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Various wind turbines have been manufactured for converting wind power into electric energy. They are fixed speed concepts with squirrel cage induction generators, limited variable speed concepts with wound rotor induction generators, variable speed concepts with double fed induction generators, direct-drive concepts with electrically excited synchronous generators and gearbox-free concepts with permanent magnet induction technologies. The composed components and the power curve of these technologies are different and to select an appropriate wind turbine for a wind site, in addition to the economic parameter, reliability criterion must be considered. To address this, a reliability model is developed in this paper that considers both component failure and the unpredictable nature of wind speed for different types of wind turbines. The optimal state number of reliability presentations is determined using XB index calculation and fuzzy c-means clustering method to create multi-state presentations for wind turbines. The proposed approach can be used to determine the most reliable wind turbine for a given wind site by assessing the adequacy of the electric network containing various types of wind turbines. The approach's effectiveness is demonstrated through adequacy assessments of the RBTS and IEEE-RTS, which contain various types of wind turbines. [ABSTRACT FROM AUTHOR]

A run‐of‐the‐river power plant is a renewable energy source used for electricity production. Its power output depends on the varying water flow rate over time, which can impact the reliability of the electric network. Previous research has not studied the effects of water flow rate and temperature variations on the hazard rate of the plant's components. This paper addresses this gap by investigating the impact of these variations on the reliability of electric networks with run‐of‐the‐river power plants. The analysis considers the hazard rates of the plant's components, incorporating the relationship between hazard rate and temperature based on the Arrhenius law. Parameters such as power output, current, power loss, operating temperature, and hazard rate are calculated for different water flow rates and ambient temperatures. Numerical simulations on a test system are conducted to examine the influence of water flow rate and temperature on the reliability indices of the electric network. The results demonstrate that water flow rate and temperature significantly affect the hazard rates of run‐of‐the‐river power plants. This highlights the need to consider these factors in the reliability analysis of electric networks incorporating these renewable resources. [ABSTRACT FROM AUTHOR]

The use of underground XLPE cables in power systems is increasing due to the problems associated with overhead lines. However, insulation failure, primarily caused by partial discharge (PD) phenomenon, remains a major concern. Monitoring the insulation condition of XLPE cables, particularly the magnitude and trend of PDs, is crucial. Detecting and localizing PDs online pose a significant challenge due to the presence of various environmental noises that must be eliminated. In recent years, power systemintroduced noises like impulse noises generated by power electronic devices have become prevalent. Therefore, effective de-noising techniques are required to filter out the noises and interferences from the detected PD signals. This paper proposes the use of wavelet transform, which encompasses both time and frequency domains, to remove various noises from PDs, considering their non-stationary nature. To determine the suitable mother wavelet transform, threshold, and number of decompositions, experimental tests are conducted to investigate the characteristics of PD signals in the cables. Additionally, background noise at the measurement site, which varies in substations, is recorded as reference noise for the wavelet-based noise removal process. Using MATLAB software, reference noises and noisy PD signals are measured in substations, and the de-noising process is executed. The proposed method is evaluated on a sample cable, and the results are discussed. Furthermore, the method is applied to detect PD signals in multiple 20 kV substations in Iran, utilizing high-frequency current transformers connected to shield wires, oscilloscopes with high-frequency bandwidth, and MATLAB software. [ABSTRACT FROM AUTHOR]

This study proposes a novel pulse width modulation (PWM) algorithm to mitigate the common mode voltage (CMV) in a multi-level voltage source inverter feeding an electric machine. Dead-time effect frequently prevents the CMV not to reach zero in several switching periods. Then the electromagnetic interference noise is generated and causes bearing failure and overvoltage stress on winding insulations. The proposed strategy compensates the dead-time effect that alleviates the highamplitude rectangular pulses with extreme range of variations during high-frequency switching transitions. The existing PWM methods reduce the CMV to ±Vdc/6, however by utilising the presented approach, CMV can be reduced to zero. However, the total harmonic distortion will be increased 0.3% at fundamental current harmonic rather than conventional state PWM method, which could be neglected. Simulation results and efficiency analysis imply on worthy performance of the proposed strategy to eliminate the CMV. [ABSTRACT FROM AUTHOR]