Intelligent control of grid connected unified doubly-fed induction generator

Skills possessed by human welders typically require a long time to develop. Especially, maintaining the torch to travel in desired speed is challenging. In this paper, a feedback control system is designed to assist the welder to adjust the torch movement for the desired speed in manual gas tungsten arc welding process. To this end, an innovative helmet based manual welding platform is proposed and developed. In this system, vibrators are installed on the helmet to generate vibration sounds to instruct the welder to speed or slow down the torch movement. The torch movement is monitored by a leap motion sensor. The torch speed is used as the feedback for the control algorithm to determine how to change the vibrations. To design the control algorithm, dynamic experiments are conducted to correlate the arm movement (torch speed) to the vibration control signal. Linear model is firstly identified using standard least squares method, and the model is analyzed. A nonlinear adaptive neuro-fuzzy inference system (ANFIS) model is then proposed to improve the model accuracy. The resultant nonlinear ANFIS model can estimate the welder’s response on the welding speed. Based on the response model, a PID control algorithm has been designed and implemented to control the welder arm movement for desired torch speed. Experiments verified the effectiveness of the system for the desired speed with acceptable accuracy.

This paper presents a coordinated control method for a doubly-fed induction generator (DFIG)-based wind-power generation system with a series grid-side converter (SGSC) under distorted grid voltage conditions. The detailed mathematical models of the DFIG system with SGSC are developed in the multiple synchronous rotating reference frames. In order to counteract the adverse effects of the voltage harmonics upon the DFIG, the SGSC generates series compensation control voltages to keep the stator voltage sinusoidal and symmetrical, which allows the use of the conventional vector control strategy for the rotor-side converter (RSC), regardless of grid voltage harmonics. Meanwhile, two control targets for the parallel grid-side converter (PGSC) are identified, including eliminating the oscillations in total active and reactive power entering the grid or suppressing the fifth- and seventh-order harmonic currents injected to the grid. Furthermore, the respective PI-R controller in the positive synchronous reference frame for the SGSC voltage control and PGSC current control have been developed to achieve precise and rapid regulation of the corresponding components. Finally, the proposed coordinated control strategy has been fully validated by the simulation results of a 2 MW DFIG-based wind turbine with SGSC under distorted grid voltage conditions.

This paper proposes and describes the controllers for doubly-fed induction generators (DFIG) with series grid side converter. It is demonstrated that with series grid side converter instead of a conventional shunt grid side converter the DFIG stator voltage can be kept balanced even under heavy unbalance grid voltages. Therefore, in this way it is avoided the undesired effects such as torque oscillations and high stator and rotor currents presents under unbalance voltages. In addition, it is demonstrated that it is possible with a conventional back-to-back three phase PWM converter to satisfy the grid code active and reactive power requirements. The design and control of the series grid-side converter with a LC-filter will also be presented. An H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">infin</sub> controller is designed to achieve robustness as well as good tracking and disturbance rejection performance for the series voltage converter. Furthermore, the DC-link, rotor currents and active and reactive power controllers are as well described, where the controllers transfer functions are selected to ensure good performance even in the presence of grid voltage unbalance. Finally, simulation results of a 2.27 MVA wind turbine generator are presented to demonstrate the good performance of the DFIG with the proposed controllers.

