Optimizing the Dynamic Performance of a Wind Driven Standalone DFIG Using an Advanced Control Algorithm

The article seeks to improve the dynamic performance of a standalone doubly fed induction generator (DFIG) which driven by a wind turbine, with the help of an effective control approach. The superiority of the designed predictive controller can be confirmed through evaluating the performance of the DFIG under other control algorithm, which is the model predictive direct torque control (MPDTC), model predictive current control (MPCC) as classic types of control. Firstly, the operating principles of the two controllers are described in details. After that, a comprehensive comparison is performed among the dynamic performances of the designed MPDTC, MPCC techniques and the predictive control strategy, so we can easily present the merits and deficiencies of each control scheme to be able to easily select the most appropriate algorithm to be utilized with the DFIG. The comparison is carried out in terms of system simplicity, dynamic response, ripples’ content, number of performed commutations and total harmonic distortion (THD). The results of the comparison prove the effectiveness and validation of our proposed predictive controller; as it achieves the system simplicity, its dynamic response is faster than that of MPDTC and MPCC, it presents a lower content of ripples compared to MPDTC and MPCC. Moreover, it can minimize the computational burden, remarkably. Furthermore, the numerical results are showing a marked reduction in the THD with a percentage of 2.23 % compared to MPDTC and 1.8 % compared to MPCC. For these reasons, it can be said that the formulated controller is the most convenient to be used with the DFIG to achieve the best dynamic performance

Dynamic Performance Analysis of a Five-Phase PMSM Drive Using Model Reference Adaptive System and Enhanced Sliding Mode Observer

This paper aims to evaluate the dynamic performance of a five-phase PMSM drive using two different observers: sliding mode (SMO) and model reference adaptive system (MRAS). The design of the vector control for the drive is firstly introduced in details to visualize the proper selection of speed and current controllers’ gains, then the construction of the two observers are presented. The stability check for the two observers are also presented and analyzed, and finally the evaluation results are presented to visualize the features of each sensorless technique and identify the advantages and shortages as well. The obtained results reveal that the de-signed SMO exhibits better performance and enhanced robustness compared with the MRAS under different operating conditions. This fact is approved through the obtained results considering a mismatch in the values of stator resistance and stator inductance as well. Large deviation in the values of estimated speed and rotor position are observed under MRAS, and this is also accompanied with high speed and torque oscillations

Robust Flux and Speed State Observer Design for Sensorless Control of a Double Star Induction Motor

In this paper, a robust flux and speed observer for sensorless control of a double star induction motor is presented. Proper operation of vector control of the double star induction motor requires reliable information from the process to be controlled. This information can come from mechanical sensors (rotational speed, angular position). Furthermore, mechanical flux and speed sensors are generally expensive and fragile and affect the reliability of the system. However, the control without sensors must-have performance that does not deviate too much from that which we would have had with a mechanical sensor. In this framework, this work mainly deals with the estimation of the flux and speed using a robust state observer in view of sensorless vector control of the double star induction motor. The evaluation criteria are the static and dynamic performances of the system as well as the errors between the reference values and those estimated. Extensive simulation results and robustness tests are presented to evaluate the performance of the proposed sensorless control scheme. Furthermore, under the same test conditions, a detailed comparison between the proposed state observer and the sliding mode-MRAS technique is carried out where the results of its evaluation are investigated in terms of their speed and flux tracking capability during load and speed transients and also with parameter variation. It is worth mentioning that the proposed state observer can obtain both high current quality and low torque ripples, which show better performance than that in the MRAS system

Performance Enhancement of a Variable Speed Permanent Magnet Synchronous Generator Used for Renewable Energy Application

