Collaborative self-control of voltage stability for parallel inverters in microgrid based on DNN-SFO

The microgrid parallel inverter system relies on mode switching control strategy to eliminate blind spots. However, this master-slave control behavior is affected by various factors and has low synergy and stability. It is necessary to design a robust and adaptive control strategy to ensure that the microgrid parallel inverter system can maintain stability under various operating voltage conditions. Therefore, a collaborative self-control method for voltage stability of parallel inverters in microgrids based on DNN-SFO is proposed. By calculating the optimal switching angle of the microgrid parallel inverter, adjusting the output voltage frequency of the microgrid parallel inverter, and ensuring the output voltage and current waveform of the microgrid parallel inverter. Applying DNN to predict the output voltage frequency of microgrid parallel inverters, improving the stability and power quality of microgrid parallel inverters, using SFO to find the optimal combination of control variables for output voltage and current waveforms, improving the overall performance of microgrid parallel inverters, and achieving coordinated self-control of voltage stability of microgrid parallel inverters. The experimental results show that the proposed method has a good voltage self-control effect on microgrid parallel inverters, with synergy and stability, and can effectively improve the voltage stability and synergy self-control performance of microgrid parallel inverters.