Improving the Characteristics of the Direct FOC Strategy in DFIG‐Based Wind Turbine Systems Using FOIDD and FOPD Controllers

A new control strategy is proposed to suppress earthquake-induced vibrations on uncertain building structures. The control strategy embeds fuzzy logic in a fractional-order (FO) proportional derivative (FOPD) controller. A new improved FO particle swarm optimization (IFOPSO) algorithm is derived to adjust the initial parameters of the FOPD controller. An original fuzzy logic-FOPD (FFOPD) controller is then designed by combining the advantages of the fuzzy logic and FOPD control, to deal with large displacements on structures under earthquake excitation. Simulation experiments are carried out on uncertain building structures subjected to the effects of different kinds of seismic signals, illustrating the validity and feasibility of the proposed method.

This paper presents the control strategy for a stand-alone wind turbine system connected to batteries is presented in this paper. The wind turbine system uses permanent magnet synchronous generators (PMSG). The control strategy consists of optimum power extraction based on particle swarm optimization (PSO) and loads voltage control based on multi-objective PSO (MOPSO). The optimum power extraction functions to get optimal power at each wind speed based on voltage and current of converter through the control of the converter duty cycle. While MOPSO will tuning parameter of the proportional integrator (PI) controller which will regulate the bidirectional converter through duty cycle setting so that the dc-link voltage can be held according to the reference value. This control strategy is tested for slowly and rapid wind speed changes. Based on the test results, this control strategy has good performance. The dc-link voltage can be maintained constant at 400V and the power can be extracted optimally even though the wind speed fluctuates rapidly.

Abstract: This article introduces hybrid Arithmetic Optimization Algorithm (AOA) and Local Unimodal Sampling (hAOA-LUS)-based fractional order (FO) proportional derivative (PD) cascaded with one plus proportional integral (1+PI) controller for automatic generation control of power system with renewable energy sources (RES) and electric vehicle (EV). The control-area 1 has thermal, hydro, gas, and wind power generators and the same true for control area 2, which uses thermal, hydro, gas, and solar energy sources. Initially, Proportional-Integral-Derivative (PID) controllers are taken into consideration and it has been demonstrated that hAOA-LUS outperforms as compared to the AOA, Particle Swarm Optimization, and Generic Algorithm (GA). The assessing of overshoots, undershoots, and different integral errors of frequency and tie-line power deviations after step load perturbations in each area allows for performance comparison of the proposed power system. In the next stage, EVs are considered in each area and the controller parameters are optimized by hAOA-LUS techniques in the presence of RES and EV. A comparative analysis is carried out by hAOA-LUS-tuned FO PD(1+PI) controller with PID as well integer ordered PD(1+PI) for various cases so as to validate the superiority of the anticipated controller. The results from MATLAB and OPAL-RT are compared in order to verify the authenticate feasibility of method. Cite this article as: A. Kumar Baliarsingh, S. “Keshori Mohapatra and P. Mohan Dash, Fractional order PD(1+ PI) controller for frequency control of power system with renewable sources and electric vehicle,” Electrica, 24(2), 406-424, 2024.

Energy ripples are among the common problems in renewable energies as a result of using less efficient strategies. In this work, a new technique is suggested to control a doubly-fed induction generator (DFIG) using the pulse width modulation (PWM). The new technique is based on the combination of neural networks and fractional-order control to minimize the reactive and active power ripples of the DFIG-based variable speed dual-rotor wind turbine system. The suggested fractional-order neural control (FONC) with the PWM is a simple, robust and a high-performance strategy. Simulation is performed using Matlab software to validate the effectiveness of the designed control of 1.5 MW DFIG and the obtained results are compared with the traditional direct power control (DPC) in different working conditions. In addition, the comparison between the suggested control and the DPC is performed in the cases of changing or not changing the device parameters in terms of ripple ratio, dynamic response, steady-state error, current quality, and overshoot of active and reactive power of the DFIG. As compared to the DPC, the proposed FONC technique improves the active and reactive power ripples by 65.71% and 84.74%, respectively. Also, improves the overshoot of the active and reactive power by 71.33% and 91.72%, respectively. The simulation results demonstrate the high performance and robustness of the FONC technique for the parametric variations of the DFIG-based variable speed dual-rotor wind turbine system compared to the DPC control.

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.

