An Intelligent Frequency Control Scheme for Inverting Station in High Voltage Direct Current Transmission System

Power system stability is crucial for the reliable and efficient operation of electrical grids. One of the key factors affecting power system stability is the frequency of the alternating current (AC) system while connected with High Voltage Direct Current (HVDC) transmission system. Changes in load demand can lead to frequency deviations, which can have detrimental effects on the stability and performance of the power system. Frequency should therefore be controlled within predefined limits in order to prevent unexpected disturbances that may cause problems to connected loads or even cause the entire system to fail. A broad simulation model of the HVDC transmission system is developed using MATLAB software to evaluate the effectiveness of the proposed controllers such as Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN), and optimization of Proportional-Integral-Derivative (PID) controller using Particle Swarm Optimization (PSO) based control strategy for addressing the frequency instability problems. To assess how well the ANFIS, ANN, and PID-PSO controller controls frequency in HVDC transmission system, several situations were simulated, including load disturbances and changes in operational circumstances. The result reveals that the ANN controller performs more accurate results in HVDC transmission system than the other proposed control and, displaying its capacity to successfully reduce frequency deviations and maintained a controlled frequency 50 Hz. Adopted method suggested the easy integration of HVDC with AC grid and enhances the system power quality and stability.