PWM Based VSC for Power Quality Assessment of Grid Integrated DFIG-WECS

Soomro, Mansoor Ahmed; Memon, Zubair Ahmed; Kumar, Mahesh

doi:10.30880/ijie.2020.12.06.027

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…[16]. To maintain maximum power output, a doubly fed induction generator (DFIG) was chosen since it includes more than 50% of all major onshore wind power plants worldwide [17]. Doubly fed wind turbines are vulnerable to various types of generator losses; these failures lead to excess vibrations that might damage other components, such as bearing failures, which produce non-stationary vibrations [18,19].…”

Section: Introductionmentioning

confidence: 99%

Condition Assessment and Analysis of Bearing of Doubly Fed Wind Turbines Using Machine Learning Technique

et al. 2023

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Condition monitoring of wind turbines is progressively increasing to maintain the continuity of clean energy supply to power grids. This issue is of great importance since it prevents wind turbines from failing and overheating, as most wind turbines with doubly fed induction generators (DFIG) are overheated due to faults in generator bearings. Bearing fault detection has become a main topic targeting the optimum operation, unscheduled downtime, and maintenance cost of turbine generators. Wind turbines are equipped with condition monitoring devices. However, effective and reliable fault detection still faces significant difficulties. As the majority of health monitoring techniques are primarily focused on a single operating condition, they are unable to effectively determine the health condition of turbines, which results in unwanted downtimes. New and reliable strategies for data analysis were incorporated into this research, given the large amount and variety of data. The development of a new model of the temperature of the DFIG bearing versus wind speed to identify false alarms is the key innovation of this work. This research aims to analyze the parameters for condition monitoring of DFIG bearings using SCADA data for k-means clustering training. The variables of k are obtained by the elbow method that revealed three classes of k (k = 0, 1, and 2). Box plot visualization is used to quantify data points. The average rotation speed and average temperature measurement of the DFIG bearings are found to be primary indicators to characterize normal or irregular operating conditions. In order to evaluate the performance of the clustering model, an analysis of the assessment indices is also executed. The ultimate goal of the study is to be able to use SCADA-recorded data to provide advance warning of failures or performance issues.

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Section: Introductionmentioning

confidence: 99%

Condition Assessment and Analysis of Bearing of Doubly Fed Wind Turbines Using Machine Learning Technique

et al. 2023

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“…The power quality indices include a variety of types of disturbances. Many researches have focused on power quality improvement in the distribution system [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

A Novel Power Quality Monitor Placement in Transmission Systems Method Using Binary Teaching Learning-Based Optimization Algorithm Considering Monitoring Redundancy

Mohammadi

2022

IJIE

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This paper deals with optimal employment of power quality monitors (PQMs) in transmission networkson the basis of the idea of monitor reach area. The proposed model uses binary string, representing the installation modeof PQMs (Yes or No) in each bus of the network. In the current article, the binary version ofthe teaching learning-based optimization algorithm (BTLBO) is used. It has the ability to enhance the search potential and provides a rapid and secure convergence rate in the optimization process. The concept of redundancy is considered in this study. Theoverall cost function is formulated to optimize the two indices. The first one is the index of monitoring overlap, and the second one is the index of sag severity. Amongthe solutions whoseobjective function experiments the minimum value, the evaluating the redundancyindexgives the final optimal answer. With an excellent redundancy, the buses of the system faced with faults are monitored more times, on average. In the current research, DIGSILENT software is employed in short circuit analysis, whereas the BTLBO manages the optimization process. In the proposed algorithm, the IEEE 30 Bus transmission network is consideredas a case study, and results are compared to similar investigations to clarify the impressiveness of the proposed algorithm.

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A review of single stage and multistage power converters for doubly fed induction generator integrated with power grid

Soomro,

Memon,

Kumar

et al. 2024

Wind Engineering

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The doubly fed induction generator (DFIG) is the most popular induction generator for onshore wind energy conversion system (WECS). Therefore, the purpose of research is to optimize power transfer from DFIG to power grid which requires frequency and voltage stability in power converters. Hence, the single-stage and multistage power converter topologies associated with grid-integrated DFIG are thoroughly examined in this work. In the single stage, a matrix converter and cycloconverter are used. Whereas, the multistage topologies include two-level back-to-back (2L-B2B) converter, Z-source converter, and multilevel converters. Furthermore, three-level neutral point clamped (3L-NPC) voltage source converters with battery energy storage systems (BESS) and modified superconducting fractional order terminal sliding mode controllers (MSTFOTSMC) have been used with multilevel converter both at rotor side converter (RSC) and grid side converter (GSC) for stabilized generated voltage and higher power output. The MATLAB simulation results demonstrate that the system effectively controls fluctuations in voltage and current thereby improving the power quality in unbalanced situations.

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PWM Based VSC for Power Quality Assessment of Grid Integrated DFIG-WECS

Cited by 3 publications

References 11 publications

Condition Assessment and Analysis of Bearing of Doubly Fed Wind Turbines Using Machine Learning Technique

Condition Assessment and Analysis of Bearing of Doubly Fed Wind Turbines Using Machine Learning Technique

A Novel Power Quality Monitor Placement in Transmission Systems Method Using Binary Teaching Learning-Based Optimization Algorithm Considering Monitoring Redundancy

A review of single stage and multistage power converters for doubly fed induction generator integrated with power grid

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