RFLSA control scheme for power quality disturbances mitigation in DSTATCOM with n-level inverter connected power systems

2019 ◽  
Vol 11 (3) ◽  
pp. 753-778
Author(s):  
N. Raveendra ◽  
V. Madhusudhan ◽  
A. Jaya Laxmi
Keyword(s):  
Power Systems ◽  
Power Quality ◽  
N Level ◽  
Control Scheme ◽  
Power Quality Disturbances

scholarly journals A Hybrid Approach to Classify Power Quality Problems in Distribution Systems

2021 ◽  
Author(s):  
Okan Ozgonenel ◽  
◽  
Kubra Nur Akpinar ◽  
Keyword(s):  
Power Systems ◽  
Power Quality ◽  
Electromagnetic Interference ◽  
Distribution Systems ◽  
Electrical Power ◽  
Hybrid Approach ◽  
Principal Component ◽  
Discrete Wavelet ◽  
Time Data ◽  
Power Quality Disturbances

Electrical power systems are expected to transmit continuously nominal rated sinusoidal voltage and current to consumers. However, the widespread use of power electronics has brought power quality problems. This study performs classification of power quality disturbances using an artificial neural network (ANN). The most appropriate ANN structure was determined using the Box-Behnken experimental design method. Nine types of disturbance (no fault, voltage sag, voltage, swell, flicker, harmonics, transient, DC component, electromagnetic interference, instant interruption) were investigated in computer simulations. The feature vectors used in the identification of the different types of disturbances were produced using the discrete wavelet transform and principal component analysis. Our results show that the optimized feed forward multilayer ANN structure successfully distinguishes power quality disturbances in simulation data and was also able to identify these disturbances in real time data from substations.

Power Quality Problems in PV Fed Grid Connected Inverter

2014 ◽  
Vol 622 ◽  
pp. 147-151
Author(s):  
Natesan Saritha ◽  
Venkatesan Jamuna ◽  
N. Nanthini
Keyword(s):  
Power Systems ◽  
Power Quality ◽  
System Performance ◽  
Short Circuit ◽  
Multilevel Inverter ◽  
Voltage Sag ◽  
Pv Inverter ◽  
Power Quality Disturbances ◽  
Grid Connected Inverter

—– In this paper, problem faced by grid connected pv inverter is presented. Inverters connected to grid are mostly affected due to short circuit problems in the power systems. Therefore it is essential to analyze power quality disturbances in order to improve the quality of the system. Performance of inverter is affected severely by voltage sag compared to other type of power quality disturbances. Also in this paper, multilevel inverter with sag condition and without sag condition is simulated using MATLAB/SIMULINK software

Power Quality Control of Wind-Diesel Hybrid Power Systems Using Fuzzy PI Controller

2012 ◽  
Vol 622-623 ◽  
pp. 1022-1026
Author(s):  
Su Hyung Yang ◽  
Ho Chan Kim ◽  
Chang Jin Boo ◽  
Min Jae Kang ◽  
Eel Hwan Kim ◽  
...  
Keyword(s):  
Power Systems ◽  
Power Quality ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Pi Controller ◽  
Hybrid Power Systems ◽  
Hybrid Power ◽  
Control Scheme ◽  
Fuzzy Pi Controller ◽  
Simulation Results

This paper proposes a modeling and controller design approach for a wind-diesel hybrid system including dump load. The proposed control scheme for power quality is fuzzy PI controller which has advantages of PI and fuzzy controller. Simulation results show that the proposed controller is more effective against disturbances caused by wind speed and load variation than the PI controller, and thus it contributes to a better quality wind-diesel hybrid power system.

scholarly journals Power Quality Improvement Using Unified Power Quality compensator

2021 ◽  
Vol 10 (4) ◽  
pp. 2803-2809
Keyword(s):  
Power Systems ◽  
Power Quality ◽  
Distribution System ◽  
Supply Voltage ◽  
Voltage Sag ◽  
Harmonic Currents ◽  
Power Quality Improvement ◽  
Power Quality Disturbances ◽  
Quality Of Electric Power

Power quality has become an important factor in power systems, for consumer and household appliances with proliferation of various electric/ electronic equipment and computer systems. The main causes of a poor power quality are harmonic currents, poor power factor, supply voltage variations, etc. In recent years the demand for the quality of electric power has been increased rapidly. Power quality problems have received a great attention nowadays because of their impacts on both utilities and customers. Voltage sag, swell, momentary interruption, under voltages, over voltages, noise and harmonics are the most common power quality disturbances.It proposes a new connection for a unified power quality compensator (UPQC) to improve the power quality of two feeders in a distribution system. It illustrates how UPQC can improve the power quality by mitigating all these PQ disturbances. The proposed configuration of the UPQC is developed and verified for various power quality disturbances by simulating the mode using MATLAB.

Classification and Identification of Power System Disturbances Using Wavalet and Artificial Neural Network Technique

2005 ◽  
Vol 2 (2) ◽  
pp. 25
Author(s):  
Noraliza Hamzah ◽  
Wan Nor Ainin Wan Abdullah ◽  
Pauziah Mohd Arsad
Keyword(s):  
Neural Network ◽  
Power Quality ◽  
Probabilistic Neural Network ◽  
Microsoft Excel ◽  
Waveform Data ◽  
The Neural Network ◽  
Harmonic Voltage ◽  
Power Quality Disturbances ◽  
Electronic Load ◽  
Wavelet Technique

Power Quality disturbances problems have gained widespread interest worldwide due to the proliferation of power electronic load such as adjustable speed drives, computer, industrial drives, communication and medical equipments. This paper presents a technique based on wavelet and probabilistic neural network to detect and classify power quality disturbances, which are harmonic, voltage sag, swell and oscillatory transient. The power quality disturbances are obtained from the waveform data collected from premises, which include the UiTM Sarawak, Faculty of Science Computer in Shah Alam, Jati College, Menara UiTM, PP Seksyen 18 and Putra LRT. Reliable Power Meter is used for data monitoring and the data is further processed using the Microsoft Excel software. From the processed data, power quality disturbances are detected using the wavelet technique. After the disturbances being detected, it is then classified using the Probabilistic Neural Network. Sixty data has been chosen for the training of the Probabilistic Neural Network and ten data has been used for the testing of the neural network. The results are further interfaced using matlab script code.  Results from the research have been very promising which proved that the wavelet technique and Probabilistic Neural Network is capable to be used for power quality disturbances detection and classification.

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