When the machine is at high speed, serious problems occur, such as high frequency loss, difficult thermal management, and the rotor structural strength insufficiency. In this paper, the performances of two high-speed permanent magnet generators (HSP- MGs) with different rotational speeds and the same torque are compared and analyzed. The two-dimensional finite element model (FEM) of the 117 kW, 60 000 rpm HSPMG is established. By comparing a calculation result and test data, the accuracy of the model is verified. On this basis, the 40 kW, 20 000 rpm HSPMG is designed and the FEM is established. The relationship between the voltage regulation sensitivity and power factor of the two HSPMGs is determined. The influence mechanism of the voltage regulation sensitivity is further revealed. In addition, the air-gap flux density is decomposed by the Fourier transform principle, and the influence degree of different harmonic orders on the HSPMG performance is determined. The method to reduce the harmonic content is further proposed. Finally, the method to improve the HSPMG overload capacity is obtained by studying the maximum power. The research showed that the HSPMG at low speed (20 000 rpm) has high sensitivity of the voltage regulation, while the HSPMG at high speed (60 000 rpm) is superior to the HSPMG at low speed in reducing the harmonic content and increasing the overload capacity.
Photovoltaic panels have a non-linear current-voltage characteristics to produce the maximum power at only one point called the maximum power point. In the case of the uniform illumination a single solar panel shows only one maximum power, which is also the global maximum power point. In the case an irregularly illuminated photovoltaic panel many local maxima on the power-voltage curve can be observed and only one of them is the global maximum. The proposed algorithm detects whether a solar panel is in the uniform insolation conditions. Then an appropriate strategy of tracking the maximum power point is taken using a decision algorithm. The proposed method is simulated in the environment created by the authors, which allows to stimulate photovoltaic panels in real conditions of lighting, temperature and shading.
A single photovoltaic panel under uniform illumination has only one global maximum power point, but the same panel in irregularly illuminated conditions can have more maxima on its power-voltage curve. The irregularly illuminated conditions in most cases are results of partial shading. In the work a single short pulse of load is used to extract information about partial shading. This information can be useful and can help to make some improvements in existing MPPT algorithms. In the paper the intrinsic capacitance of a photovoltaic system is used to retrieve occurrence of partial shading.
A solar photovoltaic (PV) system has been emerging out as one of the greatest potential renewable energy sources and is contributing significantly in the energy sector. The PV system depends upon the solar irradiation and any changes in the incoming solar irradiation will affect badly on the output of the PV system. The solar irradiation is location specific and also the atmospheric conditions in the surroundings of the PV system contribute significantly to its performance. This paper presents the cumulative assessment of the four MPPT techniques during the partial shading conditions (PSCs) for different configurations of the PV array. The partial shading configurations like series-parallel, bridge link, total cross tied and honeycomb structure for an 8#2;4 PV array has been simulated to compare the maximum power point tracking (MPPT) techniques. The MPPT techniques like perturb and observe, incremental conductance, extremum seeking control and a fuzzy logic controller were implemented for different shading patterns. The results related to the maximum power tracked, tracking efficiency of each of the MPPT techniques were presented in order to assess the best MPPT technique and the best configuration of the PV array for yielding the maximum power during the PSCs.
Maximum Torque Control (MTC) is a new method applied for control of induction motor drives. The drive is controlled by dc voltage supplying a converter in the range below nominal speed and by a field that weakens for a speed range above the nominal speed. As a consequence, the control is quite similar to the control of a classical separately excited dc motor. This control method could be explained as a kind of sim- plification of Direct Torque Control (DTC), because the switching scheme is the same as for the DTC, but the variable responsible for a torque control is constantly set for “torque increase”. This kind of control of induction motor drive is simpler than DTC because torque values need not be estimated. The proposed control method offers very good performance for 3-phase induction motors and requires smaller switching frequency in comparison to DTC and Field Oriented Control (FOC). The application of the con- trol is widely demonstrated for a 3-phase 315 kW, 6 kV motor drive by use of computer simulation.
Quality of energy produced in renewable energy systems has to be at the high level specified by respective standards and directives. One of the most important factors affecting quality is the estimation accuracy of grid signal parameters. This paper presents a method of a very fast and accurate amplitude and phase grid signal estimation using the Fast Fourier Transform procedure and maximum decay side-lobes windows. The most important features of the method are elimination of the impact associated with the conjugate’s component on the results and its straightforward implementation. Moreover, the measurement time is very short ‒ even far less than one period of the grid signal. The influence of harmonics on the results is reduced by using a bandpass pre-filter. Even using a 40 dB FIR pre-filter for the grid signal with THD ≈ 38%, SNR ≈ 53 dB and a 20‒30% slow decay exponential drift the maximum estimation errors in a real-time DSP system for 512 samples are approximately 1% for the amplitude and approximately 8.5・10‒2 rad for the phase, respectively. The errors are smaller by several orders of magnitude with using more accurate pre-filters.