Automatic Generation Control Optimization in A Multi-Area Power System using Particle Swarm and Black Hole Algorithms

Abstract

The electricity industry in Iraq has struggled to keep up with the growing demand for power over the past few decades. The country's centralized power grid has historically had issues with frequency fluctuations and power loss in tie-line connections. In order to regulate the power variations between areas that were proportional to the 1% step load disturbance in the first area, the concept of Automatic Generation Regulate (AGC) was introduced at the Iraqi Meddle Area power system in this study. This operation took place in Iraq. It was also decided to introduce Load Frequency Control (LFC) in some areas so that the system's frequency could be managed and frequency deviations due to load variations could be prevented. Each of the six sections' frequency changes were managed using a Proportional Integral Derivative (PID) controller, bringing the overall frequency closer and closer to zero. In addition, the Particle Swarm Optimization (PSO) and Black Hole Optimization (BHO) techniques were used to finetune and optimize the parameters of the six PID controllers. The effectiveness of each of the two optimization strategies was compared and contrasted. Finally, the simulation outcomes proved how effective the suggested control strategies were.