In this paper the analysis of small signal stability of grid-connected doubly fed induction generators (DFIG) is presented. The detailed model of grid-connected DFIG wind turbine is firstly estabilished, and the eigenvalues are classified and characterized based on participation factors. Then the modal analysis including its converter and pitch controllers is studied, and model simplification of the DFIG wind turbine is presented under the acceptable assumption. Finally, simplified model of DFIG wind turbine is used in dynamic analysis of Zhangjiakou wind plant in China, and the results offer a good dynamic performance. Keywords-doubly fed induction generator (DFIG); small signal stability; model simplificationI.

This paper introduces a condition-based maintenance method combined with long short-term memory network for offshore wind turbine. According to the ranking of offshore wind turbine components using multiple indicators (failure rate, repair time, and maintenance cost), the optimization object focuses on four critical components, namely, rotor, pitch system, gearbox, and generator. Long short-term memory network is implemented to evaluate system condition and predict potential risks, then the preventive maintenance can be performed on the component that reaches the reliability threshold. The repair activity provides an advance maintenance opportunity for the other components, sharing the fix maintenance costs and the downtime. A maintenance decision process is presented in this paper, aiming to achieve the maximum cost savings. Calculated and comparative results demonstrate that the policy proposed in this article is superior in validity and accuracy.

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A novel failure analysis method named D‐vine copula Bayesian Network is proposed, aimed to extract fault correlation information from various condition monitoring channels of floating offshore wind turbine components, quantify risk probability and consequence, and obtain risk priority of components considering condition correlation. First, a copula Bayesian model is established based on the Bayesian network and D‐vine copula theory. Then, a risk consequence calculation method considering relative loss is developed. Finally, critical failure items are identified by a risk matrix. The proposed technique is expected to: (i) Release the limitation that parent nodes with condition monitoring input are processed as independent in Bayesian analysis. (ii) Provide an alternative way for presenting relationships between nodes instead of conditional probability tables. (iii) Simplify the calculation of high‐dimensional copula. This study screened out high‐risk level components of floating offshore wind turbines, and operation recommendations avoiding potential failure risk are put forward. The comparative results demonstrate the feasibility and reliability of the proposed method.

With rapid tempo of development in the information technology, design model of information network based on three-layer structure and WCF could solve problems about dormitory managing work which relies on its merit as to independence of programming language and platform. It makes programmers’ distribution and collaboration of tasks more effective to apply key technology of three-layer structure and Web Service to student dormitory management system’s design and implement. Therefore, developers of system can pay more attention to the relative business logic in order to reduce difficulty of maintenance in late stage of software development life cycle. Moreover, it does not need artificial intervention to realize RFID which has speedily and convenience operation. In this case, efficiency of managing work and unity of system data can be guaranteed.