A Novel Supervised Control Strategy for Interconnected DFIG-Based Wind Turbine Systems: MiL Validations

Moghadam, Hooman Mohammadi; Gheisarnejad, Meysam; Esfahani, Zahra; Khooban, Mohammad‐Hassan

doi:10.1109/tetci.2020.3010060

Cited by 13 publications

(5 citation statements)

References 48 publications

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“…Through literature reviews, there are some investigations [4] which provide the advantage of PV systems with respect to other RESs. In [5], it is deducted that the PV schemes require very low maintenance costs, zero pollution, reliable output power and low operational costs with respect to traditional power plants equipped with synchronous generators. Therefore, considering an integrated system consisting of PV, OWF and WEF sources, it is possible to supply considerable amount of generating electrical power with several RES advantages in a unit electrical system [6].…”

Section: B1 Recent Research Evaluationsmentioning

confidence: 99%

“…From (5), ρWEF represents density of the water in kg/m3, ArWEF is the turbine blade area in m 2 , VWEF is the turbine velocity in m/s and CpWEF represents a constant coefficient evaluated from turbine speed ratio λWEF and pitch angle βWEF, correspondingly. Based on provided model ( 5) and considering cut-in value=1m/s, cut-off value= 5 m/s and rated value=2.5 m/s, the provided wave-based turbine dynamic model is evaluated.…”

Section: B Wave Energies Turbine Modelmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive Neuro-Fuzzy Damping Controller of Grid-Connected Microgrid Hybrid System Integrating Wind Farms and Batteries

Habibi,

Yousefi,

Shirazi

et al. 2024

IEEE Access

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Renewable energies equipped with LIRs as wind turbines and photovoltaic arrays provide negative impacts on power system dynamic securities. For this issue, developing adaptive controlling strategies play important role on controlling the system dynamic oscillations. In this paper, based on HVDC link, an ANFDC damping controller is proposed for controlling the system dynamic behavior through different LIRs. To do this, a fuzzy linguistic role proposed for tuning ANFDC parameters which the input dynamic signals are transferred into linguistic variables through offline working mode. Then, considering microgrid consists of different LIRs as offshore and onshore WTs, PVs and SSSGs integrated with together, ANFDC is trained which then in online working mode, the system damping performances through different operational and technological structures are evaluated. The proposed scheme is an online and non-modelbased controller which uses the advantages of both neural and fuzzy logics together for providing a fast and secure structure of damping controller through online evaluations. The merit and effectiveness of the proposed approach investigated on a grid-connected microgrid consisting of PV, WT and SSSG connected in an incorporated HVDC link which considering different short circuit faults, damping performances are evaluated. Results indicate effectiveness of the proposed scheme for damping dynamic oscillations of LIRs with high damping ratios subject against severe fault events.

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Section: B1 Recent Research Evaluationsmentioning

confidence: 99%

Section: B Wave Energies Turbine Modelmentioning

confidence: 99%

Adaptive Neuro-Fuzzy Damping Controller of Grid-Connected Microgrid Hybrid System Integrating Wind Farms and Batteries

Habibi,

Yousefi,

Shirazi

et al. 2024

IEEE Access

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“…In [14], the low voltage ride-through (LVRT) capability of the DFIG-WTs and damping of voltage oscillation are enhanced under symmetrical and asymmetrical grid faults. Several papers have also concentrated on the advanced control theories such as sliding mode control (SMC) [16][17][18], fuzzy logic control (FLC) [19][20][21], model predictive control (MPC) [22][23][24] for the power converter of the DFIGs connected to AC grids. In [23], the MPC-based control strategy is suggested to enhance system reliability and power quality and this method has been evaluated in the AC grid with unbalanced and distorted voltage.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, in [17], a fractional‐order sliding mode control (FOSMC) strategy is introduced to minimize the undesirable influence of chattering on the system. FLC‐based control methods, as heuristic control approaches, exhibit low dependency on the precise system model and parameters and operating points [19, 25]. In [21], the FLC‐based control method is developed for the DFIG‐WT and system capability is assessed against symmetrical and unsymmetrical faults.…”

