Journal of Electrical Engineering & Technology最新文献

This paper explores two critical aspects of solar panel tracking systems and quantifies their outcomes. Firstly, we tackle the issue of slow tracking performance in traditional solar panels by implementing time-optimal theory. We introduce an adaptive model following control, which significantly improves tracking speed, yielding concrete numerical results. We also calculate the tracking time, assuming the tracking actuator follows the trajectory well. In the second part of our study, we use MATLAB Simulink to model solar panels that actively follow the sun for maximum electricity production. To minimize positioning errors during solar tracking, a dedicated controller adjusts motor voltage, resulting in precise alignment with the sun. Our research produces quantitative data demonstrating enhanced tracking efficiency, reduced tracking time, and increased electricity generation. These findings contribute valuable insights to the field of solar panel tracking, offering tangible solutions for optimizing solar energy utilization.

Nature-inspired patch antennas are gaining attention in wireless applications. A novel self-complementary Deoxyribonucleic Acid (DNA) structure-based frequency reconfigurable antenna is proposed in this work. DNA itself follows the golden ratio. The structure of the DNA-shaped antenna is modelled using Fibonacci numbers. The structure dimensions are 80 × 80 × 0.787 mm³. Rogers RT Duroid 5870 with a dielectric constant of 2.33 is used as a substrate. Techniques like the placement of the parasitic patch and Defected Ground Structure (DGS) are implemented and analyzed for gain enhancement. Parametric analysis has been carried out to achieve better radiation characteristics. The antenna is made reconfigurable by incorporating two PIN diode switches. The designed structure covers a wide band from 4.86 GHz to 6.12 GHz (WLAN) during an OFF-ON state. 0.988 GHz (Sub 1 GHz) and 4.58 GHz (5G) (dual band) are the resonating frequencies of the ON-OFF state. For the ON-ON state, the resonating frequencies are 2.67 GHz (WiMAX), 3.36 GHz (LTE), and 4.76 GHz (5G) (triple band). The proposed structure offers acceptable radiation performance. Fabrication and testing are done to validate the results. The simulated findings and the measured results agree quite well.

As an important element of the renewable energy distribution generations, the modeling accuracy and control performance of the interleaved Buck-Boost converter directly affects the stability and efficiency of the renewable power generation. Based on the fact that the inductor and capacitance are fractional-order (FO) elements, the Buck-Boost converter is FO system. At present, most FO control strategy research has focused on the integer-order (IO) converters, which is inconsistent with the fractional order nature of converters. In order to improve the stability and dynamical performance of the FO interleaved Buck-Boost converter control system, a dual-loop control system based on the fractional-order lead-lag compensation control (FOLLCC) strategy is proposed. To begin with, the FO state space average model for interleaved Buck-Boost converter operating in continuous conduction mode (CCM) is established according to the FO calculus theory and state space average method. Then, the FOLLCC of the FO interleaved Buck-Boost is designed by using the peak current closed-loop control with inner current loop outer voltage loop. The impact of different FO controllers on the steady-state performance of the system is analyzed to improve the control effect. Using MATLAB for simulation, the simulation results show that the control system based on FOLLCC has shorter rise times, faster response speed, stronger robustness, and better dynamic performance. Finally, the experiments verify the effectiveness of the proposed approach.

This paper proposes a novel approach to designing a fault-tolerant ({H}_{infty }) sampled-data fuzzy filter using exponential time-varying gains. The utilization of exponential time-varying gains not only achieves a reduction in convergence time but also provides relaxation in the numerical optimization of design conditions. Also, through the use of a robust control technique, the designed filter is equipped with enhanced fault-tolerant capabilities. In addition, sufficient conditions for ensuring ({H}_{infty })-based state estimation performance are derived as linear matrix inequalities (LMIs) based on the Lyapunov–Krasovskii functional (LKF). Finally, simulation results demonstrate the superior performance of the proposed method when compared to existing methodologies.

The grid-connected converter synchronizes with the power grid through the controller, so its out-of-step mechanism and out-of-step characteristics are different from synchronous generators. The out-of-step characteristics and out-of-step protection of grid-connected converter are urgent research topics at present. In this paper, the out-of-step mechanism of grid-connected converter under the low voltage ride through (LVRT) control strategy is analyzed by combining the phase plane method and the equal area criterion. The characteristics of current, voltage and measured impedance angle at the point of interconnection (PoI) are analyzed after the grid-connected converter is out-of-step, and compared with those of the traditional power system. On the basis of these, a novel out-of-step protection method for the grid-connected converter is proposed based on the measured impedance angle at the PoI. It judges the out-of-step by the characteristic that the measured impedance angle oscillates continuously and the difference of its extreme values increases gradually. The faster the out-of-step oscillation develops, the faster the protection acts, so it is adaptive. Finally, a MATLAB/Simulink simulation model is built to verify the effectiveness of the proposed protection method.

