Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : International Journal of Electrical and Computer Engineering

Low-voltage ride-through for a three-phase four-leg photovoltaic system using SRFPI control strategy Haval Sardar Kamil; Dalila Mat Said; Mohd Wazir Mustafa; Mohammad Reza Miveh; Nasarudin Ahmad
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (14.611 KB) | DOI: 10.11591/ijece.v9i3.pp1524-1530

Abstract

With the innovative progresses in power electronics in recent years, photovoltaic (PV) systems emerged as one of the promising sources for electricity generation at the distribution network. Nonetheless, connection of PV power plants to the utility grid under abnormal conditions has become a significant issue and novel grid codes should be recommend. The low-voltage ride-through (LVRT) capability is one of the challenges faced by the integration of PV power stations into electrical grid under abnormal conditions. This work firstly provides a discussion on recent control schemes for PV power plants to enhance the LVRT capabilities. Next, a control scheme for a three-phase four-leg grid-connected PV inverter under unbalanced grid fault conditions using synchronous reference frame proportional integral (SRFPI) controller is proposed. Simulation studies are performed to investigate the influence of the control strategy on the PV inverter.
Comparison analysis of different classification methods of power quality disturbances Nur Adrinna Shafiqa Zakaria; Dalila Mat Said; Norzanah Rosmin; Nasarudin Ahmad; Mohamad Shazwan Shah Jamil; Sohrab Mirsaeidi
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i6.pp5754-5764

Abstract

Good power quality delivery has always been in high demand in power system utilities where different types of power quality disturbances are the main obstacles. As these disturbances have distinct characteristics and even unique mitigation techniques, their detection and classification should be correct and effective. In this study, eight different types of power quality disturbances were synthetically generated, by using a mathematical approach. Then, continuous wavelet transform (CWT) and discrete wavelet transform with multi-resolution analysis (DWT-MRA) were applied, which eight features were then extracted from the synthesized signals. Three classifiers namely, decision tree (DT), support vector machine (SVM) and k-nearest neighbors (KNN) were trained to classify these disturbances. The accuracy of the classifiers was evaluated and analyzed. The best classifier was then integrated with the full model, which the performance of the proposed model was observed with 50 random signals, with and without noise. This study found that wavelet-transform was effective to localize the disturbances at the instant of their occurrence. On the other hand, the SVM classifier is superior to other classifiers with an overall accuracy of 94%. Still, the need for these classifiers to be further optimized is crucial in ensuring a more effective detection and classification system.