, idle particles are reset. The real velocity is digitized (0/1) by a logistic function for binary UC. Finally, the benchmark data and methods are used to show the effectiveness of the proposed method.
- IEEJ Transactions on Power and Energy
IEEJ Transactions on Power and Energy 127(1), 155-164, 2007-01-01
The Institute of Electrical Engineers of Japan