Accurately predicting photovoltaic (PV) power generation is essential for effective power system scheduling. However, increased incidences of sandy weather in recent years pose significant challenges for PV power plants in desert regions. This study addresses the inaccuracies in PV power forecasting under windy-sandy conditions by conducting wind tunnel experiments to evaluate the impact of varying wind speeds and PV panel tilt angles on power generation. Polynomial equations are developed through polynomial surface fitting to establish a relationship between the power loss rate, sand-blowing wind speed, and panel tilt angle. Latin hypercube sampling is used to extend the fitted surface scenarios, simulating real-world variations in PV power generation to enhance the accuracy and applicability of the model. In addition, the model incorporates three uncertainties related to wind direction, module aging, and airflow effects on PV arrays. A case study utilizing data from a PV power plant employs the Pseudo-similar day selection method, enabling a comparative analysis of the predicted outcomes with traditional methodologies. This comparison demonstrates the accuracy and effectiveness of the proposed method for improving PV power prediction under challenging conditions.

DC-link capacitors play a vital role in managing ripple voltage and current in converters and various devices. This study focuses on exploring the aging characteristics of DC-link capacitors in alternating humid and thermal environments aligned with the operational conditions in photovoltaic and wind power applications. Adhering to relevant power equipment standards, we designed a 24-h alternating humid and thermal aging environment tailored to the requirements of DC-link capacitors. An aging test platform is established, and 20 widely used metallized polypropylene film capacitors are selected for evaluation. Parameters such as the capacitance, equivalent series resistance (ESR), and phase angle are assessed during aging, as well as the onset time and extent of aging at various intervals. This study focuses on the aging mechanisms, analyzing electrode corrosion, the self-healing process, and dielectric aging. Fitting the aging characteristics enabled us to calculate the lifespan of the capacitor and predict it under different degrees of capacitance decay. The results show that under alternating humid and thermal conditions, capacitance attenuation and ESR increase exhibit exponential nonlinearity, influenced by factors such as the oxidation and self-healing of capacitive metal electrodes, dielectric main-chain fracture, and crystal transformation. This study underscores the pivotal role of encapsulation in determining the aging decay time.

With the growing demand for precise voltage adjustment and reactive regulation, the frequent operation of on-load tap changers (OLTCs) in oil-immersed systems has led to increased erosion of switch contacts by arcs during the switching process. This erosion causes significant wear on the contacts, thereby reducing their lifespan. Therefore, the present study aims to investigate the behavior and mechanism of arc erosion on contact surfaces in oil-immersed OLTCs. To achieve this, a self-designed friction and wear test device for OLTC contacts was utilized to conduct experiments at various sliding speeds and contact pressures. Additionally, finite element analysis was employed to validate the experimental results regarding the influence of sliding speed on arc energy. The surface morphology of the contacts was observed using an optical microscope. The findings revealed that as the sliding speed increased, the arc energy, arc initiation rate, and contact resistance initially exhibited an upward trend, then decreased, and eventually increased again. The minimum values were observed at a sliding speed of 90 mm/s. Moreover, the arc energy, arc initiation rate, and contact resistance decreased gradually as the contact pressure increased. After reaching a contact pressure of 1.5 N, the variation in the arc energy stabilized. At lower contact pressures, arc erosion dominated the wear on the contact surface. However, at higher contact pressures, the wear transitioned from predominantly arc erosion to a combination of mechanical wear and arc erosion. In summary, experimental and analytical investigations provided insights into the effects of sliding speed and contact pressure on the behavior of arc erosion, contact resistance, and surface damage of OLTC contacts in oil-immersed systems.

An accurate extraction of vibration signal characteristics of an on-load tap changer (OLTC) during contact switching can effectively help detect its abnormal state. Therefore, an improved fuzzy C-means clustering method for abnormal state detection of the OLTC contact is proposed. First, the wavelet packet and singular spectrum analysis are used to denoise the vibration signal generated by the moving and static contacts of the OLTC. Then, the Hilbert-Huang transform that is optimized by the ensemble empirical mode decomposition (EEMD) is used to decompose the vibration signal and extract the boundary spectrum features. Finally, the gray wolf algorithm-based fuzzy C-means clustering is used to denoise the signal and determine the abnormal states of the OLTC contact. An analysis of the experimental data shows that the proposed secondary denoising method has a better denoising effect compared to the single denoising method. The EEMD can improve the modal aliasing effect, and the improved fuzzy C-means clustering can effectively identify the abnormal state of the OLTC contacts. The analysis results of field measured data further verify the effectiveness of the proposed method and provide a reference for the abnormal state detection of the OLTC.