The regional grid codes mandate that wind energy conversion systems (WECSs) stay connected during grid faults as long as terminal voltages stay above a specified level with respect to the fault duration. While existing low-voltage ride-through (LVRT) strategies for DFIG-WECSs satisfy these requirements, they do not guarantee maximum AC bus voltage recovery, which is essential for maintaining grid connectivity during severe faults. This paper presents an LVRT strategy for an on-grid DFIG supplying an AC microgrid. Rotor and stator overcurrent in the initial fault stage are limited using a crowbar. Then, a proposed coordinated RSC-GSC control aligns the DFIG-stator and transformer HV-side currents, maximizing the resultant AC bus injected current. Next, a modified adaptive voltage support scheme further maintains optimal real-time d-q current ratios for both converters (utilizing full capacity), so that overall injected current matches the network X/R ratio, ensuring maximum voltage recovery, regardless of the fault level, duration, location, wind speed, and wind farm condition. OPAL-RT real-time simulations confirm a 5.90% improvement in AC-bus voltage recovery and an 82% enhancement in post-fault transient response over recent literature.

Wind Energy Conversion systems (WECS), supplying islanded microgrids, often incorporate a Battery Energy Storage System (BESS) as an energy-buffer. To ensure safety and long life, the battery-bank (BB) in such systems must not be overcharged or deep-discharged. This paper proposes a reconfigurable operational strategy for a doubly-fed induction generator (DFIG) based islanded WECS integrated with a BESS. When the State-of-Charge (SoC) of the BB approaches the maximum limit, the rotor side converter regulates the DC bus voltage using a modified voltage controller while operating the DFIG away from the Maximum Power Point. When the BB-SoC approaches the minimum limit, a minimum consumer-discomfort factor based load-shedding strategy is proposed so that the BESS can regulate the DC-bus voltage without deep discharging the BB. The DFIG-BESS system supplying the benchmark CIGRE residential distribution network has been simulated in an Opal-RT real-time simulation environment. The proposed voltage controller shows 69.44% and 46.66% lower undershoot in the DFIG-stator active-power and 3.45% and 99.83% lower DC-voltage deviation compared to a PI-controller and latest literature, respectively, while transiting from the BESS to RSC based DC-bus voltage regulation. The proposed load-shedding strategy also reduces the DC-bus voltage dip significantly compared to a similar strategy proposed in the literature.

The doubly-fed induction generator (DFIG) based wind energy conversion system (WECS) is a mature and promising renewable energy solution amid growing global energy demand. As supply reliability and system resiliency become increasingly important, low voltage ride-through (LVRT) capability has become mandatory for such systems. During a voltage dip at the AC bus, where the WECS delivers power, it must stay connected and aid voltage recovery by supplying reactive power, as per local grid standards. While ON-grid LVRT strategies have been extensively researched, OFF-grid LVRT operations have received little attention. For greater source reliability, WECSs should also operate in OFF-grid mode, where similar voltage dip issues can arise. This paper proposes a hybrid LVRT strategy for DFIG-WECS in OFF-grid mode. A battery energy storage system (BESS) maintains the DC bus voltage, while a grid-forming converter (GFC) holds the AC bus voltage with its limited current capacity. The DFIG rotor disconnects from the rotor side converter (RSC) and connects to a crowbar during the voltage fall and rise period. Between these two periods, the DFIGRSC provides reactive power. The method is validated using a MATLAB/SIMULINK model in an OPAL-RT real-time simulation, demonstrating that under different wind velocities, the OFF-grid DFIG-WECS withstands different levels of voltage dips while supporting voltage recovery.

