Electric spring control based on intelligent controller and cascade second-order generalized integrator phase locked loop

Abstract

Electric Spring (ES) is proposed to adapt the power consumption to the changes of power generation, so as to effectively alleviate the power quality problems caused by power imbalance in power grid and ensure the stable operation of key loads. Generally, the ES uses second-order eneralized integrator phase locked loop (SOGI-PLL) to track the voltage and frequency of power grid, and uses proportional-integral (PI) controller to stabilize the critical load (CL) voltage. However, for microgrids with large voltage and frequency fluctuations, the conventional ES control method is difficult to stabilize the CL voltage quickly and accurately. To solve this problem, an ES control method based on cascade second-order generalized integrator phase locked loop (CSOGI-PLL) and simplified brain emotional learning based intelligent controller (BELBIC) is proposed in this paper. By using the frequency adaptive tracking characteristic of CSOGI-PLL, the ability of ES to stabilize CL voltage in power grid with large frequency variation is improved. An ES control method based on simplified BELBIC is proposed, which uses its self-learning ability to automatically adjust control parameters and improve the control speed of ES. To verify the feasibility of the proposed scheme, the ES is modeled and simulated by MATLAB/Simulink and verified by dSPACE platform. The results show that the method is effective and feasible.