Research on the Operation Control Strategy of a Low-Voltage Direct Current Microgrid Based on a Disturbance Observer and Neural Network Adaptive Control Algorithm

Liang Zhang, Kang Chen, Ling Lyu and Guowei Cai
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Liang Zhang: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
Kang Chen: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
Ling Lyu: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
Guowei Cai: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China

Energies, 2019, vol. 12, issue 6, 1-17

Abstract: Low-voltage direct current (DC) microgrid based on distributed generation (DG), the problems of load mutation affecting the DC bus under island mode, and the security problems that may arise when the DC microgrid is switched from island mode to grid-connected mode are considered. Firstly, a DC bus control algorithm based on disturbance observer (DOB) was proposed to suppress the impact of system load mutation on DC bus in island mode. Then, in a grid-connected mode, a pre-synchronization control algorithm based on a neural network adaptive control was proposed, and the droop controller was improved to ensure better control accuracy. Through this pre-synchronization control, the microgrid inverters output voltage could quickly track the power grid’s voltage and achieve an accurate grid-connected operation. The effectiveness of the algorithms was verified by simulation.

Keywords: direct current (DC) microgrid; island mode; grid-connected mode; DC bus; droop control; neural network; pre-synchronization control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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