DocumentCode :
1470054
Title :
Dual Active Low-Frequency Ripple Control for Clean-Energy Power-Conditioning Mechanism
Author :
Wai, Rong-Jong ; Lin, Chun-Yu
Author_Institution :
Dept. of Electr. Eng., Yuan Ze Univ., Chungli, Taiwan
Volume :
58
Issue :
11
fYear :
2011
Firstpage :
5172
Lastpage :
5185
Abstract :
This paper focuses on the design of a dual active low-frequency ripple control for a clean-energy power-conditioning mechanism with an aim to achieve both the alleviation of the low-frequency current ripple of clean-energy sources (e.g., solar photovoltaic, fuel cell, etc.) and the improvement of the ac power quality of a power conditioner. First, a simplified circuit for representing both the current-ripple phenomena at the high-voltage bus and the polluted ac output terminal inside a general power conditioner, including a dc-dc converter and a dc-ac inverter, is derived, and the dynamic model of a dual active low-frequency ripple control circuit is analyzed. Moreover, two adaptive linear neural networks are taken as neural filters to generate the compensation current commands, and an adaptive total sliding-mode controller is designed to manipulate the ripple control circuit for injecting respective suitable compensation currents into the high-voltage bus and the ac output terminal of the conditioner. In addition, the effectiveness of the proposed dual active low-frequency ripple control framework is verified by numerical simulations and experimental results.
Keywords :
DC-AC power convertors; DC-DC power convertors; adaptive control; neurocontrollers; power supply quality; variable structure systems; ac power quality; adaptive linear neural networks; adaptive total sliding-mode controller; clean-energy power conditioner; dc-ac inverter; dc-dc converter; dual active low-frequency ripple control; high-voltage bus; neural filters; polluted ac output terminal; Active filters; DC-DC power converters; Harmonic analysis; Power conditioning; Power harmonic filters; Power quality; Sliding mode control; Adaptive linear neural network; adaptive total sliding-mode control (SMC); clean energy; dual active low-frequency ripple control circuit (DALFRCC); neural filter; power condition;
fLanguage :
English
Journal_Title :
Industrial Electronics, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0046
Type :
jour
DOI :
10.1109/TIE.2011.2126533
Filename :
5729361
Link To Document :
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