Synchrophasor measurement with quadrature amplitude modulation based on artificial ecosystem optimization algorithm

With the increasing population, the number of loads connected to the grid is rising, and the diversity of these loads is expanding. Due to this change in the supply-demand balance, requirements arise concerning the monitoring and control of system and infrastructure components. Phasor measurement units enable the prevention of disruptive events in the system by comparing measurement data taken from specific points on the system. This study proposes an algorithm based on Quadrature Amplitude Modulation to ensure accurate and precise measurement of synchrophasors, which are crucial for ensuring power quality, efficiency, control, and protection systems in electrical systems. Firstly, the frequency values of the signals in the power system are estimated using the Artificial Ecosystem-based Optimization algorithm. Based on the estimated frequency value and using the Quadrature Amplitude Modulation method, the power signal is decomposed into its positive and negative components at this frequency value. Then, these components are filtered using a low-pass filter to eliminate high-frequency components, ensuring that only the components belonging to the frequency estimated by the optimization algorithm are obtained. The performance of this proposed method has been investigated for M and P classes defined in IEEE Std. C37.118.1 standard.