This article presents an improved deadbeat indirect torque control (ITC) method for switched reluctance motors (SRMs) with the primary goal of reducing torque ripple. The proposed control approach comprises two parts: a torque-to-current conversion scheme that the proposed method achieves excellent current and a deadbeat controller (DBC). In the conversion scheme, a second-order SRM Fourier-series model is constructed by integrating the current vector decomposition method. Subsequently, an iterative learning controller (ILC) is designed based on this model to achieve precise conversion from the electromagnetic torque to the q-axis current, which eliminates the need for additional modeling processes. Within the proposed DBC controller, a novel recursive least squares (RLS) estimator is introduced to effectively tackle the issue of model variations. This integration enables the adaptive calibration of the predictive model, ultimately guaranteeing optimal performance in the current control. Furthermore, the consistency of the model employed in both the DBC and conversion scheme empowers the RLS to further refine the accuracy of torque-to-current conversion, thereby improving torque ripple suppression performance. Comparative experiments are conducted on a 12/8 SRM to evaluate the proposed control method’s performance. The experimental results show that the proposed method achieves excellent current tracking and torque ripple suppression performance in SRM drives.

Wide attention from academia and industry has been received for Multilevel Inverters (MLIs) as they offer high power capacity, lower harmonics, and lower switching losses. The usage of many switches in the conventional configuration causes a limitation, which leads to the development of a new topology with a switch count. This paper presents the development of Reduced Switch Single Source (RSSS) MLI, which can produce all voltage levels. The analysis of RSSS MLI is done using nine-level MLI, which consists of a few components compared to conventional topologies, thereby ensuring reduced size, minimum switching loss, and installation cost. The harmonic contents of the output voltage are obtained and compared using the carrier-based PWM technique. MATLAB/Simulink environment and experimental tests in the laboratory are used to validate the results.

The production of hydrogen from electrolytic water using renewable energy is a highly effective way to reduce carbon emissions and has garnered significant attention from scholars around the world. As the crucial link between the electrolyzer and the DC bus, the performance of the DC-DC buck converter is paramount. Therefore, a multiphase stacked interleaved buck converter (MSIBC) is proposed in this paper, which offers superior performance in terms of low voltage, high current, and minimal current ripple. This paper delves into the circuit design methods and current ripple elimination mechanisms of this topology. Furthermore, a detailed analysis is conducted to compare the performance of MSIBC with that of interleaved buck converter (IBC) and stacked interleaved buck converter (SIBC), covering factors such as efficiency, inductor current stress, and switching current stress. The results indicate that MSIBC offers superior efficiency, low inductor current stress, and switching current stress. Additionally, MSIBC enables redundant control of the system. Finally, experimental and MATLAB/SIMULINK simulation results confirm the accuracy of ripple cancellation.

With the steadily increasing number of systems utilizing ultrahigh-voltage transmission lines, such as 765 kV and 400 kV substations, shunt reactors have come under the spotlight as a viable option to increase the load capacity and reduce losses. However, the cumulative losses during their operational life increase. In this study, we improved the magnetic flux of a yoke and analyzed its effect on loss reduction in the iron core. We applied a magnetic flux control structure that equalized the main and leakage fluxes generated from the main leg of a gapped core-type shunt reactor with the leakage flux generated from the winding. The magnetic flux generated by the yoke and its distribution in the in-plane direction with and without the flux-control plate were analyzed and compared using Maxwell’s three-dimensional finite element method. We evaluated the losses exhibited by two fabricated shunt reactors with a sensor installed on their iron cores to verify the effectiveness of improving the magnetic flux distribution of shunt reactors. The results confirmed that the magnetic flux control plate reduced the iron and winding eddy-current losses in the gapped core-type shunt reactor. Further investigations are required to minimize loss and noise throughout the operational lifespan of these reactors as well as to decrease the size and weight of shunt reactors for different applications.

Accurate short-term forecasting of photovoltaic power generation is crucial for power dispatching, capacity analysis, and unit commitment. Existing data-driven prediction algorithms have a certain impact on calculation speed and prediction accuracy, but they fail to consider the internal mechanism of photovoltaic power generation and have the risk of generalization. First, the fuzzy C-means clustering (FCM) algorithm method was used for preprocessing of the PV sample set. The sample points with variability were categorized into different sample sets with less variability. Second, the photovoltaic mechanism model is added to the first layer learner of the Stacking framework to form a one-layer learner of the Long Short-Term Memory (LSTM) neural network, Light Gradient Boosting model (LGBM), and mechanism-driven model. The mechanistic model limits PV generation to a reasonable range as a prediction constraint for the data-driven model. The proposed model can seize the useful inherent information from the mechanism model and utilize the ability of data analysis to extract the inexplicit linear relationship. Finally, the PV power and weather observation data collected from photovoltaic power stations located in a certain place in Germany are used to verify the effectiveness of the proposed method.