Wind power has characteristics of randomness and uncontrollability. China needs to learn from the successful experience of wind power prediction in European. Wind power forecasting (WPF) will be an important part of the power system construction in the future. Firstly, the classification of WPF is discussed according to the different classified methods. Secondly, the evaluation criteria about the uncertainty of WPF are summarized. Thirdly, we give a survey on the main methods of WPF. Finally, the development direction of WPF is proposed

Background: A positive professional identity is key for nursing students in determining career direction and predicting future engagement in the profession. Despite its complexity and susceptibility to various influences, the factors shaping nursing students' professional identity remain poorly understood.Objectives: This study aims to investigate how perceived stress can directly and indirectly influence professional identity among nursing students, with self-control and self-directed learning ability as mediators.Materials and methods: A cross-sectional survey was conducted from October to December 2023, collecting data from 675 nursing students across five tertiary hospitals in Xi'an, Shaanxi Province, China. The survey captured detailed data on sociodemographic characteristics, perceived stress, self-control, self-directed learning ability, and professional identity among the participants. Descriptive analysis and correlation matrices were used to analyze participant characteristics and assess bivariate correlations. The mediation model was analyzed using the PROCESS macro for SPSS.Results: Perceived stress showed a direct and negative influence on professional identity among nursing students; self-control was shown to play a mediating role between perceived stress and professional identity; self-directed learning ability was shown to play a mediating role between perceived stress and professional identity; and self-control and self-directed learning ability were shown to play a chain mediating role between perceived stress and professional identity.Conclusion: Self-control and self-directed learning ability have a chain mediating role in between perceived stress and professional identity among nursing students. It suggests that nursing managers and educators can improve the self-control and self-directed learning ability of nursing students to mitigate the negative impact of perceived stress on professional identity.

The performance evaluation of wind power forecasting under commercially operating circumstances is critical to a wide range of decision-making situations, yet difficult because of its stochastic nature. This paper firstly introduces a novel TRSWA-BP neural network, of which learning process is based on an efficiency tabu, real-coded, small-world optimization algorithm (TRSWA). In order to deal with the strong volatility and stochastic behavior of the wind power sequence, three forecasting models of the TRSWA-BP are presented, which are combined with EMD (empirical mode decomposition), PSR (phase space reconstruction), and EMD-based PSR. The error sequences of the above methods are then proved to have non-Gaussian properties, and a novel criterion of normalized Renyi’s quadratic entropy (NRQE) is proposed, which can evaluate their dynamic predicted accuracy. Finally, illustrative predictions of the next 1, 4, 6, and 24 h time-scales are examined by historical wind power data, under different evaluations. From the results, we can observe that not only do the proposed models effectively revise the error due to the fluctuation and multi-fractal property of wind power, but also that the NRQE can reserve its feasible assessment upon the stochastic predicted error.

A novel, tabu-based real-coded small-world optimization algorithm (TR-SWA) is proposed. Tabu search is adopted to avoid duplicate searches of the real-coded small-world optimization algorithm (R-SWA). A crossover operator is introduced to construct search operators. The convergence behaviour of this TR-SWA scheme is shown by establishing the Markov model, and it is proved that TR-SWA meets the convergence theorem of a general random search algorithm proposed by Solis and Wets. Simultaneously, martingale convergence theorems are used to prove the nearly universal strong convergence of TR-SWA. Finally, five benchmark functions are introduced to evaluate the performance of TR-SWA: comparisons are made between TR-SWA, particle swarm optimization, binary-coded small-world optimization algorithm and R-SWA. Numerical experiments demonstrate that the addition of the tabu search improves the performance of R-SWA for most of the investigated optimization problems, and the global convergence of TR-SWA is guaranteed if the feasible set is bounded.