.png){kind=icon}
返回
Neural Network Based Conductance Estimation Control Algorithm for Shunt Compensation
.png){kind=icon}
PRE
AI
DOI：10.1109/TII.2013.2264290.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
For mitigation of power quality problems in a distribution system, it is important to estimate effecting factors which are responsible for their origin. Main objectives of neural network application in Distribution Static Compensator (DSTATCOM) are to enhance the efficiency, robustness, tracking capability according to requirements. A control algorithm based on load conductance estimation using the neural network is implemented for DSTATCOM in a four wire distribution system. The proposed control algorithm is used for extraction of load fundamental conductance and susceptance components of distorted load currents. It is implementated for mitigation of power quality problems such as reactive power compensation, harmonics elimination, load balancing and reduction of neutral current under linear/nonlinear loads. Test results on a developed DSTATCOM have shown the acceptable level of performance under balanced and unbalanced loads.
Keyword:
Conductance
load balancing
neural network (NN)
neutral current
power factor correction (PFC)
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
9.9
论文数:
8.6K
被引数:
6.0W
机构
引用论文
.png){kind=icon}
Investigation on the Dielectric Properties of 0–3 Lead Zirconate Titanate-Geopolymer Composites
PREAI
分享收藏A Shunt Active Power Filter With Enhanced Performance Using ANN-Based Predictive and Adaptive Controllers使用基于ANN的预测和自适应控制器增强性能的并联有源电力滤波器
PREAI
分享收藏An Adaptive Robust Predictive Current Control for Three-Phase Grid-Connected Inverters三相并网逆变器的自适应鲁棒预测电流控制
OAAI
OAAI分享收藏
查看更多内容