“…For better operation of these systems, Maximum Power Point Tracking (MPPT) algorithms are 2 Mathematical Problems in Engineering needed to improve the energy efficiency and to extract the maximum power available from the wind turbine. In literature, several techniques were used going from the utilization of classical extreme algorithms such as Perturb and Observes (P&O), Incremental Conductance (INC), and Hil Climbing (HCS) [1] to those based on artificial intelligence as Fuzzy Logic and Neural networks [2]. However, the wind turbine has an advantages that it can be reliably characterized by its specific function ( ).…”
This paper aims at contributing to the modeling and control of a variable speed Wind Energy Conversion System (WEC-System) based on a Squirrel Cage Induction Generator (SCI-Generator). The connection between the SCI-Generator and the main utility grid is achieved by back-to-back three phase power converters (Generator and Grid Side Converters). A new control strategy named the Active Disturbance Rejection Control (ADRC) is proposed and utilized to control the Wind Energy Conversion (WEC) system based on the SCI-Generator. The objective is to control both the generator and the grid side converters in order to operate the system and to ensure the connection with the power grid. The first converter is used to control the SCI-Generator speed and field to extract the available maximum power from the wind turbine by using a Maximum Power Point Tracking (MPPT) technique and, also, to ensure that the extracted power does not exceed its rated value in case of strong wind speeds; in this case a pitch actuator system is used to control the blades pitch angle of the wind turbine. The second converter is used to control the active and reactive powers injected into the utility grid as well as to regulate the DC-Link Voltage. This control takes into account the rejection of internal disturbances as the variation of electrical parameters (the resistance, the inductance…) and the external disturbances as voltage dips and frequency droops in the main grid. To test and validate the performances of the proposed controller, a series of simulations were developed under MATLAB/Simulink environment, and the results have demonstrated the effectiveness of the proposed control under different case of simulations.
“…For better operation of these systems, Maximum Power Point Tracking (MPPT) algorithms are 2 Mathematical Problems in Engineering needed to improve the energy efficiency and to extract the maximum power available from the wind turbine. In literature, several techniques were used going from the utilization of classical extreme algorithms such as Perturb and Observes (P&O), Incremental Conductance (INC), and Hil Climbing (HCS) [1] to those based on artificial intelligence as Fuzzy Logic and Neural networks [2]. However, the wind turbine has an advantages that it can be reliably characterized by its specific function ( ).…”
This paper aims at contributing to the modeling and control of a variable speed Wind Energy Conversion System (WEC-System) based on a Squirrel Cage Induction Generator (SCI-Generator). The connection between the SCI-Generator and the main utility grid is achieved by back-to-back three phase power converters (Generator and Grid Side Converters). A new control strategy named the Active Disturbance Rejection Control (ADRC) is proposed and utilized to control the Wind Energy Conversion (WEC) system based on the SCI-Generator. The objective is to control both the generator and the grid side converters in order to operate the system and to ensure the connection with the power grid. The first converter is used to control the SCI-Generator speed and field to extract the available maximum power from the wind turbine by using a Maximum Power Point Tracking (MPPT) technique and, also, to ensure that the extracted power does not exceed its rated value in case of strong wind speeds; in this case a pitch actuator system is used to control the blades pitch angle of the wind turbine. The second converter is used to control the active and reactive powers injected into the utility grid as well as to regulate the DC-Link Voltage. This control takes into account the rejection of internal disturbances as the variation of electrical parameters (the resistance, the inductance…) and the external disturbances as voltage dips and frequency droops in the main grid. To test and validate the performances of the proposed controller, a series of simulations were developed under MATLAB/Simulink environment, and the results have demonstrated the effectiveness of the proposed control under different case of simulations.
“…To solve this, the hybrid HCS method described in [8] includes optimal torque control to solve the problem of incorrect directionality under rapid wind speed changes. In [9], the authors presented a new control strategy for the induction generator in WECS using a sliding mode speed observer to estimate the rotational speed of the induction generator. However, the traditional proportional integral (PI) controller cannot ensure fast convergence to a simple linear dynamic behavior.…”
This paper presents a hybrid intelligent control method that enables frequency support control for permanent magnet synchronous generators (PMSGs) wind turbines. The proposed method for a wind energy conversion system (WECS) is designed to have PMSG modeling and full-scale back-to-back insulated-gate bipolar transistor (IGBT) converters comprising the machine and grid side. The controller of the machine side converter (MSC) and the grid side converter (GSC) are designed to achieve maximum power point tracking (MPPT) based on an improved hill climb searching (IHCS) control algorithm and de-loaded (DL) operation to obtain a power margin. Along with this comprehensive control of maximum power tracking mode based on the IHCS, a method for kinetic energy (KE) discharge control of the supporting primary frequency control scheme with DL operation is developed to regulate the short-term frequency response and maintain reliable operation of the power system. The effectiveness of the hybrid intelligent control method is verified by a numerical simulation in PSCAD/EMTDC. Simulation results show that the proposed approach can improve the frequency regulation capability in the power system.
“…Dynamic Model of DC-Link and Filter. A commonly used dynamic Park model of the grid side can be expressed by (15)- (19):…”
Section: Dynamic Model Of Dfigmentioning
confidence: 99%
“…As mentioned previously in the introduction, the maximum power point tracking algorithm is a technique which is used to extract the maximum power from the turbine for different wind speeds. As described in [19], the available MPPT algorithms can be classified as either with or without wind sensors. e authors in [2] have demonstrated the superiority of the optimal torque control (OTC) method in terms of simplicity and accuracy (because it does not measure the wind speed directly).…”
A novel and robust active disturbance rejection control (ADRC) strategy for variable speed wind turbine systems using a doubly fed induction generator (DFIG) is presented in this paper. The DFIG is directly connected to the main utility grid by stator, and its rotor is connected through a back-to-back three phase power converter (AC/DC/AC). Due to the acoustic nature of wind and to ensure capturing maximum energy, a control strategy to extract the available maximum power from the wind turbine by using a maximum power point tracking (MPPT) algorithm is presented. Moreover, a pitch actuator system is used to control the blades’ pitch angle of the wind turbine in order to not exceed the wind turbine rated power value in case of strong wind speeds. Furthermore, the rotor-side converter is used to control the active and reactive powers generated by the DFIG. However, the grid-side converter is used to control the currents injected into the utility grid as well as to regulate the DC-link voltage. This paper aims to study and develop two control strategies for wind turbine system control: classical control by proportional integral (PI) and the proposed linear active disturbance rejection control (LADRC). The main purpose here is to compare and evaluate the dynamical performances and sensitivity of these controllers to the DFIG parameter variation. Therefore, a series of simulations were carried out in the MATLAB/Simulink environment, and the obtained results have shown the effectiveness of the proposed strategy in terms of efficiency, rapidity, and robustness to internal and external disturbances.
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