A High-Efficiency Dual Boost Converter Approach to PV-Powered DSTATCOM for Reactive Power Compensation

The growing demand for energy highlights the need of power system stability, which guarantees systems operate reliably in face of failures, load fluctuations, voltage variations, harmonics, and frequency deviations. Custom power devices are critical for managing reactive power and improving power quality in distribution networks. This presentation will primarily address the integration of DSTATCOM into three phase distribution systems. The DSTATCOM’s DC-link is powered by a separate energy source, usually a solar cell, and its output is enhanced by a Dual Boost Converter (DBC) to boost performance. This structure is designed to effectively address power quality issues inside the distribution system. Additionally, DSTATCOM is connected with the Artificial Neural Network (ANN) optimized firefly algorithm is proposed as a replacement for the traditional controllers. The control of output compensating currents is achieved through the application of a feed forward neural network. Proposed model is implemented using MATLAB/Simulink and results shows that DBC attains highest efficiency of 92.42% and reduced THD of 0.62%. Also, firefly optimized ANN controller attains a lowest settling time of 0.6 s.