DSTATCOM employing hybrid neural network control technique for power quality improvement

被引:29
作者
Kumar, Anup Panda [1 ]
Mangaraj, Mrutyunjaya [1 ]
机构
[1] Natl Inst Technol Rourkela, Elect Engn, Rourkela 769008, India
关键词
static VAr compensators; neurocontrollers; power supply quality; backpropagation; power factor correction; capacitors; power convertors; harmonic distortion; DSTATCOM; hybrid neural network control technique; power quality; hybrid control technique; gradient descent back propagation; two-level distribution static compensator; harmonic mitigation; reactive loads; voltage source converter; real-time digital simulator; harmonics distortion; IEEE-519; standard; CONTROL STRATEGIES; FILTER; PERFORMANCE; ALGORITHM; TOPOLOGY; 3-PHASE; VOLTAGE; PI;
D O I
10.1049/iet-pel.2016.0556
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A new hybrid control technique called gradient descent back propagation (GDBP)-based i cos phi for a three phase two-level distribution static compensator (DSTATCOM) to perform the functions such as harmonic mitigation, power factor correction under reactive loads, which further reduces the DC link voltage across the self-supported capacitor of voltage source converter (VSC). The weighted value of fundamental active and reactive components of load currents are extracted using the proposed control technique to generate the reference source currents. Furthermore, these currents are used to trigger the VSC of the DSTATCOM. The effectiveness of this control technique is demonstrated through simulation using MATLAB/SIMULINK and sim power system tool boxes. The real-time implementation of DSTATCOM is also realised by real-time digital simulator. These results reveal the robustness of the proposed DSTATCOM as it is showing outstanding harmonic compensation capabilities under the various loading conditions and keeping the total harmonics distortion of the source current well <5%, the limit imposed by IEEE-519 standard.
引用
收藏
页码:480 / 489
页数:10
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