The paper aims to develop an improved control system to enhance the dynamics of a permanent magnet synchronous generator (PMSG) operating at varying speeds. The generator dynamics are evaluated based on lowing current, power, and torque ripples to validate the effectiveness of the proposed control system. The adopted controllers include the model predictive power control (MPPC), model predictive torque control (MPTC), and the designed predictive voltage control (PVC). MPPC seeks to regulate the active and reactive power, while MPTC regulates the torque and flux. MPPC and MPTC have several drawbacks, like high ripple, high load commutation, and using a weighting factor in their cost functions. The methodology of designed predictive voltage comes to eliminate these drawbacks by managing the direct voltage by utilizing the deadbeat and finite control set FCS principle, which uses a simple cost function without needing any weighting factor for equilibrium error issues. The results demonstrate several advantages of the proposed PVC technique, including faster dynamic response, simplified control structure, reduced ripples, lower current harmonics, and decreased computational requirements when compared to the MPPC and MPTC methods. Additionally, the study considers the integration of blade pitch angle and maximum power point tracking (MPPT) controls, which limit wind energy utilization when the generator speed exceeds its rated speed and maximize wind energy extraction during wind scarcity. In summary, the proposed PVC enhanced control system exhibits superior performance in terms of dynamic response, control simplicity, current quality, and computational efficiency when compared to alternative methods

Enhancing the Performance of Power System under Abnormal Conditions Using Three Different FACTS Devices

In this paper, a comparison between Flexible Alternating Current Transmission System (FACTS) devices including Static Synchronous Compensator (STATCOM), Static Synchronous Series Compensator (SSSC) and Unified Power Flow Controller (UPFC) for providing a better adaptation to changing operating conditions and improving the usage of current systems. The power system using FACTS devices is presented under different conditions such as single phase fault and three phase fault. A digital simulation using Matlab/Simulink software package is carried out to demonstrate the better performance including the voltage and the current of the presented system using FACTS that located between buses B1 and B2 under different faults types. The results obtained investigate that the presented system gives better response with FACTS as compared to not using them under abnormal conditions besides, the UPFC gives better performance of power system under several faults as compared to STATCOM or SSSC as It can absorb reactive power in a manner which significantly reduced the fault current. It is demonstrated that UPFC can reduce the peak fault current at bus B1 ‎to 63.85% of its value without ‎using FACTS devices under line to ground fault and 79.18% under three line to ‎ground fault whereas STATCOM and SSSC reduce it ‎to (75.21, 94.35%) and (75.40, 94.68%), respectively

Enhanced Control and Power Management for a Renewable Energy-Based Water Pumping System

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A distributed architecture of parallel buck-boost converters and cascaded control of DC microgrids-real time implementation

To enhance the stability and reliability of the system, the converters’ parallel operation can be cascaded to address the constraints posed by the substantial integration of renewable resources. Buck-boost DC-DC converters are often controlled via a cascaded control approach to allow parallel operation. The converter’s output current and its voltage will be controlled by nested loop control. This study proposes adaptive droop control parameters that are updated and verified online using the principal current sharing loops to minimize the fluctuation in load current sharing. When the converters in the microgrid are paralleled, load sharing will be accomplished using the droop control approach in addition to nested proportional-integral-based voltage and current control loops. To restore the correct voltage across the DC microgrid, an outer addition voltage secondary loop will be used, rectifying any voltage disparities caused by the droop management strategy. Several common load resistances and input voltage variations are used to test the suggested method. Using a linearized model, this work assesses the stability and performance of the proposed method. It then confirms the findings with an adequate model created in MATLAB/SIMULINK, Real-Time Simulation Fundamentals, and hardware-based experiments

Enhancing the control of doubly fed induction generators using artificial neural networks in the presence of real wind profiles

This study tackles the complex task of integrating wind energy systems into the electric grid, facing challenges such as power oscillations and unreliable energy generation due to fluctuating wind speeds. Focused on wind energy conversion systems, particularly those utilizing double-fed induction generators (DFIGs), the research introduces a novel approach to enhance Direct Power Control (DPC) effectiveness. Traditional DPC, while simple, encounters issues like torque ripples and reduced power quality due to a hysteresis controller. In response, the study proposes an innovative DPC method for DFIGs using artificial neural networks (ANNs). Experimental verification shows ANNs effectively addressing issues with the hysteresis controller and switching table. Additionally, the study addresses wind speed variability by employing an artificial neural network to directly control reactive and active power of DFIG, aiming to minimize challenges with varying wind speeds. Results highlight the effectiveness and reliability of the developed intelligent strategy, outperforming traditional methods by reducing current harmonics and improving dynamic response. This research contributes valuable insights into enhancing the performance and reliability of renewable energy systems, advancing solutions for wind energy integration complexities

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection