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As the share of photovoltaic （PV） power generation grows increasingly within electric power systems， the accurate probabilistic forecasting of PV output can be help for grid regulation and operation. To enhance forecasting precision， a probabilistic forecasting method for ultra-short-term photovoltaic output using the improved grey wolf optimization （GWO）， temporal convolutional neural networks and quantile random forests （TCN-QRF） is proposed. Firstly， the preprocessed time series dataset for PV output is converted into a supervised learning dataset. Then， the TCN is used to extract the temporal features of PV output as the input to the QRF， constructing the TCN-QRF model. Finally， the GWO is improved using the nonlinear convergence factor and Gaussian mutation strategy. The improved GWO efficiently selects hyperparameters for TCN-QRF， enabling a more precise probabilistic forecasting of PV output.

To efficiently evaluate the dynamic reliability of the impeller structure in cross-flow fans, its probability density function of maximal stress is established using the probability density evolution theory（PDEM）. The stochastics in structure and surroundings are considered and the finite element analysis model is used. On the basis, the structural failure probability and time-dependent reliability at different operation times are given. The Abaqus finite element analysis software is developed again. Through the joint simulation of Matlab and Abaqus, the whole process batch simulation analysis of model building, stress analysis, result extraction and probability density evolution is realized. By comparing with the agent model method and the Monte-Carlo model from the perspectives of calculation efficiency and accuracy, the practicability of PDEM in evaluating the dynamic reliability of impeller structure is further validated.

Aimed at the problem of the inertia power allocation due to different indexes when multiple optical storage units are running together, a cooperative control strategy of multiple optical storage units is proposed by using adaptive virtual inertia control as a means to improve power quality. According to the charging and discharging characteristics of the battery, the inertia provided by the system is adjusted. As high-frequency disturbance occurs in the system, the super capacitor is the first choice to provide inertia support. As low-frequency disturbance occurs in the system, the battery provides inertia power support, and the distance algorithm of the superior and inferior solutions is introduced. As cooperative control is performed, indicators such as the allowable power fluctuation range of the converter and the allowable power fluctuation range of the energy storage device are selected as the evaluation reference, the coordination among multi virtual synchronous generator (VSG) units in multi-index comprehensive evaluation is realized. Finally, an AC system with multi VSG units is built on the experiment platform, and the effectiveness of the proposed control strategy is verified.

Objective: To compare the differences between proximal femoral nail antirotation (PFNA) and dynamic hip screw (DHS) in treatment of femoral trochanteric fracture and analyze the factors influencing recovery after PFNA treatment., Methods: Eighty-six patients with femoral trochanteric fracture admitted to Taizhou Hospital of Traditional Chinese Medicine between January 2019 and June 2021 were enrolled in the study and assigned into a PFNA group and DHS group (n=43 in each group) before undergoing these treatments. The clinical efficacy, inflammatory factors, and myocardial injury markers were compared between the two groups. The influencing factors on recovery after PFNA treatment were analyzed by univariate and multivariate analysis., Results: Compared to the DHS group, the PFNA group had shorter surgical time, length of stay in hospital, postoperative weight-bearing time, time of healing and detumescence, and less intraoperative blood loss (all P<0.001). The incidence of post-surgical complications with PFNA was lower than with DHS (P<0.05). The serum levels of interleukin-6, C-reactive protein and tumor necrosis factor-αof the PFNA group were lower than those of the DHS group (all P<0.05). Moreover, the serum levels of cardiac troponin T, creatine kinase-MB and myoglobin in the PFNA group were also lower than for the DHS (all P<0.05). At the first, third, and sixth months after surgery, the Harris scores for PFNA were higher than for DHS (all P<0.05). The univariate and multivariate analysis showed that instability of fracture, history of osteoporosis, excessive intraoperative bleeding, poor compliance with rehabilitation exercise, and long time from injury to surgery were risk factors for poor recovery following PFNA treatment for patients with femoral trochanteric fracture., Conclusion: Compared to DHS, PFNA had better clinical efficacy and gave lower serum levels of inflammatory factors and myocardial injury markers. Fracture classification, history of osteoporosis, intraoperative amount of bleeding, compliance of rehabilitation exercise, and time from injury to surgery were closely associated with recovery following PFNA treatment., Competing Interests: None., (AJTR Copyright © 2022.)