Nashriyyah -i Muhandisi -i Barq va Muhandisi -i Kampyutar -i Iran: 111 (2)

Open Access Article

1 - Fault Detection and Localization in Hybrid Shipboard Electrical Power Grids Using Wavelet Transform
Mohsen Aliyani Arash Dehestani Kolagar Mohammad Reza Alizadeh Pahlavani

In the hybrid shipboard power networks, the possibility of occurrence of various types of faults is very high. According to the studies conducted in the field of fault detection and localization in hybrid microgrids, the lack of comprehensive fault management techniq More

In the hybrid shipboard power networks, the possibility of occurrence of various types of faults is very high. According to the studies conducted in the field of fault detection and localization in hybrid microgrids, the lack of comprehensive fault management techniques to protect the microgrid against short-circuit faults is the main obstacle to the use of hybrid microgrids in vessels for vital marine missions. Considering the restrictions and limitations in marine vessels, the design of an electrical protection system for hybrid microgrids requires high attention to special requirements. In this paper, an appropriate protection scheme for fault detection and localization in hybrid shipboard microgrids is presented. In this regard, fault detection, classification and localization in a period of 0.034 to 0.54 seconds are performed using an algorithm based on Daubechies order 4 wavelet transform (db4). Observing the results and analyzing them shows that the proposed algorithm can detect, classify and localize all types of faults both in the AC and DC parts of the shipboard microgrids. Manuscript profile

Open Access Article

2 - Improvement of Harmonic Losses and Power Quality Due to Matrix Converter Switching in Bidirectional Feeding Induction Generator Using Passive Hybrid Filter
neda ghaderi hoda naderi Mohammad عابدینی محمدحسن مرادی

In two-way feeding induction generators, the stator coils connect directly to the grid, while the rotor coils connect through power electronic converters. Back-to-Back (BTB) converters are commonly used but suffer from high losses, size, and weight due to their two-s More

In two-way feeding induction generators, the stator coils connect directly to the grid, while the rotor coils connect through power electronic converters. Back-to-Back (BTB) converters are commonly used but suffer from high losses, size, and weight due to their two-stage structure and DC link capacitor. This paper proposes replacing BTB converters with matrix converters for improved efficiency and compactness. The proposed method utilizes direct power control in the matrix converter for superior tracking of reference values during changes in both reference and turbine power. However, power electronic converters can introduce harmonics and power fluctuations. To address this, a passive hybrid filter is employed at the converter's input and output. This filter reduces active and reactive power fluctuations, improves Total Harmonic Distortion (THD), and enhances overall power quality. Additionally, the matrix converter's fast dynamic response to reference power changes eliminates the need for complex current control loops, resulting in a simpler structure with minimal calculations. The paper compares the performance of the proposed method (matrix converter with filter) against scenarios with and without a filter. The results demonstrate the filter's effectiveness and superiority in achieving optimal performance. Manuscript profile

Open Access Article

3 - Nonlinear Fractional Intelligent Controller for Photovoltaic Inverters
Hadi Delavari Sara Arjmandpour

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At present, with the significant growth of energy consumption, increase of greenhouse gases and environmental pollutants, more attention is directed toward renewable energies. Renewable energies include geothermal, wind, photovoltaic energy and etc. Among the advantages of photovoltaic energy, its wide range and easy access, helping to preserve the environment, compatibility with distributed power networks, low noise, quick installation and lower cost compared to other energies can be noted. Important challenges facing photovoltaic systems are changing climatic conditions and parameters variation that affect the performance of the system. In this paper, to track the maximum power point in a photovoltaic system, a fuzzy fractional order sliding mode controller based on disturbance observer and uncertainty estimator using neural network is designed. The sliding mode control is used to reduce chattering, neural network to estimate the system uncertainties, fuzzy system to estimate the coefficient of the signum function in the control law and disturbance observer to approximate the disturbances in the system. Also, the stability of the system has been proven using the Lyapunov method. The simulation results of the photovoltaic system confirm the effectiveness of the proposed method and shows satisfactory performance. Manuscript profile

Open Access Article

4 - Detection and Analysis of Acoustic Signals of Power Transformers On-Load Tap Changers for Assessment of Their Faults
adel younesi Abbas Ghayebloo Hasanreza Mirzaei

On load tap changers are very important equipment of the power transfor More

On load tap changers are very important equipment of the power transformers. Due to the strongly mechanical movements and high-energy arcs, this equipment has a much higher failure rate with respect to other internal transformer equipment. Online and accurate evaluation of well operation of these equipment by indicators with no interfere on the normal operation of the transformer, is very important issue. In this paper, various faults detecting methods in the tap changer have been discussed an investigated by some extracted features of acoustic signals. These signals have been captured experimentally in various tap changing periods by an accelerometer sensor mounted on a power transformer body. In this paper, in addition to common features, two new feathers entitled time and frequency indicators have been introduced. Finally, for selecting the proper features to faults detection and proposing an effective classification method, some available experimental data were randomly defected by results in the references, and classified successfully as healthy and defective data by support vector machine (SVM) method. Manuscript profile

Open Access Article

5 - Determining the Location of Lightning Strike Using Electromagnetic Time Reversal (EMTR) Method and Machine Learning
Abbas Hamedooni Asli m.h. m.