This article proposes a control strategy based on a Fractional Order Proportional Derivative (FOPD) controller to enhance the performance and robustness of quadrotors operating in trajectory tracking mode. The tuning method proposed for the FOPD controller is based on an ideal Bode transfer function in a closed loop as a fractional reference model. The latter represents the quadrotor desired closed-loop response, and its specification is the key design decision. In this study, we first appropriately set model reference parameters to realistic desired time response characteristics (i.e. overshoot and time constant). Then, the parameters of the FOPD controller are computed using the direct synthesis design approach. The dynamic model of the quadrotor is developed using Lagrange formulation. The model is used to test the performance of the proposed FOPD-based control strategy for the attitude, position, and altitude of the flying robot. The results show that the proposed controller achieved accurately set points tracking with transient responses (i.e. overshoot and time constant) that satisfactorily meet those assigned for their respective reference models. These results validate the effectiveness of our proposed control strategy. Moreover, our comparative studies of the proposed FOPD controller with the conventional PD controller show that the former satisfies better-desired design requirements.

A synergetic sliding mode (SSM) approach is designed to address the drawbacks of the direct field-oriented control (DFOC) of the induction generators (IGs) integrated into variable speed dual-rotor wind power (DRWP) systems with the maximum power point tracking (MPPT) technique. Using SSM controllers in the DFOC strategy, the active power, electromagnetic torque, and reactive power ripples are reduced compared to traditional DFOC using proportional-integral (PI) controllers. This proposed strategy, associated with SSM controllers, produces efficient state estimation. The effectiveness of the designed DFOC strategy has been evaluated on variable speed DRWP systems with the MPPT technique.

This paper considers the fractional order proportional derivative (FOPD) controller and fractional order [proportional derivative] (FO[PD]) controller for networked position servo systems. The systematic design schemes of the networked position servo system with a time delay are presented. It follows from the Bode plot of the FOPD system and the FO[PD] that the given gain crossover frequency and phase margin are fulfilled. Moreover, the phase derivative w.r.t. the frequency is zero, which means that the closed-loop system is robust to gain variations at the given gain crossover frequency. However, sometimes we can not get the controller parameters to meet our robustness requirement. In this paper, we have studied on this situation and presented the requirement of the gain cross frequency, and phase margin in the designing process. For the comparison of fractional order controllers with traditional integer order controller, the integer order proportional integral differential (IOPID) was also designed by using the same proposed method. The simulation results have verified that FOPD and FO[PD] are effective for networked position servo. The simulation results also reveal that both FOPD controller and FO[PD] controller outperform IO-PID controller for this type of system.

Aim. This paper presents the minimization of reactive and active power ripples of doubly fed induction generators using super twisting algorithms and pulse width modulation based on neuro-fuzzy algorithms. Method. The main role of the indirect active and reactive power control is to regulate and control the reactive and active powers of doubly fed induction generators for variable speed dual-rotor wind power systems. The indirect field-oriented control is a classical control scheme and simple structure. Pulse width modulation based on an adaptive-network-based fuzzy inference system is a new modulation technique; characterized by a simple algorithm, which gives a good harmonic distortion compared to other techniques. Novelty. adaptive-network-based fuzzy inference system-pulse width modulation is proposed. Proposed modulation technique construction is based on traditional pulse width modulation and adaptive-network-based fuzzy inference system to obtain a robust modulation technique and reduces the harmonic distortion of stator current. We use in our study a 1.5 MW doubly-fed induction generator integrated into a dual-rotor wind power system to reduce the torque, current, active power, and reactive power ripples. Results. As shown in the results figures using adaptive-network-based fuzzy inference system-pulse width modulation technique ameliorate effectiveness especially reduces the reactive power, torque, stator current, active power ripples, and minimizes harmonic distortion of current (0.08 %) compared to classical control.

This paper proposes a novel direct power control (DPC) strategy for doubly fed induction generator (DFIG) drives fed by a four-switch three-phase converters (FSTPCs). In this method, two FSTPCs in rotor and grid side have been used instead of two six-switch three-phase converters (SSTPC). Reduction in the number of active switches will lead to improvement in reliability, reduction in costs and less conduction losses. The FSTPC will generate four unbalanced voltage vectors. A strategy used in order to balance these four voltage vectors. The introduced strategy is based on the emulation of the operation of the conventional SSTPC. In this method, four unbalanced voltage vectors that were generated by FSTPC somehow combined together which produced six balanced voltage vectors of the SSTPC. Then, the new switching table is written for new DPC method for DFIG. Also, during the unbalanced grid voltage condition, three selectable targets are provided for compensating active and reactive power, electromagnetic torque and stator current. These targets are added to power references and are caused decreasing the active and reactive power ripples, mitigation electromagnetic torque pulsations and sinusoidal and balanced stator currents. In the end, an economic comparison between two FSTPC and SSTPC is done. Also, the novel DPC method, i.e., use of FSTPC in rotor and grid side, is compared with prior DPC method, i.e., use of SSTPC in rotor and grid side, and its effectiveness is confirmed by simulation results from a 1-MW DFIG system.

