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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Attaullah Khidrani
Balochistan University of Engineering and Technology

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Internal mode control based coordinated controller for brushless doubly fed induction generator in wind turbines during fault conditions Ahsanullah Memon; Mohd Wazir Mustafa; Attaullah Khidrani; Farrukh Hafeez; Shadi Khan Baloach; Touqer Ahmed Jumani
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 2: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i2.pp650-656

Abstract

Brushless double fed induction generator (BDFIG) based machines have gained popularity in wind turbine applications because of their easily accessible design. Low voltage ride through (LVRT) is critical for the reliable integration of renewable energy with the power grid. The refore, LVRT capability of brushless DFIGs makes them an attractive choice for maintaining voltage stability in grid. The existing works on BDFIG control suffer from two major drawbacks. Firstly, the methodology does not consider LVRT as a design metric, and secondly, these techniques do not have any means for coordinating between a machine side inverter (MSI) and grid side inverter (GSI). This results in sub-optimal controller design and eventually result in the violation of grid code requirements. To solve these issues, this paper proposes the use of brushless DFIGs in wind turbines using a control technique based on analytical modeling. Moreover, employing internal model control (IMC), the proposed technique can effectively coordinate the control between the MSI and GSI resulting in reduced oscillations, overshoots and improved stability under fault conditions. Furthermore, the simulation results for wind turbine generators show that the proposed scheme significantly improves the stability and compliance of grid codes ascompared to the existing hardware techniques.
Dynamic response enhancement of BDFIG using vector control scheme based internal model c ontrol Ahsanullah Memon; Mohd Wazir Mustafa; Shadi Khan Baloch; Attaullah Khidrani; Touqeer Ahmed
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp90-97

Abstract

Doublefed induction generator(DFIG) has shown tremendous success inwind turbines due to its flexibility and ability to regulate the active andreactive power. However, the presence of brushes and slip rings affects itsreliability, stability, and power quality. Furthermore, itdoes not providepromising outcomes in case of faults even in presence of the crowbar circuit.In contrast, thebrushless doubly fed induction generator(BDFIG) is a morereliable option for wind turbines than its mentioned counterpart due to theabsence of the brushes and slip rings. This research work as such attempts toimprove the dynamic performance of thevector control(VC)oriented powerwinding (PW) stator flux-based BDFIG by optimally selecting theproportional-integral(PI) gains throughinternalmodel control(IMC)approach. The proposed control scheme is utilized to regulate the speed,torque, and reactive power of the considered BDFIG independently. Contraryto the previous literature where the “trial and error method” is generallyutilized, the current research work uses the IMC for selecting the mostsuitable PI parameters, thus reduces the complexity, time consumption, anduncertainty in optimal selection. The considered BDFIG based wind turbinewith the proposed control scheme provides a better BDFIG control designwith an enhanced dynamic response as compared to that of the same withDFIG under identical operating conditions and system configurations.
Distant temperature and humidity monitoring: prediction and measurement Farrukh Hafeez; Usman Ullah Sheikh; Attaullah Khidrani; Muhammad Akram Bhayo; Saleh Masoud Abdallah Altbawi; Touqeer Ahmed Jumani
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i3.pp1405-1413

Abstract

Sensing environmental measuring parameters has a pivotal role in our everyday lives. Most of our daily life activities depend upon environmental conditions. Accurate information about these parameters also helps in several industrial applications like ventilation rate calculation, energy prediction, stock maintenance in warehouses, and saving from harmful conditions. The emergence of machine learning can make it easy to predict such time series problems. This paper describes the design of a remotely controlled robotic car for measuring and predicting humidity and temperature. A customized app for accessing the robotic car is designed to indicate predicted and realtime measured values of humidity and temperature. A sensor installed builtin helps in the measurement. The recurrent neural network (RNN) model is used to predict humidity and temperature. For this purpose, experiments are carried out in both outdoor and indoor settings. Accuracy of 85% and 90% is achieved in an outdoor environment and indoor settings.
Co-Authors Ahsanullah Memon Ahsanullah Memon Farrukh Hafeez Farrukh Hafeez Mohd Wazir Mustafa Muhammad Akram Bhayo Saleh Masoud Abdallah Altbawi Shadi Khan Baloach Shadi Khan Baloch Touqeer Ahmed Touqeer Ahmed Jumani Touqer Ahmed Jumani Usman Ullah Sheikh