Determining the location of lightning strikes (LLS) is one of today's challenges in various fields, especially in the fields of electricity and electronics. To determine the location of the lightning strike, classical methods were used previously; however, the use of More

Determining the location of lightning strikes (LLS) is one of today's challenges in various fields, especially in the fields of electricity and electronics. To determine the location of the lightning strike, classical methods were used previously; however, the use of electromagnetic time reversal (EMTR) method has also become popular recently. According to the calculation of the complete waveform of the field using the EMTR method, the accuracy in determining the location of the lightning strike has significantly increased compared to the traditional methods. In the electromagnetic time reversal method with the help of finite difference time domain (FDTD), the transient electromagnetic field produced by the lightning channel is calculated first. After the time reversal of the wave, it is re-emitted from the sensor or sensors to its source and again with the help of FDTD, The re-emission electromagnetic field in the desired environment is calculated. With the electromagnetic field of the environment, using criteria (such as maximum field amplitude, maximum energy and entropy, etc.), the location of the lightning strike is determined. In traditional methods, it is quite difficult to determine the uniqueness of the final response in environments with different characteristics, and the use of at least three sensors is mandatory. In this paper, to overcome these limitations, a method based on the combination of machine learning and three-dimensional EMTR (3D-FDTD) is proposed to determine the lightning strike location. First, the three-dimensional time domain finite difference method is used to calculate the electromagnetic field of the environment and using EMTR, the back-diffusion electromagnetic field (again with the help of 3D-FDTD) is calculated in the entire environment. In this way, the necessary data for the production of RGB image profiles is prepared. Then VGG19, a pre-trained convolutional neural network (CNN), is used to extract image features. Finally, a fitting layer is used to determine the location of the lightning strike. The proposed method is simulated and implemented in MATLAB and Python, and the results show the effectiveness of the proposed method to determine the location of lightning strikes in a three-dimensional environment without requiring the use of at least three sensors. Manuscript profile

Open Access Article

6 - Modeling of Solar Power Plant Using a Neural Network Based on the Equivalent of a Single Diode
Ali Reza reisi Rohollah Abdollahi

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Various methods have been proposed for modeling solar panels, but modeling solar power plants using them is associated with challenges. In equivalent circuit-based methods, the modeling depends on factory data that changes over time. Modeling of voltage-current characteristic using intelligent methods such as neural network was less considered due to the low accuracy of modeling. In this article, a method independent of the manufacturer's data for modeling the solar power plant is presented, so that it is possible to accurately model the solar power plants that have been installed for several years. The proposed method consists of two steps, in the first step, open circuit voltage, maximum power point and short circuit current are modeled according to atmospheric conditions using neural network. In the second step, the unknown parameters of the equivalent circuit are determined by circuit analysis relations and using neural network outputs. Finally, to evaluate the proposed method, a 3-kW solar power plant was modeled, and the results show the appropriate accuracy of the proposed method for modeling the solar power plant.   Manuscript profile

Open Access Article

7 - Performance Improvement of High Voltage Transformer in Klystron Amplifier Power Supply by Magnetizing Current Balancing
Abolfazl Nasiri mohsen ganji seed mohamad Alavi

In this research, the structure of a Full-bridge converter has been used to feed the klystron amplifier. Three Full-bridge transducer modules with high voltage transformers are used to supply the power of klystron (100 kW, 4 kV, 25 kV). The output of More

In this research, the structure of a Full-bridge converter has been used to feed the klystron amplifier. Three Full-bridge transducer modules with high voltage transformers are used to supply the power of klystron (100 kW, 4 kV, 25 kV). The output of the transformers is rectifier in a star structure and after passing through a π filter, the circuit of the klystron lamp is supplied. The output of the power supply is 1 ms width and frequency of repetition is 50 Hz. The input voltage of the converter is 500 VDC, which is supplied by a three-phase feed. In this research, by balancing the magnetizing current of high frequency transformers, the maximum magnetization current of transformers decreases and decreases the maximum current of transistors. In addition, the core dimensions of the transformer decrease by reducing the maximum magnetization current. As a result, the dimensions, volume, and weight of the klystron drive circuit are reduced. Also, by using leakage inductance of high frequency transformer, series resonance circuit has been created and soft switching conditions have been provided. In this way, it improves the performance of the klystron driven circuit. Modulator performance has been simulated and approved using PSCAD software and resistive load. Manuscript profile

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