scholarly journals Power Quality Evaluation of Distribution Network Containing Microgrid Based on PCNN

2015 ◽  
Vol 9 (1) ◽  
pp. 160-165 ◽  
Author(s):  
Ni Fuyin ◽  
Li Zhengming ◽  
Pan Tianhong
Keyword(s):  
Neural Network ◽  
Power Quality ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Distribution Network ◽  
Threshold Value ◽  
Input Power ◽  
Evaluation Indexes ◽  
Quality Grade ◽  
Fuzzy Neural

Aiming at the nonlinear relationship between the evaluation indexes and the complex grade of power quality, a power quality evaluation method is proposed based on model of pulse coupled neural network (PCNN). The operating schematic is analyzed according to PCNN modeling. The input power quality grade is controlled by threshold value, and the evaluation grade is output by neuron ignition. The evaluation methods between PCNN and fuzzy neural network are compared through the measured data, the results indicate that PCNN method is more scientific and accurate, and provides a new method to solve the problem on power quality evaluation of distribution network containing microgrid.

Research on Information Technology with Wine Quality Evaluation Based on Neural Network

2014 ◽  
Vol 886 ◽  
pp. 532-536 ◽  
Author(s):  
Rong Liang Zhu ◽  
Yong Cun Cao ◽  
Qiu Mei Pu
Keyword(s):  
Neural Network ◽  
Information Technology ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Great Influence ◽  
Chemical Properties ◽  
Red Wines ◽  
Wine Quality ◽  
Quality Grade

Use modern information technology to replace the traditional manual quality grade evaluation of red wine. According to the red wines 11 physical and chemical properties which have a great influence on the quality, a quality grade evaluation model based on BP neural network pattern classification is established in this paper. The input variables are the red wines 11 parameters, output are the quality levels for wine. Experimental results show that it is an effective wine quality evaluation method.

Research on Reliability Evaluation Methods of Distribution System

2014 ◽  
Vol 672-674 ◽  
pp. 1441-1446 ◽  
Author(s):  
Yu Qiang Ou ◽  
Le Feng Cheng ◽  
Jian Zhong Wen ◽  
Xuan Yu Qiu ◽  
Tao Yu
Keyword(s):  
Distribution System ◽  
Evaluation Method ◽  
Network Reliability ◽  
Distribution Network ◽  
Reliability Evaluation ◽  
Evaluation Indexes ◽  
Specific Distribution ◽  
And Function ◽  
Meaning And Function

Research on reliability of distribution network has very important meaning and function to ensure the quality of power supply. This paper introduces some basic concepts of reliability in distribution network, including distribution network reliability definition, task and index. The classical reliability evaluation method was reviewed, and focused on specific distribution network, an example analysis was given, and specific reliability evaluation indexes were calculated. Finally, the future development of distribution network reliability evaluation was made a simple prospect.

APPLICATIONS OF WAVELET TRANSFORM AND FUZZY NEURAL NETWORK ON POWER QUALITY RECOGNITION

2008 ◽  
Author(s):  
Chiung-Chou Liao ◽  
Hong-Tzer Yang ◽  
Ying-Chun Lin ◽  
Nader Barsoum ◽  
Sermsak Uatrongjit ◽  
...  
Keyword(s):  
Neural Network ◽  
Wavelet Transform ◽  
Power Quality ◽  
Fuzzy Neural Network ◽  
Fuzzy Neural

Research on the Application of Fuzzy Neural Network in the Automobile Reliability

2010 ◽  
Vol 136 ◽  
pp. 77-81
Author(s):  
Yan Zhong Men
Keyword(s):  
Neural Network ◽  
Fuzzy Neural Network ◽  
Evaluation Method ◽  
Theoretical Foundation ◽  
Field Conditions ◽  
Maintenance Strategy ◽  
Automobile Engines ◽  
Fuzzy Neural ◽  
Engine Failure

The data of engine failures about automobile operating in field conditions was collected by running engine failure tracking tests. An evaluative model was established using the theory of Fuzzy Neural Network (FNN) for the automobile “using reliability, based on the data of failures about automobiles, finally, the evaluative result for the automobile” using reliability was obtained by evaluative model of reliability. The result of research can be used as references for the improvement of reliability and maintainability of automobile engines, and for the establishment of maintenance strategy, and it also laid a theoretical foundation for studying the improvement of evaluation method for the automobiles' reliability as well.

scholarly journals VOLTAGE COMPENSATION USING ARTIFICIAL NEURAL NETWORK: A CASE STUDY OF RUMUOLA DISTRIBUTION NETWORK

2016 ◽  
Vol 36 (1) ◽  
pp. 178-185
Author(s):  
R Uhumnwangho ◽  
E Omorogiuwa ◽  
G Offor
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Power Quality ◽  
Distribution Network ◽  
Dynamic Voltage Restorer ◽  
Port Harcourt ◽  
Voltage Restorer ◽  
Dynamic Voltage ◽  
Artificial Neural ◽  
Rivers State

 A study of hourly voltage log taken over a period of six months from Rumuola Distribution network Port Harcourt, Rivers State indicates that power quality problems prevalent in the Network are undervoltage/voltage sags and overvoltage/voltage swells. This paper aims at addressing these power quality problems in the distribution network using artificial neural network (ANN) controller based dynamic voltage restorer (DVR). The artificial neural networks controller engaged to controlling the dynamic voltage restorer were trained with input and output data of proportional integral (PI) controller and of unit amplitude generator obtained during simulation. All simulations and modeling were carried out in MathLab/Simulink. Proposed dynamic voltage restorer was tested with replicated model of Rumuola substation by simulating with sample of average voltage for Omerelu, Waterlines, Rumuola, Shell Industrial and Barracks feeders. Simulation results showed that DVR is effective in compensating for under-voltage and over-voltage in Rumuola Distribution network Port Harcourt, Rivers State. http://dx.doi.org/10.4314/njt.v36i1.23

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