Voltage Control Based on Fuzzy Adaptive Particle Swarm Optimization
Comparison between traditional and Various particle swarm optimization techniques
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Keeping an acceptable voltage profile at the system buses is a challenging and a system-wide task. Voltage-control is rooted in rescheduling of the reactive power flow in the lines of power system. Despite the fact that many voltage-control techniques are available to electric power system operators, these systems around the world have been subjected to voltage instability problems and voltage collapses that cause in many occasions complete system breakdowns. In this Book, a new voltage control methodology is presented, which is originated on the use of multi- objective function based on fuzzy...
Keeping an acceptable voltage profile at the system buses is a challenging and a system-wide task. Voltage-control is rooted in rescheduling of the reactive power flow in the lines of power system. Despite the fact that many voltage-control techniques are available to electric power system operators, these systems around the world have been subjected to voltage instability problems and voltage collapses that cause in many occasions complete system breakdowns. In this Book, a new voltage control methodology is presented, which is originated on the use of multi- objective function based on fuzzy set theory and adaptive particle swarm optimization. This methodology is applied to get a solution to the mathematical model that represents the voltage- control problem of a power system. The purpose is to ensure acceptable voltage profile and to minimize both the voltage deviation and the real power loss. The IEEE 30-Bus system model is used to employ the suggested technique to the mathematical model built for the new voltage-control methodology using Matlab code. The findings will be documented and compared with other voltage-control strategies.
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