Open AccessOptimal power flow using particle swarm optimization for IEEE 30 bus
Author(s) -
Kukuh Widarsono,
Farid Dwi Murdianto,
Mohammad Mohammad,
Ali Mustofa
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1595/1/012033
Subject(s) - particle swarm optimization , mathematical optimization , population , generator (circuit theory) , power (physics) , value (mathematics) , convergence (economics) , computer science , control theory (sociology) , mathematics , physics , demography , control (management) , quantum mechanics , artificial intelligence , sociology , economics , economic growth , machine learning
Particle Swarm Optimization (PSO) is one of the algorithm intends to get minimum or maximum value of a function, based on the behavior of a bird flocks. In this research, PSO has implemented to overcome the problem of power flow in the plant. The search for solutions is carried out by a population of several individuals. Population is the representation of a generator in electric power distribution system. The plant used in this study is IEEE 30 bus. There are 6 plants which must be optimized. PSO generate one power value in each generator as a reference value. This value will be shifted by increasing or reducing it, until the optimal generation value is found for all plants. The result of the experiment proved that PSO is able to solve power flow optimization problems on IEEE 30 bus, indicated by the individual rate in each population, the rate of fitness and the rate of generation can reach its convergence. This convergence rate is strongly influenced by the value of Velocity on the PSO. With PSO method, the IEEE 30 bus system can generate optimal power of 193 MW.