Mitigation of DC Components Using Adaptive BP-PID Control in Transformless Three-Phase Grid-Connected Inverters

Long Bo, Lijun Huang, Yufei Dai, Youliang Lu and Kil To Chong
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Long Bo: School of Mechanical and Electrical Engineering, Institute for Electric Vehicle Driving System and Safety Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
Lijun Huang: School of Mechanical and Electrical Engineering, Institute for Electric Vehicle Driving System and Safety Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
Yufei Dai: School of Mechanical and Electrical Engineering, Institute for Electric Vehicle Driving System and Safety Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
Youliang Lu: School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Kil To Chong: Department of Electronics & Information Engineering, Chonbuk National University, Jeonju 567, Korea

Energies, 2018, vol. 11, issue 8, 1-22

Abstract: Transformerless grid-connected inverters, due to their advantages of high efficiency, small volume and light weight, have been the subject of more research and interest in recent years. Due to the asymmetrical driving signal in pulse width modulation (PWM) caused by time-delay, zero-drift of the current sensors and imparities of the power transistors, output of the grid current contains dc component. As a result, power quality of the grid is degraded. In this paper, a dc (direct current) component suppression scheme with adaptive back-propagation (BP) neural network proportional-integral-differential (PID) control is proposed for dc component minimization. Moreover, sliding-window-double-iteration-method (SWDIM) is utilized for fast dc component extraction. Compared with the conventional method, the proposed scheme shows better performance, and the dc component can be attenuated to be within 0.5% of the rated current.

Keywords: dc component; power quality; adaptive back-propagation; neural network; grid-connected inverter (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: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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