Minimization of Reactive Power Losses with FACTS with the application various optimization techniques

ENG. JOEL SUTTER, PROF. JOHN NDERU, DR. ENG. ARIEL MUTEGI

Augmentation, Artificial intelligence, Bus, Normalize, Genetic algorithm grid capacity reactive control.

This paper work presents a novel individual and Hybrid MGA and IGWO was utilized to develop FACTS-controlled optimization model for improvement of bus voltage profiles. The algorithm simultaneously solved the objective problem and tunes as it searches for FACTS location and sizes. Objective function constrained optimal power flow (CPF) with FACTS devices for TTC within real and reactive power generation limits, voltage limits, line flow limits, and FACTS devices operation limits. Thyristor-Controlled Series Capacitor (TCSC) parameters has been optimized for the research and the work has been successfully carried on MATLAB platform using IEEE 30-bus test bus systems. Power system processes and parameters can be optimized using artificial intelligence techniques like artificial neural networks and genetic algorithm alongside power electronics based Flexible AC Transmission Systems (FACTS) devices. FACTS normalize voltage or control the power that is either added into or absorbed from the system. They enhance the overall grid capacity and performance. They also increase the dependability and efficiency of power systems. Apart from alleviating power transients, FACTS provide greater system real and reactive control augmentation.