This paper presents an automated power balancing approach for DC bus voltage regulation in an on-grid solar-wind integrated hybrid microgrid (HMG), assisted by a battery energy storage system (BESS). The latest reported work is limited to either a fixed reduction in the controllable variable (to reduce the source power generation during maximum SoC condition of the battery) or with an adaptive approach but applicable to a single source only. This work has automated the HMG-BESS operation using an adaptive strategy based on real-time battery-SoC condition, applicable to any number of controllable sources in the HMG. In HMG, to ensure a stable operation of the wind energy conversion system and solar photovoltaic system, the control strategy dynamically adjusts power flow by either operating all available sources in OFF-maximum power point mode at high SoC or reducing power supply to the grid at low SoC. Unlike existing studies focusing only on a single-source regulation approach, this work integrates multiple energy sources, enhancing the system's reliability. Opal-RT RTDS based simulation results demonstrate that the proposed automated control mechanism maintained the DC bus voltage regulated within × 4% and the battery SoC within 20% to 80%, utilizing the maximum possible available sources and ensuring seamless microgrid operation under varying wind velocity (7m/s-11m/s), solar irradiance (300w/m2-900w/m2), and load (3.1kW-16kW) conditions.

This paper proposes a jellyfish search algorithm (JSA)-based offline method to design a DC voltage controller of AC/DC front-end converter (FEC) in a doubly fed induction generator (DFIG)-based wind energy conversion system (WECS). First, a multi-objective tuning problem is formulated using a full-order converter model to achieve maximum utilization of converter parameters in controller design. Next, a normalized mono-objective problem is developed using a utopia-tracking approach to reduce the computational complexity in design. Finally, the mono-objective problem is solved using JSA to enhance the controller performance by obtaining optimal gain values for the controller. A comparative study is performed with other metaheuristic optimization techniques to justify the use of JSA in this application. The results confirm that the accuracy of the JSA-based approach is higher, whereas the execution time of the method is lower than the other methods. Furthermore, to validate the performance of the proposed approach, a DFIG-based WECS is modeled and simulated using OPAL-RT real-time simulator. A grid voltage-oriented vector control is used as the overall control algorithm for the FEC. Unlike the conventional pole-zero cancellation method, the proposed approach provides no voltage overshoot during voltage development. Compared to the published literature, it also ensures 40.65% lesser voltage deviation without any overcurrent, irrespective of wind speed and load variations.

In a wind energy conversion system (WECS) based on a doubly fed induction generator (DFIG), a fast and smooth automatic synchronization of the DFIG with the utility grid is always desirable. Additionally, elimination of the need for a speed encoder makes the synchronization process much more reliable. This paper proposes a modified voltage controller-based automatic grid-synchronization strategy for the DFIG-WECS using a rotor-current-dependent model-reference-adaptive-system (MRAS) for rotor-speed/position estimation. A V/f control-based starting strategy is used to start the DFIG. An improved decoupled DFIG stator voltage controller is proposed to enhance the transient response during the DFIG grid synchronization. The modified controller is implemented in a grid-voltage-oriented reference frame to synchronize the DFIG-stator with the grid. A robust modified MRAS with higher noise immunity and reduced machine parameter dependency is used to estimate the rotor-speed/position during synchronization control. To validate the performance of the proposed strategy, a DFIG-based WECS is modeled and simulated using an OPAL-RT real-time simulator, where a motor-generator setup is modeled to have an equivalent WECS configuration. As compared with the latest reported work, this approach reduces the synchronization time by 16.99% while ensuring a smooth synchronization with no stator inrush-current, even without any speed/position encoder.

