Neural Network Inverse Control for the Output Voltage of Energy Storage Inverter in Micro-grid

doi:10.16182/j.issn1004731x.joss.201611024

Abstract

Abstract: In order to improve the output voltage waveform quality of energy storage inverter in micro-grid, an inverse control method was proposed based on BP neural network. Mathematical model of the energy storage inverter was established, and the main factors affecting the output voltage were analyzed, and then the expansion inverse model of the system was established based on BP neural network. In order to overcome the local optimum disadvantage in BP training algorithm, gravity algorithm was adopted to optimize the network initial parameters. The neural network inverse model was put in series with its original model to form a pseudo linear system, and then PI controller was selected to perform the single loop control. The simulation results show that the proposed control method can effectively improve the dynamic response speed of the inverter output voltage and reduce the harmonic content. Experiment is performed on 10 kW inverter prototype, which proves the proposed method feasibility and effectiveness.

Key words: energy storage inverter, inverse model, neural network, harmonic content

CLC Number:

TM85

Liu Weiliang, Lin Yongjun, Liu Changliang, Chen Wenying, Ma Liangyu. Neural Network Inverse Control for the Output Voltage of Energy Storage Inverter in Micro-grid[J]. Journal of System Simulation, 2016, 28(11): 2813-2822.

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