Section: Introductionmentioning

confidence: 99%

Direct current grid‐based doubly‐fed induction generator wind turbines: Real‐time control and stability analysis

Akhbari

Rahimi

Khooban

2022

IET Power Electronics

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Commonly, a simple topology consisting of a single diode‐rectifier and pulse‐width‐modulation (PWM) converter is used for the connection of the doubly‐fed induction generator‐based wind turbines (DFIG‐WTs) to the DC grid, in which the rotor‐side converter (RSC) and the stator diode‐rectifier are linked to the common DC bus. But, this topology suffers from less flexibility due to the requirement of matching the stator nominal voltage with the DC grid. Hence, in this paper, a buck converter is added to the DFIG‐WT topology and two methods are proposed to control the power converters, where in the first one, the RSC regulates the active power and stator flux linkage, and in the second one, the RSC regulates the DC bus voltage and stator flux linkage. Then, the small‐signal stability and the performance of the DFIG‐WT system with the mentioned control strategies are compared analytically and through the off‐line simulations. At last, a real‐time hardware‐in‐the‐loop (HIL) emulation‐based OPAL‐RT is carried out to investigate the performance of the proposed control methods from a practical perspective.

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“…As the world is experiencing a diminishing trend in terms of fossil fuels and their bad effects on the environment through emitting harmful gases into the atmosphere, wind energy has become the fastest-growing renewable energy source that has an eco-friendly power generation [1][2][3][4][5]. For this reason and also due to the advanced technological equipment and facilities, the number of wind turbine installations along with their size has increased for converting the wind's kinetic energy into electrical energy.…”

Section: Introductionmentioning

confidence: 99%

A Novel Nonsingular Terminal Sliding Mode Control-Based Double Interval Type-2 Fuzzy Systems: Real-Time Implementation

Moghadam¹,

Gheisarnejad²,

Yalsavar³

et al. 2021

Inventions

Self Cite

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Extensive use of wind turbine (WT) systems brings remarkable challenges to the stability and safety of the power systems. Due to the difficulty and complexity of modeling such large plants, the model-independent strategies are preferred for the control of the WT plants which eliminates the need to model identification. This current work proposes a novel model-independent control methodology in the rotor side converter (RSC) part to ameliorate low voltage ride through (LVRT) ability especially for the doubly-fed induction generator (DFIG) WT. A novel model-independent nonsingular terminal sliding mode control (MINTSMC) was developed based on the principle of the ultra-local pattern. In the suggested controller, the MINTSMC scheme was designed to stabilize the RSC of the DFIG, and a sliding-mode supervisor was adopted to determine the unknown dynamics of the proposed system. An auxiliary dual input interval type 2 fuzzy logic control (DIT2-FLC) was established in a model-independent control structure to remove the estimation error of the sliding mode observer. Real-time examinations have been carried out using a Real-Time Model in Loop (RT-MiL) for validating the applicability of the proposed model-independent control in a real-time platform. To evaluate the usefulness and supremacy of the MINTSMC based DIT2-FLC, the real-time outcomes are compared with outcomes of RSC regulated conventional PI controller and MINTSMC controller.

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A Novel Supervised Control Strategy for Interconnected DFIG-Based Wind Turbine Systems: MiL Validations

Cited by 13 publications

References 48 publications

Adaptive Neuro-Fuzzy Damping Controller of Grid-Connected Microgrid Hybrid System Integrating Wind Farms and Batteries

Adaptive Neuro-Fuzzy Damping Controller of Grid-Connected Microgrid Hybrid System Integrating Wind Farms and Batteries

Direct current grid‐based doubly‐fed induction generator wind turbines: Real‐time control and stability analysis

A Novel Nonsingular Terminal Sliding Mode Control-Based Double Interval Type-2 Fuzzy Systems: Real-Time Implementation

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