Optimization of Voltage Dynamic Performance at Inverter Output with Machine Learning and Intelligent Virtual Impedance

Abstract

With the continuous improvement of industrial production and manufacturing level, all kinds of equipment are developing in the direction of refinement and precision, especially the equipment manufacturing industry such as automobile manufacturing, equipment, integrated circuits, chip manufacturing, and other semiconductor industries. An intelligent virtual resistance control strategy based on machine research is proposed for rational power distribution and cycle suppression when multiple inverters are operated in parallel in low-voltage microgrids. Based on this, the control strategy of temporary power reduction of inverters is improved to improve the parallel inverter power distribution accuracy and ensure the reliable dynamic response of the constrained current in the circuit between parallel inverters. Finally, a multi-inverter parallel system model is established to verify the correctness and effectiveness of the proposed control strategy. The voltage waveform under nonlinear load conditions is improved and high-frequency harmonics are suppressed, which has obvious advantages compared with the general virtual impedance design method.

Retracted: Optimization of Voltage Dynamic Performance at Inverter Output with Machine Learning and Intelligent Virtual Impedance

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