This paper proposed a battery (in battery energy storage system (BESS)) state-of-charge (SoC-based control strategy to address the power imbalance issue in the wind energy conversion system (WECS), especially for the doubly-fed induction generator (DFIG)-based WECS, keeping the battery safe under any condition. Unlike the latest reported work, where a fixed rotor-current-gain or manual operation-based strategy (to reduce the DFIG power generation or power export to the grid) is presented, this work has automated the DFIG-BESS-WECS operation, using a reconfigurable control strategy based on real-time battery-SoC condition. If the battery-SoC approaches the maximum limit, the BESS immediately stops charging the battery further. The DC bus is then maintained by the DFIG-rotor side converter, operating the DFIG in the off-MPP (maximum power point) mode. If the battery-SoC approaches the minimum limit, the BESS immediately stops discharging the battery further, and the DC bus is then maintained by the grid-side interlinking converter, reducing the grid-power export to a lower maximum permissible value. To validate this strategy, the DFIG-BESS-WECS is modeled in MATLAB/Simulink environment and simulated in Opal-RT real-time simulator. Simulation results show that regardless of wind velocity and load variations, the battery SoC is maintained within a safe range while utilizing the maximum possible wind energy. The DC bus voltage is also regulated throughout the operation.

In recent years, there has been a persistent increase in energy demand and at the same time extinction of conventional resources for energy requirements shooting up the gap between demand and supply of energy. However, the most prominent and eco-friendly energy resources, viz., solar photovoltaic (SPV), wind energy systems (WES), fuel cells, biomass, etc., are paving way for the fulfillment of energy demand. PV and wind are abundant and freely accessible resources in nature. The ensemble of these two sources remains challenging to attain a satisfactory level of sustainability and power quality. Therefore, there is a need for an intellectual method to fulfill the requirements of reliability, sustainability, and the highest quality power for the power grid and domestic loads. In this work, we develop a mechanism to facilitate the tracking of maximum power (MPPT) against the power produced by the combination of SPV and wind turbines (WT) by adopting a common ensemble point. Further, a single-stage converter in association with a proportional resonant (PR)-dependent current control circuit is employed to supply reliable and maximum power to the grid. In the present system, high costs enable the minimum battery utilization and facilitate the maximum power transfer from solar and wind sources to the grid using an intelligent algorithm. Further, the converter reference tracking performance is improved with the aid of the PR controller. This manifests as a better replacement for the shortcomings of conventional PI control as directed by IEEE standards. The entire system proposed in this work was designed and implemented by using MATLAB/Simulink environments to accomplish the task. The final outcomes of the proposed system as directed by the MATLAB simulations are executed for 1 kW, and the results depicted the performance and efficacy of the controller and the adaptive behavior of the grid coupled with the PV-wind ensemble system.

The wind energy conversion system (WECS) is one of the most developed renewable energy sources. In WECS, the doubly-fed induction generator (DFIG) has become the leader among all the types of generators, due to several advantages. For control of DFIG, rotor speed and position data are required. These data can be collected either using speed/position sensors or can be estimated using already available sensed parameters. Due to the issues related to robustness, economy, cabling, and maintenance, of speed-transducers or position-encoders, the speed/position sensor-less techniques are expected in DFIG-WECS control. In this paper, a Modified Rotor-Current-dependent Model reference adaptive system (MRAS) Observer (MRCMO) based estimation technique is proposed with improved rotor speed estimation. In the proposed method stator voltage, stator current, and rotor current data are used to estimate rotor position and speed using one additional estimator structure to the existing Rotor-Current based MRAS Observer (RCMO). To validate this modified technique, one comparative case study is carried out with the existing RCMO approach, in MATLAB/Simulink platform.

The water-crisis is one of the biggest issues in India, where 18% of the world-population has only 4% of the world’s freshwater. Again, among this ground freshwater, 80% is used in agricultural purposes. In India, rice is one of the chief grains and it has a time varying requirement of cultivation-water. This paper proposes a grid-connected hybrid system where a solar-photovoltaic (PV) system is used to drive an induction-motor (IM)-based pump with a proposed topology, where the supply of water is according to the water-demand, to reduces the wastage of water. This topology also includes a web-server-based hybrid energy management scheme. One model reference adaptive system (MRAS)-based speed-sensor-less vector-control with closed-loop water level controller is used here. The web-server-based topology not only helps to run the pump using the economical available power source, which is decided by the weather report predictive analysis, but it also helps to monitor and control the entire system remotely. The proposed system has been simulated by MATLAB/Simulink in a wide range of water discharge and speed variations. Then, the appropriateness of that system has been verified by the practical data of an agricultural water pump.