A conventional sliding mode (SMC) and second-order sliding mode (SOSMC) control schemes based on pulse width modulation (PWM) for the rotor side converter (RSC) and grid side converter (GSC) feeding a doubly fed induction generator (DFIG) are presented in this paper. The proportional integral (PI) controllers for wind turbine system (WTS) driven-DFIG have shown many limitations such as parameter adjustment difficulties, sensibility to DFIG parameter variations and poor robustness. Therefore, nonlinear controllers based on SMC and SOSMC are proposed to improve the wind energy conversion efficiency and the system robustness by controlling the RSC and GSC at a constant switching frequency. The proposed controllers turn-out to be more robust against parameter variations of the DFIG and external disturbances. In addition, the SMC and SOSMC approaches can optimize the WTS production, i.e. improve quality of energy produced and energy efficiency. Detailed simulation studies of WTS under various conditions are carried out in MATLAB/Simulink software, and the results confirm the robustness of the proposed control techniques.

This paper presents a comparative study between three controllers for the Doubly Fed Induction Generator (DFIG) integrated into a wind turbine system. The active and reactive powers between the stator of DFIG and the grid are controlled independently by using three control strategies, the first called the active disturbance rejection control (ADRC), the second is the classical Proportional-Integral (PI) and the third called polynomial RST controller. First, a modeling of wind turbine and DFIG is presented. Also, in order to maximize the power of wind energy conversion, the use of MPPT control is indispensable. Then, these three control strategies are designed, simulated and their performances were tested and compared in terms of instruction tracking and robustness. The simulations were realized by Matlab/Simulink software.

The work presents a new direct power command (DPC) strategy based on a second order sliding mode controller (SOSMC) of a doubly fed induction generator (DFIG) integrated in a wind energy conversion system (WECS). In the first step we propose to use a five-level inverter based on the neural space vector pulse width modulation (NSVPWM) to supply the DFIG rotor side. This is the harmonic distortion (THD) of the DFIG rotor voltage and then performs provides the power to the grid by the stator side. The traditional DPC with space vector pulse width modulation (DPC-SVPWM) using proportional-integral (PI) controllers has considerable reactive and active power oscillations at a steady-state operation. In order to ensure a robust DFIG DPC-SVPWM technique and minimize the reactive and active power ripples, a SOSMC algorithms is used in the second step. The Simulation results show the efficiency of the designed control scheme especially in terms of the quality of the provided power compared to DPC-SVPWM.

This paper deals with the speed control of a variable speed doubly-fed induction generator (DFIG)-based marine current turbine (MCT). To increase the generated power and therefore the efficiency of an MCT, a nonlinear controller has been proposed. DFIG has been already considered for similar applications, particularly wind turbine systems using mainly proportional-integral (PI) controllers. However, such kinds of controllers do not adequately handle some tidal resource characteristics such as turbulence and swell effects. These may decrease MCT performances. Moreover, DFIG parameter variations should be accounted for. Therefore, a robust nonlinear control strategy, namely high-order sliding mode (HOSM) control, is proposed. This control strategy relies on the resource and the marine turbine models that were validated by experimental data. The sensitivity of the proposed control strategy is analyzed regarding the swell effect as it is considered as the most disturbing one for the resource model. Tidal current data from the Raz de Sein (Brittany, France) are used to run simulations of a 7.5-kW prototype over various flow regimes. Simulation results are presented and fully analyzed.

This paper introduces a novel multi-stage FOPD(1 + PI) controller for DC motor speed control, optimized using the Pelican Optimization Algorithm (POA). Traditional PID controllers often fall short in handling the complex dynamics of DC motors, leading to suboptimal performance. Our proposed controller integrates fractional-order proportional-derivative (FOPD) and proportional-integral (PI) control actions, optimized via POA to achieve superior control performance. The effectiveness of the proposed controller is validated through rigorous simulations and experimental evaluations. Comparative analysis is conducted against conventional PID and fractional-order PID (FOPID) controllers, fine-tuned using metaheuristic algorithms such as atom search optimization (ASO), stochastic fractal search (SFS), grey wolf optimization (GWO), and sine-cosine algorithm (SCA). Quantitative results demonstrate that the FOPD(1 + PI) controller optimized by POA significantly enhances the dynamic response and stability of the DC motor. Key performance metrics show a reduction in rise time by 28%, settling time by 35%, and overshoot by 22%, while the steady-state error is minimized to 0.3%. The comparative analysis highlights the superior performance, faster response time, high accuracy, and robustness of the proposed controller in various operating conditions, consistently outperforming the PID and FOPID controllers optimized by other metaheuristic algorithms. In conclusion, the POA-optimized multi-stage FOPD(1 + PI) controller presents a significant advancement in DC motor speed control, offering a robust and efficient solution with substantial improvements in performance metrics. This innovative approach has the potential to enhance the efficiency and reliability of DC motor applications in industrial and automotive sectors.