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In wind power generation system, studying the correlation characteristics between wind speed and power fluctuation can provide a good theoretical basis for wind power prediction, and has important reference value for enhancing the security and stability of power system. Aiming at the problem that power does not fluctuate linearly in real time with wind speed fluctuation, this paper has divided the wind speed and power fluctuation process by K-means clustering algorithm and fuzzy C-means clustering algorithm respectively, and obtained five different fluctuation processes. Then, the correlation characteristics of wind speed and power fluctuation under different fluctuation processes are analyzed by Pearson correlation analysis method and grey correlation analysis method. The results show that the maximum correlation coefficient is 0.492 5 and the minimum correlation coefficient is 0.331 8 in K-means clustering. In fuzzy C-means clustering, the maximum correlation coefficient is 0.486 8 and the minimum correlation coefficient is 0.329 3. Under all fluctuation processes, the grey correlation degree is around 0.5, indicating that the trend of power fluctuation is similar to that of wind speed fluctuation.

Large scale new energy access to weak alternating current (AC) power grid is prone to transient overvoltage,phase-locked synchronous stability and other problems,which bring problems for the full use of new energy. In this paper,the influencing factors of the stability level of the new energy access system are explored. The short-circuit ratio index of new energy is used as the quantitative evaluation basis of the system voltage intensity,and the sensitivity of the short-circuit ratio of new energy generation power is derived. The comprehensive sensitivity index of the short-circuit ratio of new energy is constructed by comprehensively considering the sensitivity of the average short-circuit ratio and the lowest short-circuit ratio of the system,and an optimal power allocation control scheme for new energy generation based on equal comprehensive sensitivity criterion is proposed. Based on this method,the optimal control of new energy power generation is carried out,and the full utilization of renewable energy is realized on the basis of ensuring the security and stability of the system. Finally,the feasibility and effectiveness of the proposed method are verified by taking a new energy centralized transmission system in Northwest China as an example.

Overvoltage is a common fault in high voltage direct current (HVDC) transmission systems, which directly affects the safe and stable operation of the system. Energy storage system has been widely used in power system because of its fast response speed, high precision and bidirectional energy transmission. As a variable parameter, the low voltage traverse active power coefficient directly affects the overvoltage of commutation failure in HVDC system. In this paper, the influence of transient characteristics and energy storage parameters on commutation failure overvoltage of energy storage system connected to HVDC is analyzed. Based on PSASP simulation, combined with the actual characteristic setting parameters of a power grid in northwest China, the positive correlation between energy storage low-pass active power and transient overvoltage of HVDC system commutating failure is verified by dynamic trajectory sensitivity analysis, and the optimization space of HVDC energy storage system is expanded.

In this paper, combined with the actual engineering, a modular transportation status monitoring system is designed, which can be used to measure environmental conditions such as vibration, inclination, temperature and humidity during the process of transportation. The system consists of a main control module, a storage module, a data acquisition module, a real-time clock module, a power management module and an alarm module. The design scheme has high development efficiency and strong practicability. The measurement device used in the experiment for environmental monitoring during transportation process performs well, and can be a typical application case of innovative practice teaching

Combined with the actual project, a grating ruler accelerated life test device is designed, which can simulate the actual loads, including temperature, humidity and speed stress. An accelerated life test scheme based on stepped stress loading is proposed, and 6 grating rulers are tested based on time-censored test method. An accelerated life model based on Weibull distribution used for evaluating the lifetime is established. Related experimental techniques also can be typical application cases for innovative practical teaching.

Introduction: Anal mucinous adenocarcinoma (AMAC) is an extremely rare form of anal cancer. Our objective was to examine the incidence, management, and prognostic factors of AMAC. Methods: We analyzed age-adjusted incidence (AAI) rates over time and compared the prognosis of AMAC with anal squamous cell carcinoma (ASCC) and adenocarcinoma (AAC) using propensity score matching and Kaplan-Meier analysis. Patients were classified based on summary stage and treatments to determine cancer-specific survival. Results: AAI of AMAC fluctuated within a narrow range (0.082–0.237 per million person-years) from 2000 to 2018. AMAC had a slight non-significant trend of worse prognosis than ASCC (p = 0.348) and a better prognosis than AAC (p < 0.01). Females made up a larger proportion of patients diagnosed with the distant disease (p < 0.05) and unmarried (p < 0.05) and somewhat less probably to need surgical removal (p < 0.01) and radiotherapy (p < 0.01). Elderly patients have lower rates of survival (p < 0.05). Localized stage was associated with better prognosis (p < 0.05). Surgery was associated with a tendency toward better survival (p = 0.095). Conclusions: AMAC exhibits a low incidence yet favorable prognosis compared to typical AAC and slightly worse compared to ASCC. Elderly age is associated with poorer prognosis, while localized stage indicates better prognosis. Surgery demonstrates a trend toward improved survival. [ABSTRACT FROM AUTHOR]

Slow-moving landslides often occur in areas of high relief, which are significantly affected by tropospheric delay. In general, tropospheric delay correction methods in the synthetic-aperture radar interferometry (InSAR) field can be broadly divided into those based on external auxiliary information and those based on traditional empirical models. External auxiliary information is hindered by the low spatial–temporal resolution. Traditional empirical models can be adaptable for the spatial heterogeneity of tropospheric delay, but are limited by preset window sizes and models. In this regard, this paper proposes an improved tropospheric delay correction method based on the multivariable move-window variation model (MMVM) to adaptively determine the window size and the empirical model. Considering topography and surface deformation, the MMVM uses multivariate variogram models with iterative weight to determine the window size and model, and uses the Levenberg–Marquardt (LM) algorithm to enhance convergence speed and robustness. The high-precision surface deformation is then derived. Combined with hotspot analysis (HSA), wide-area potential landslides can be automatically identified. The reservoir area of the Baihetan hydropower station in the lower reaches of the Jinsha River was selected as the study area, using 118 Sentinel-1A images to compare with four methods in three aspects: corrected interferograms, derived deformation rate, and stability of time-series deformation. In terms of mean standard deviation, the MMVM achieved the lowest value for the unwrapped phase in the non-deformed areas, representing a reduction of 56.4% compared to the original value. Finally, 32 landslides were identified, 16 of which posed a threat to nearby villages. The experimental results demonstrate the superiority of the proposed method and provide support to disaster investigation departments. [ABSTRACT FROM AUTHOR]

The reliability of machine tool components, particularly the tool magazine manipulator, significantly affects the overall performance of the machine tool. To address the challenge of accurately evaluating the manipulator's health status using a single performance indicator, this study proposes a method that combines Fuzzy Comprehensive Evaluation (FCE) and a Combined Weighting Method (CWM). By considering both subjective and objective factors, this method provides a comprehensive evaluation of the manipulator's health status, enhancing the accuracy and reliability of the assessment. The method utilizes fuzzy distribution to construct membership matrices for different health levels and adopts the CWM that combines the Entropy Weight Method (EWM) and Analytic Hierarchy Process (AHP) to determine the combined weights of the health evaluation indices. This approach improves the accuracy and reliability by considering multiple indicators and objectively weighting them based on their importance. The current health status of the manipulator is evaluated using the fuzzy weighted average operator and the maximum membership principle. Moreover, a fault prediction method based on Particle Swarm Optimization (PSO) and GM(1,1) is proposed to overcome the information gap and small sample problems. The proposed model's prediction accuracy is verified by comparing it with other models, demonstrating its effectiveness and reliability. [ABSTRACT FROM AUTHOR]