The doubly fed induction generator (DFIG)-based wind energy conversion systems (WECSs) are prone to certain uncertainties, nonlinearities, and external disturbances. The maximum power transfer from WECS to the utility grid system requires a high-performance control system in the presence of such nonlinearities and disturbances. This paper presents a nonlinear robust chattering free super twisting fractional order terminal sliding mode control (ST-FOTSMC) strategy for both the grid side and rotor side converters of 2 MW DFIG-WECS. The Lyapunov stability theory was used to ensure the stability of the proposed closed-loop control system. The performance of the proposed control paradigm is validated using extensive numerical simulations carried out in MATLAB/Simulink environment. A detailed comparative analysis of the proposed strategy is presented with the benchmark sliding mode control (SMC) and fractional order terminal sliding mode control (FOTSMC) strategies. The proposed control scheme was found to exhibit superior performance to both the stated strategies under normal mode of operation as well as under lumped parametric uncertainties.

In the direct torque control (DTC) of induction motor (IM) drive systems utilizing model predictive torque control (MPTC) in the inner loop and classical proportional integral (PI) control in the outer loop is prone to weaknesses, such as uncertainties, external disturbances, parameter variations, and nonlinear dynamics. A high-performance control system for speed and torque is required to guarantee a smooth and robust control architecture that can withstand such unpredictable effects. In this study, we propose an integral super twisting sliding mode control (ISTSMC) to address the shortcomings of the classical PI used in the outer loop of DTC drive systems. A sliding mode speed observer is also designed and utilized to overcome problems associated with mechanical sensors. The robustness of the proposed control strategy and fast dynamic speed response are compared favorably with a benchmark PI controller and conventional sliding mode control (SMC). The ability of the proposed system to regulate both speed and torque was evaluated through simulations, under various fault perturbations, parameter variations, and load disturbances, conducted in MATLAB/ Simulink. Various performance indices were used to demonstrate the superior performance of the proposed strategy compared to a benchmark PI system and conventional SMC-based MPTC approaches.

The penetration of renewable energy sources on a large scale in conventional electric networks increases exponentially for environmental preservation. However, the increase in RESs leads to some technical problems that include (a) fluctuations in power production, (b) less or no generation units for power balancing, (c) reduced inertia due to RESs decoupling from the conventional grid using converters. Micro-hydro power plants (MHPPs) are emerging as a mature balancing technology and a great alternative to large hydropower plants as they encounter population displacement and many environmental problems. Modern pump storage MHPPs uses a power converter between the grid and machine to control the consumption of power during pumping mode. This power electronic interface loses the ability of the rotating mass of the machine to contribute to the grid inertia by making it independent of the grid frequency. This problem is solved through the control of power converters in such a way that the inertia effect is synthesized termed as synthetic inertia. MHPPs can also be operated in a standalone mode where they are not connected to the grid. This paper reviews control schemes applied in literature for the frequency, voltage, and inertia control, in both the grid-connected and standalone modes. This study starts with the standalone MHPPs, covering the literature review and control structure for voltage and frequency control of standalone MHPPs. Then it presents a detailed operation, control principle, synthetic inertia concepts, and architecture of grid-connected MHPPs. The mathematical formulation of the grid, permanent magnet synchronous generator, synthetic inertia inclusion, and control structures, including direct torque control, virtual synchronous machine, and model predictive control, is also presented. Finally, the paper presents the concluding remarks with the comparative analysis of various control structures to include synthetic inertia, its suitability, and future scope for MHPPs.

This paper proposes an artificial intelligence integrated (AI) fractional order robust control for a DFIG based wind energy conversion system. To reduce the chattering phenomena in the excitation signal, fuzzy system is employed for the adaptive adjustment of the discontinuous control gain while preserving the robustness of the closed-loop system. The stability of the closed loop system with fuzzy fractional order robust control (FFORC) is ensured using fractional order Lyapunov system. The proposed FFORC control scheme is tested using processor in the loop (PIL) experiment.MATLAB/Simulink environment is used to emulate DFIG based wind energy system and a Texas Instrument (TI) DSP320F37D processor is used for interfacing the proposed control scheme with the emulated DFIG model in Simulink environment. System performance under the proposed FFORC scheme is compared with classical sliding mode control(SMC).The experimental results justifies the superiority of the proposed FFORC control scheme under all test conditions.Under ideal condition and with the proposed FFORC control scheme, the speed tracking error is approximately zero while with SMC method the peak tracking error is 0.4 radian/s. Similarly the active and reactive powers tracking is smooth with the proposed control system, while with SMC method the reactive power oscillates on both sides of the reference and it reaches 0.01 kVAR on positive side and -0.01kVAR on the negative side of the plot.Under parameters variation, system with FFORC control scheme offers minimum steady state error which is about 0.01 radian/s, while in case of SMC with saturation function a peak value of 0.6 radian/s is recorded. In case of SMC with sgn function, the speed tracking error is around 0.1 radian/s.Moreover the proposed FFORC scheme exhibits minimum chattering.

The smooth and robust injection of wind power into the utility grid requires stable, robust, and simple control strategies. The super-twisting sliding mode control (STSMC), a variant of the sliding mode control (SMC), is an effective approach employed in wind energy systems for providing smooth power transfer, robustness, inherent chattering suppression and error-free control. The STSMC has certain disadvantages of (a) less anti-disturbance capabilities due to the non-linear part that is based on variable approaching law and (b) time delay created by the disturbance and uncertainties. This paper enhances the anti-disturbance capabilities of STSMC by combining the attributes of artificial intelligence with STSMC. Initially, the STSMC is designed for both the inner and outer loop of a doubly fed induction generator (DFIG) based wind energy conversion system (WECS). Then, an artificial neural network (ANN)-based compensation term is added to improve the convergence and anti-disturbance capabilities of STSMC. The proposed ANN based STSMC paradigm is validated using a processor in the loop (PIL) based experimental setup carried out in Matlab/Simulink.

This article formulates a fully-distributed and delay-tolerant secondary control scheme for droop-controlled AC microgrids. The proposed strategy is inspired by the cooperative control concept of multi-agent systems (MASs). It considers the hierarchical control structure of the distributed energy resource (DER) units. It ensures equal active power sharing between three DER units, where each unit tracks the time-varying average load, with a finite-time convergence. As a result, the frequencies of the DER units are regulated to their nominal values. Furthermore, it offers plug-and-play capability for DER units, demonstrates significant robustness against load disturbances, and successfully tolerates, small as well as large, communication time-delays. Due to the fully-distributed configuration of the proposed control strategy, each DER unit in the test microgrid requires only its own information and information of its neighbors. The benefit is two-fold: not only this configuration assists in minimizing the overall bandwidth requirement, and cost of the corresponding communication network, but also it increases the reliability of the microgrid operation. The performance and effectiveness of the proposed technique is supported by exhaustive numerical simulations performed in Matlab/Simulink on an AC microgrid testbench comprising three DER units. The proposed strategy renders the superior performance in several aspects as compared to the existing developments in the literature in this area.