Liu Xinrui

Analysis of ice disaster failure considering the multi angle information modification for distribution network

In this paper, the method of ice disaster for distribution network failure rate analysis is developed. This method takes the line segment as a research unit according to the characteristic of obvious regional differences in distribution network. The priority is rightly to determine the high risk line segments based on the analysis of history sensitivity of disaster and component loss rate. Besides, it is assumed that the rate of a real-time failure due to the ice disaster weather depends on failure rate for operation and frozen disaster together with the interaction of internal and external factors. In order to mitigate severe consequences of future ice disasters in an efficient way it is essential to be able to estimate the risk failure rate based on forecast of the real-time failure rate and the history sensitivity of disaster. And the real-time analysis of risk failure rate can be modified by the multi angle information to achieve early warning timely and accurately. The numerical example show the impact of ice disaster on a part of the Shen Yang distribution network using date from real weather situations and the analysis method, and the validity of the method is verified.

Robust and reliable H ∞ fuzzy hyperbolic decentralized control for a class of nonlinear large-scale systems with parametric uncertainties

This paper develops robust Hinfin fuzzy hyperbolic control for nonlinear large-scale systems with parameter uncertainties. Firstly, fuzzy hyperbolic model (FHM) can be used to establish the model for certain complex large-scale systems, then according to the Lyapunov direct method and the decentralized control theory of large-scale systems, the sufficient condition in the terms of linear matrix inequalities (LMIs) which guarantee the existence of the state feedback Hinfin control based on FHM for the fuzzy large-scale systems is proposed. The main advantage of using FHM over Takagi-Sugeno (T-S) fuzzy model is that no premise structure identification is needed and no completeness design of premise variables space is needed, therefore there needs much less computation expense than that of using T-S fuzzy model, especially when a lot of fuzzy rules are needed to approximate highly nonlinear complex systems. In addition, an FHM is not only a kind of valid global description but also a kind of nonlinear model in nature. A simulation example is provided to illustrate the design procedure of the proposed method and its validity.