Gotowa bibliografia na temat „Bi-directional Boost Rectifiers”

Simple control of a stand-alone variable speed wind turbine with a permanent magnet synchronous generator (PMSG) is presented in this paper. PMSG fed different types of loads by means of a converter where switched mode rectifier is connected to the PMSG, boost DC-DC converter, and voltage source inverter (VSI). The wind turbine is operated at measured wind speed and it is tested at estimated wind speed which is based on the power calculation of turbine power, generating electric power, losses power, and the dynamic power during the variation of wind speed. The estimation of wind speed would provide a scope of what a control method is applicable in practice and this would increase the performance by scheduling the connected loads. The bidirectional battery charger is controlled and used during the shortage of wind speed. The converter of the battery charger is controlled and implemented on an embedded system by using an STM32-based microcontroller. During the shortage or fluctuation of wind speed, the load voltage is controlled within the acceptable limit, where the voltage has been compensated. An extensive simulation has been conducted by MATLAB/Simulink, and the system shows a good dynamic response to the variation and decrease in wind speed.

The series-parallel combination of the photovoltaic array can meet the needs of different applications such as high power or low power with the continuous optimization of photovoltaic cell materials and the increasing improvement on efficiency of photovoltaic cell. This exploration takes the independent photovoltaic power generation (PPG) device as the research goal. The system includes a photovoltaic array, Boost rectifier, single-phase photovoltaic inverter, battery and bi-directional DC/DC converter. Single-phase photovoltaic inverter is employed for the AC load power supply, and a lead-acid battery is adopted for energy storage. Buck mode and Boost mode are modeled respectively based on the analysis of the converter topology, and the designed model is employed to control the converter. Back propagation neural network (BPNN) is introduced to analyze the factors which can affect the output power of PPG. In experiment, the effective value of output voltage, output voltage, and current waveform of single-phase inverter are analyzed. The analysis results show that the output voltage changes suddenly with the load, and the device can be followed again within a few milliseconds, which means that the device has good dynamic performance. The corresponding output frequency fluctuates at a small amplitude (±1%) when the output voltage is above 220 V. Meanwhile, the distortion of the output waveform is less than 1%. The ripple coefficient of the output voltage is less than 1% when the operating mode of PPG (boost and Buck) is changed. The neural network is introduced to select the appropriate parameters (irradiation intensity, relative humidity, ambient temperature and wind speed), and the results show that the environmental temperature exerts a great influence on the output power of PPG.

The quality assurance of MOOCs focuses on improving their pedagogical quality. However, the tools that allow reflection on and assistance regarding the pedagogical aspects of MOOCs are limited. The pedagogical classification of MOOCs is a difficult task, given the variability of MOOCs' content, structure, and designs. Pedagogical researchers have adopted several approaches to examine these variations and identify the pedagogical models of MOOCs, but these approaches are manual and operate on a small scale. Furthermore, MOOCs do not contain any metadata on their pedagogical aspects. Our objective in this research work was the automatic and large-scale classification of MOOCs based on their learning objectives and Bloom’s taxonomy. However, the main challenge of our work was the lack of annotated data. We created a dataset of 2,394 learning objectives. Due to the limited size of our dataset, we adopted transfer learning via bidirectional encoder representations from Transformers (BERT). The contributions of our approach are twofold. First, we automated the pedagogical annotation of MOOCs on a large scale and based on the cognitive levels of Bloom’s taxonomy. Second, we fine-tuned BERT via different architectures. In addition to applying a simple softmax classifier, we chose prevalent neural networks long short-term memory (LSTM) and Bi-directional long short-term memory (Bi-LSTM). The results of our experiments showed, on the one hand, that choosing a more complex classifier does not boost the performance of classification. On the other hand, using a model based on dense layers upon BERT in combination with dropout and the rectified linear unit (ReLU) activation function enabled us to reach the highest accuracy value.

Grid connected converters are widely used as front end rectifiers, interface between renewable energy and grid, and power quality applications. Popular control techniques to generate gating signals for active devices, reported in literature are voltage-oriented control, direct power control and one cycle control. In literature, one cycle control has also been reported as scalar resistive emulation or unified constant frequency integration control. The above-mentioned control techniques has been collectively addressed as conventional one cycle control (C-OCC). Light load instability and steady state dc offset phenomenon are the major concerns with of the conventional one cycle control reported in literature. These issues were addressed in the literature by treating them independently. This thesis proposes a common solution to address the light load instability and steady state dc offset phenomenon of conventional one cycle control. C-OCC employs peak detection comparison method, hence the peak of the current always confines with the grid voltage. Therefore, the average current will differ by the ripple error. This results in the steady state dc offset, which is more severe at light load. Further in C-OCC, since the valley of current is not controlled a localized sub-harmonic instability occurs when slope of the falling current is greater than that of the slope of carrier. This thesis proposes a method to control both peak and valley of current, such that the converter changes its state when the expected value of current has been attained. Valley of current in each carrier cycle is decided such that the current has no steady state dc offset in current. To control peak and valley of current, this comparison is necessitated once more. This results in two comparisons in a carrier cycle, hence the name dual comparison one cycle control (DC-OCC). A generalized approach for controlling average current in a carrier cycle for grid connected converter has been proposed. Stability of the inherent current loop in DC-OCC, using propagation dynamics of small disturbance, showed that the proposed control strategy did not suffer from localized sub-harmonic instability. In a converter controlled by C-OCC and DC-OCC, the current lags the grid voltage. The reason for this has been discovered to be the inductive drop across the boost inductor. A novel method to compensate for the inductive drop is proposed in this thesis. The sensed input current is modified by adding a 90°phase shifted current with appropriate gain and is used for comparison to generate gating signals for active devices. The sensed input current is added with a fictitious current, generated from gating signal of the active devices, to enable bi-directional power ow in converters controlled by DC-OCC. A second order band pass filter (BPF) is used to generate the fictitious current from the gating signal. Effects of BPF corner frequency in quality of current drawn or injected into the grid is used during the design of the filter. The sum of sensed input current and fictitious current, is further modified by adding a 90°phase shifted current with appropriate gain. This modification enabled the converter to draw or inject power at an adjustable displacement power factor. Moreover, this modification also enables the converter to operate as a STATCOM. The gain of the phase shifted current determines the phase of the current drawn or injected. The current loop showed a tendency to become unstable when the gain of the phase shifted current approached 0.5. Small signal model of the converter is used to analyze this instability. Average modeling technique is used to derive the model of the converter controlled by DC- OCC. Further, the non-linear average model is linearized using small signal analysis. The small signal model shows the presence of an inherent current loop with a proportional controller. Gain of the proportional controller is the effective resistance seen by the current loop. As the gain of the phase shifted current loop approaches 0.5, the closed poles of the inherent current loop crosses over to the right half of s-plane, causing an instability in the current loop. Design of voltage loop controller parameters is also presented in this thesis. All of the above modifications are validated in simulations and experiments. Simulation and experimental results are presented in this thesis for converters in the range from 600 W to 2 kW.