Nowadays actual scientific problem of renewable energy is the problem of developing control systems, that ensure the generation of stable voltage in a changing environment. This paper presents a structure and methods of synthesis of control system development, which allow to decide the indicated problem. An electric subsystem of wind power plant is a well-known structure with well-known advantages, consisting mainly of double-fed induction generator (DFIG) and power converter in the circuit of rotor. Operation of the control system based on the original nonlinear mathematical model of DFIG in rotational dq coordinates, taking into account the nonlinear external and internal DFIG disturbances, such as inductances of coil winding, changes of coil winding resistances from temperature, etc. The study received mathematical model, adaptive control algorithms and its computer simulation of the wind turbine with DFIG. Introduction An increasing requirement in energy resources at unstable oil prices stimulate to search the alternative decisions of power problems. One of the most successfully developed types of alternative energy is wind power. Its rapid growth observed in the world, proofing an attractiveness of this technology. It is expressed in the purity, reliability and input speed. So, according to Global Wind Energy Council (GWEC), to the end of 2015 global wind power capacity will reach 609 GW, compared to 237. 4 gigawatts at the end of 2011. The three leading world markets remain the China, U. S. and Europe. In recent years, the rapid growth of installed wind power capacity turned out to be possible through the development and implementation of new technological solutions, one of which is DFIG used as generator in wind power plants(WPP). Such DFIG are widely used in powerful WPP, as they allow to convert the available wind energy more efficiently, especially in periods of weak winds. It is known that the parameters of the generated voltage depends on terms of environment. At the same time, the necessity of quality stable voltage generation sets the problem of technological decisions development, allowing to minimize influence of different factors on output voltage quality. Such a technological solution is adaptive control system (CS) of a WPP with DFIG , permitting high speed reaction to wind speed changes and the rate of the connected electrical load, thus maintaining the stability of the generator output voltage. Synthesizing an adaptive high-speed CS and using the structure of WPP with DFIG it becomes possible to design and build these types of wind turbines. Synthesis of nonlinear CS Nonlinear CS control law. The solution of the indicated problem, offered in this paper, is based on the nonlinear model of DFIG in rotational dq coordinates, as in the conditions of different disturbances, linearizing appears uneffective [1]. Because, coming from the structure of WPP, control circuit is a rotor circuit, then primary control objective is feed on it control voltage of some parameters, at that DFIG output voltage remains unchanging and corresponds to set, without depending on influences. As it applies to a model, it is necessary to get the control values of voltages International Conference on Advances in Energy, Environment and Chemical Engineering (AEECE-2015) © 2015. The authors Published by Atlantis Press 1 on the dq rotor axes dr V and qr V , at the well-known required stator voltages ref ds V and ref qs V . The classic mathematical model of DFIG does not take into account the nonlinear changes of its parameters, such as winding inductances, changes of winding resistances from temperatures etc., accepting their permanent, that is not quite right. Meantime, in real DFIG such changes have an influence on control quality, so the synthesis of control system, which is taking into account such nonlinear disturbances, is an actual task. The disturbances arising up from nonlinear character of the control object are difficult to mathematical description, however valuation of these disturbances with the subsequent bringing of adjustments in work of CS on the basis of such estimation is a fully solvable task. For this purpose, in the standard mathematical model of DFIG we will add some functions of immeasurable disturbances, and (Eq.1), accordingly for the stator d and q axes currents, and next we synthesize control laws.

This work presents the overall model of the doubly fed induction generator (DFIG) and proposes a new control design for the grid side converter of the concerned DFIG plant. The system under study consists of two DFIG wind turbines which are connected to the grid by a bi-directional Z-source inverter. In order to ameliorate the DC link voltage regulation of the DFIG generation plant; particularly, a new supervised control method is introduced and is directly applied to the grid side converter (GSC). In this way, initially, by tuning two control coefficients (CCs) which forms the footprint of uncertainty (FOU), a double-input interval type-2 fuzzy logic (DIT2-FL) is designed for the GSC system. The best setting of the control coefficients for the desired performance of the concerned system is recommended and a new DIT2-FL supervised online adaptive neuro fuzzy inference system (ANFIS) is then developed accordingly. By implementing the supervised controller, the dynamic behavior of the tested wind turbines under two distinct operations for low/high wind speeds is investigated. Detailed experimental outcomes have been presented to ascertain the correctness and accuracy of the suggested control methodology. Compared with the prevalent state-of-the-art techniques, the suggested controller leads to remarkable transient improvement of closed-loop DFIG system.<br/>

Satisfactory performance of doubly fed induction generator (DFIG) is indebted to determining the proportional-integral (PI) gains of the power electronic converter controls as accurate as possible to guarantee minimum transients when disturbances occurred in the power system. Since the DFIG is introduced as a dynamical system, PI gains must be changed according to the system requirements. Fuzzy controllers designed based on our best knowledge on the system behavior are able to continuously adjust parameters of the control system to enhance the performance of the system. In this paper, a control scheme based on self-tuning fuzzy PI (STFPI) is proposed to control the power electronic converters of the DFIG. Different arrangements of the STFPI controller are considered in the control scheme of active and reactive power. The performances of the DFIG in three operating modes are compared when the STFPI and the conventional PI are installed and the system experiences a single phase to ground short circuit fault. Super-synchronous, synchronous, and sub-synchronous operating modes are examined in the paper. The idea is implemented on a study system equipped with a DFIG wind turbine, and the obtained results show that when the proposed scheme is employed a superior performance can be achieved in transient conditions and the transients are significantly improved. Copyright © 2014 John Wiley & Sons, Ltd.

© 2017 IEEE. In this paper, a harmonic mitigation technique is introduced to the doubly fed induction generator (DFIG) based wind energy conversion system (WECS) by modifying its grid side converter (GSC) classical control. When this technique implemented, the DFIG's GSC acts like an active power filter, which compensates for current harmonics generated by a nonlinear load connected to the point of common coupling (PCC), in addition to its primary purposes which are maintaining the dc-link voltage constant and ensuring unity power factor operation with the grid. This technique is simple, easy to be integrated with the existing system, and has the ability to compensate for the current harmonics even if the generator is in brake mode. Moreover, a robust control method is applied to DFIG's rotor side converter (RSC) to verify that the proposed technique does not affect the DFIG system nominal operation. Experimental results show that the proposed DFIG technique reduces the current total harmonic distortion (THD) at PCC.

This paper presents a new configuration of doubly fed induction generator (DFIG)-based wind farm with multilevel cascaded H-bridge (CHB) converter and its control system, which is suitable not only for unbalanced grid voltage conditions, but also for small voltage sags. The proposed configuration of DFIG can balance the point of common coupling (PCC) voltage without needing additional DC link capacitor or energy storage unlike other configurations and methods. Consequently, the stator voltage and the other loads voltage connected to the PCC are kept constant at the nominal value. The new configuration improves all the DFIG signals under unbalanced grid voltage and small voltage sag conditions unlike other methods. Some of the DFIG units in wind farm require to connect the CHB converter, therefore, it is cost-effective. Matlab/Simulink is used for simulation of a 13.5-MW wind farm consisting of nine 1.5-MW DFIG units and the results demonstrate the good efficiency of the proposed scheme.

With steadily increasing wind turbine penetration, regulatory standards for grid interconnection have evolved to require that wind generation systems ride-through disturbances such as faults and support the grid during such events. Conventional modifications to the doubly fed induction generation (DFIG) architecture for providing ride-through result in compromised control of the turbine shaft and grid current during fault events. A DFIG architecture in which the grid side converter is connected in series as opposed to parallel with the grid connection has shown improved low voltage ride through but poor power processing capabilities. In this paper, a unified DFIG wind turbine architecture which employs a parallel grid side rectifier and series grid side converter is presented. The combination of these two converters enables unencumbered power processing and robust voltage disturbance ride through. A dynamic model and control structure for this architecture is developed. The operation of the system is illustrated using computer simulations.

The growth rate of penetration of wind energy has addressed many challenges and impacts related to the power quality and power system stability because of its intermittent nature. Once a doubly fed induction generator (DFIG) is connected to a power system, it absorbs lagging reactive power during the grid operation causing instability issues to the grid voltages. In this research paper, a DFIG based wind turbine is being modeled considering the optimal power coefficient and reactive power control strategy. The optimal power coefficient correlates the power law exponent with the respect of velocity and elevation. The reactive power control strategy is modeled using back-to-back converter system. The paper also investigates the voltage improvement of a large distribution network connected with DFIG system. By using steady state analysis, the voltage magnitude profiles are determined during DFIG at point of common coupling. The proposed control shows that DFIG based wind-turbine integration to the large distribution network enhances the weak bus voltage.

Harmonics forecasting stands as a crucial approach in the development of devices aimed at minimizing harmonics disturbances. The primary objective of this study is to create a hybrid forecasting model that can deliver precise and dependable forecasts for harmonics in Renewable Energy Systems (RES). To achieve this goal, the Adaptive Neuro Fuzzy Inference System (ANFIS) with the Long Short-Term Memory Network (LSTM) are combined in two distinct structured models. In the first model, LSTM is employed in the initial stage and ANFIS in the subsequent one, while the second model follows the reverse order. Additionally, for the generation of harmonics, two renewable generator models are utilized. The first model encompasses a grid-connected Double-Fed Induction Generator (DFIG) driven by a wind turbine and integrated with a Solar Photovoltaic (PV)-based power generator. The second generator model combines a Solar-PV generator with a wind turbine-linked Permanent Magnet Synchronized Generator (PMSG) connected to a shared grid. The harmonics produced by these generator models are used to construct training and testing datasets, which are subsequently employed for generating forecasts using the proposed hybrid forecasting models. The accuracy of forecasting results is verified through a comparison with benchmark studies in the literature. The findings reveal that the model employing ANFIS in the initial stage and LSTM in the second stage (referred to as the ANFIS-LSTM model) consistently yields the best forecasts among all the models tested in this study. Moreover, it exhibits a significant improvement over any of the techniques used in previous literature. Ultimately, this research establishes that both hybrid models proposed outperform the individual forecasting techniques used as benchmarks in terms of accuracy and precision.

