2022
DOI: 10.1007/s40435-022-00952-2
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Comparative application of the self-adaptive fuzzy-PI controller for a wind energy conversion system connected to the power grid and based on DFIG

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Cited by 5 publications
(2 citation statements)
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“…Fuzzy-proportional integral (PI) control Wadawa et al, (2022) Reactive power control and performance comparison with the conventional PI controller to show the effectiveness of the work H∞ (Hinf) control (Huo and Xu, 2022) Distributed cooperative automatic generation control and multi-event triggered mechanism co-design State-feedback with disturbance observer (SFDO) control (Khan and Mallik, 2022) Mechanical sensorless control using a high gain observer placed on the rotor side of the DFIG State-feedback with high gain observer (SFHGO) control (Debouza et al, 2016) Robust state-feedback control law using a high gain observer to achieve better operation of the DFIG. State-feedback with sliding mode perturbation observer (SFSMPO) control (Debouza et al, 2018) Disturbance observer-based control applied to the direct power control (DPC) strategy Power quality control (Yang and Jin, 2020) A unified power quality conditioner with advanced dual control is used to improve the power quality of the DFIG under unbalanced grid conditions Frequency control (Mohamed et al, 2020) Adaptive model predictive controller for load frequency control under load variations Power oscillation damping control (Surinkaew and Ngamroo, 2016) Hierarchical coordinated wide-area and PSS for robust power oscillation damping Synchrophasor data-based QV droop control (Mahish and Mishra, 2022) Voltage-reactive power droop control strategy under synchronizing conditions An adaptive droop coefficient-based voltage control approach (Shabbir et al, 2022) Enhanced reactive power support is adopted using the droop coefficient technique Optimal ancillary control for frequency regulation (Prasad and Padhy, 2020) Optimal pitch dynamics under the optimal ancillary control for frequency regulation The overview of the wind energy conversion system (WECS) for an HVDC-based grid-connected system considered in this study is shown in Figure 1.…”
Section: Ancillary Controlmentioning
confidence: 99%
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“…Fuzzy-proportional integral (PI) control Wadawa et al, (2022) Reactive power control and performance comparison with the conventional PI controller to show the effectiveness of the work H∞ (Hinf) control (Huo and Xu, 2022) Distributed cooperative automatic generation control and multi-event triggered mechanism co-design State-feedback with disturbance observer (SFDO) control (Khan and Mallik, 2022) Mechanical sensorless control using a high gain observer placed on the rotor side of the DFIG State-feedback with high gain observer (SFHGO) control (Debouza et al, 2016) Robust state-feedback control law using a high gain observer to achieve better operation of the DFIG. State-feedback with sliding mode perturbation observer (SFSMPO) control (Debouza et al, 2018) Disturbance observer-based control applied to the direct power control (DPC) strategy Power quality control (Yang and Jin, 2020) A unified power quality conditioner with advanced dual control is used to improve the power quality of the DFIG under unbalanced grid conditions Frequency control (Mohamed et al, 2020) Adaptive model predictive controller for load frequency control under load variations Power oscillation damping control (Surinkaew and Ngamroo, 2016) Hierarchical coordinated wide-area and PSS for robust power oscillation damping Synchrophasor data-based QV droop control (Mahish and Mishra, 2022) Voltage-reactive power droop control strategy under synchronizing conditions An adaptive droop coefficient-based voltage control approach (Shabbir et al, 2022) Enhanced reactive power support is adopted using the droop coefficient technique Optimal ancillary control for frequency regulation (Prasad and Padhy, 2020) Optimal pitch dynamics under the optimal ancillary control for frequency regulation The overview of the wind energy conversion system (WECS) for an HVDC-based grid-connected system considered in this study is shown in Figure 1.…”
Section: Ancillary Controlmentioning
confidence: 99%
“…The PI controller and tuning of it and the Bode plot-based analysis were discussed in the studies by Boubzizi et al (2018) and Hu et al (2020). Recent techniques have been developed to overcome balanced and unbalanced faults without allowing decomposition into positive and negative components, and the work was found to be more effective as discussed in Table 1 (Yang et al, 2010;Mohseni et al, 2011;Noureldeen, 2012;Xiao et al, 2012;Bounadja et al, 2014;Justo et al, 2014;Huang et al, 2015;Justo et al, 2015;Varma et al, 2015;Debouza et al, 2016;Ismail and Bendary, 2016;Abdelrahem and Kennel, 2017;Haidar et al, 2017;Justo et al, 2017;Debouza et al, 2018;Döşoğlu et al, 2018;Justo and Bansal, 2018;Rini Ann Jerin et al, 2018;Ali et al, 2019;Huang and Li, 2020;Kadri et al, 2020;Nair and Narayanan, 2020;Yang and Jin, 2020;Baimel et al, 2021;Benbouhenni and Bizon, 2021;Chandravanshi and Gupta, 2021;Hannoon et al, 2021;Kelkoul and Boumediene, 2021;Wadawa et al, 2022;Bhattacharyya and Singh, 2022;Wadawa et al, 2022;Conde D et al, 2022;Din et al, 2022;Ganthia et al, 2022;Gasmi et al, 2022;Hiremath...…”
Section: Introductionmentioning
confidence: 99%