Ever-growing penetration of wind energy conversion systems (WECS) into the grid, has made their continuous operation compulsory, even during sudden dips in the grid voltage. Also, they should deliver reactive power for better voltage recovery during the voltage dip. This capability of remaining connected and supporting reactive power to the grid during a sudden voltage dip, is defined as low voltage ride through (LVRT). Various international grid codes have been introduced on LVRT of grid-connected WECS, to maintain the power system stability. Doubly fed induction generators (DFIGs) are extensively used in high and medium power WECS applications, due to its several advantages. But the DFIG, is very much grid-sensitive, due to the presence of a direct link between DFIG-stator and the grid. So, along with the development of DFIG-WECS, a comprehensive understanding of proper LVRT topology selection, is also becoming much important. In this paper, various external configuration based LVRT solutions for DFIG, are compared in MATLAB / Simulink environment.

Environmental pollution is one of the serious issues in the current era. In diminishing this issue, electric vehicles (EVs) can play one key role. Again, along with the development of modern drive technologies in various electric traction applications, a comprehensive understanding of proper motor selection, is also becoming much important. This paper compares induction motor (IM), brushless DC (BLDC) motor and permanent magnet synchronous motor (PMSM) for EV traction applications. In this study, field-oriented control (FOC) strategy with ANN based controller, is chosen due to its accuracy, fast dynamical response and ease of proper torque and speed control. This comparative study and the model simulation has been carried out in the MATLAB/Simulink environment.

In this paper, a modified hybrid synchronization technique to improve the synchronization process and one power control and management scheme during normal and abnormal condition of a single-phase grid connected solar photovoltaic (SPGCSPV) system have been proposed. Generally, ZCD (Zero Crossing Detection) and second-order generalized integrator (SOGI) based phase-locked loops (PLLs) are widely used for grid synchronization in SPGC inverter. However, adaptive notch filter (ANF) based algorithm is also gaining attention due to its simplicity and accuracy. In this work, to improve the synchronization technique with reduced steady state phase error, reduced allowable lock range and improved synchronization speed, an amplitude adaptive notch filter (AANF) is used with combining PLL with it, to implement a new AANF-PLL with control in d-q (direct-quadrature) frame. It gives very good response with the voltage and frequency variation. Further, modified technique can also be used in the detection of signal amplitude, harmonics, frequency, and control of power. The simulation study of the SPGCSPV system has been done using MATLAB/SIMULINK environment followed by hardware implementation for performance monitoring, anti-islanding, and low voltage ride through (LVRT) capability testing.

Due to ever increasing energy demand and depletion of conventional energy resources, there is a need to generate and fulfill this gap, using clean and green energy resources such as Solar Photo-Voltaic (SPV), Wind Energy System (WES), Fuel Cell and Biomass etc. PV and Wind are abundantly and easily available in the nature. Combining these two intermittent sources are always challenging in the term of sustainability and power quality, so an intelligent technique is required for supplying the reliable, sustainable, and maximum quality power to the power grid and domestic load. In this paper, the power generated by SPV and Wind Turbine (WT) with Maximum Power Point Tracking (MPPT) has been collected on the common coupling point. Then single stage converter along with Proportional-Resonant (PR) based current controller has been used to transfer reliable and maximum power to the grid, in MATLAB/SIMULINK environment. In this system, due to high cost, battery utilization has been minimized and intelligent algorithm has been adopted to transfer maximum available solar and wind power into the grid. Further, using the PR controller, the converter reference tracking performance has been enhanced and shortcoming associated with conventional PI control has been alleviated for reliable and stable grid connection as per the IEEE standards. The simulation results of 1 kW show the control performance and dynamic behavior of the grid interfaced PV-wind system.