In complex industrial processes (CIPs), due to technical and economic limitations, key performance indicators (KPIs), especially the chemical content-related KPIs, are often difficult to measure in real time, which hinders the propagation of advanced process control technologies. This paper presents a soft sensor-based online KPI inference scheme by a state transition algorithm (STA)-optimized adaptive pre-sparse neuro-fuzzy inference system model, called STA-APSNFIS. It introduces a pre-sparse neural network to the traditional adaptive neuro-fuzzy inference system (ANFIS) model to establish an adaptive pre-sparse neuro-fuzzy inference system (APSNFIS) model to alleviate the adverse effects of data redundancy and noise interference in the detectable process monitoring data, which can effectively reduce the complexity of neuro-fuzzy inference system (NFIS) and speed up its convergence. Successively, to avoid being trapped at a local optimum, the STA-based optimization algorithm is adopted to replace the traditional gradient-based optimization approach to achieve an optimal APSNFIS model. Extensive validation and comparative experiments on nonlinear numeric simulation systems, benchmark Tenessee Eastman (TE) process and a real industrial bauxite flotation process demonstrated that the proposed STA-APSNFIS performed favorably against traditional ANFIS model as well as its variants, e.g., PSO-ANFIS, GA-ANFIS, and some other soft sensor-based KPI inference models.

The safe and stable operation of the power system has become an increasingly critical issue as the large-scale of wind power integration and its long-distance transmission. Splitting control (or islanding control) of the power system is an important prevention measure to mitigate the system collapses. In general, the oscillation center (i.e. the point of which voltage is the lowest in the power gird) is applied to searching the splitting boundary. However, fast responses, low inertia, and asynchronous operation of the doubly fed induction generator (DFIG) might change the migration mechanism of oscillation centers. This paper tries to analyze the impact of DFIG characteristics on oscillation center migration. First, Thevenin equivalent circuit equation of DFIG is established, based on which the characteristic admittance of DFIG under out-of-step oscillation is analyzed. Then by substituting the characteristic admittance of DFIG into the oscillation center migration function, results manifest that the distribution range of the oscillation center is extended, and the splitting location keeps away from the point of common coupling (PCC). Finally, simulations on 2-area 4-machine system and IEEE 118-bus system integrated with wind farms verify the correctness and effectiveness of the theoretical analysis.

Since 2004, Doubly Fed Induction Generator (DFIG) has become the most admired wind turbine generator type that is widely installed worldwide. The popularity of DFIG is due to its capability to extract more energy than fixed speed wind turbine generator type. Moreover, a DFIG requires only one-third of the full converter size used by type-4 wind turbine generator which in turn reduces the total cost of DFIG installation. The main weakness of DFIG is its vulnerability to grid faults such as voltage dip and swell. Grid faults may have adverse impacts on the overall performance of the DFIG including the voltage at the point of common coupling that, at certain fault levels, may violate the permissible margins of the grid codes established by the transmission line operators. This paper investigates the application of Superconducting Magnetic Energy Storage (SMES) unit to improve the fault ride-through capability of a DFIG during grid faults. Results show that the connection of a SMES unit at the point of common coupling between the DFIG and the grid can enhance the overall performance of the DFIG during such faults events.

Temporary islanding of offshore wind farm will happen owing to the HVDC (High Voltage Direct Current system) blocking while transient DC-fault occurs in the connected FB-MMC (Full Bridge Modular Multilevel Converter) HVDC system. As the mainstream of offshore wind farm, DFIG (Doubly Fed Induction Generator) has defects under islanding conditions in control strategy, which causes the phenomena of overvoltage and instantaneous impulse current in PCC (Point of Common Coupling) node, threating to security of both HVDC and wind-farm. This paper analyzes response of DFIG under temporary islanding in detail and proposes a solution of transient DC FRT (Fault Ride Through) for DFIG, which is verified by simulation on PSCAD/EMTDC.