Utilizing Artificial Neural Network For the Regulation Of Electric Springs In Renewable Systems

Abstract

Now a days the research work is going on to improve the performance of electric springs (ESs) by integrating a current source inverter (CSI) and a neural network controller. A new ES configuration that includes CSIs is introduced to enhance ES functionality. This configuration is accompanied by a control strategy that involves direct current control and mitigation of harmonic distortion, like the methods used in active power filters (APFs). By transitioning from voltage source inverters (VSIs) to CSIs and integrating a neural network controller, a significant reduction in total harmonic distortion (THD) can be achieved. The paper presents two distinct control loops, each equipped with proportional-integral (PI) controllers. One loop is focused on regulating the Critical load voltage (CL voltage), while the other is specifically designed for reactive power compensation.