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In this paper, quasi-Monte Carlo combined with multiple linear regression (QMC-MLR) is proposed to solve probabilistic load flow (PLF) calculation. A distinguishing feature of the paper is that PLF is approached by a low-dimensional problem with the concept of the effective dimension, and thus QMC based on low-discrepancy sequences is used to improve the sampling efficiency of the Monte Carlo simulation...
The uncertainties of wind power have a great influence on the static voltage stability of power systems. The effect of uncertainty and correlation of wind power on the static voltage stability is studied in this paper and the static voltage stability is analyzed on the basis of probabilistic load flow (PLF). Moreover, quasi-Monte Carlo using Sobol sequences is adopted to obtain the samples of input...
Probabilistic load flow (PLF) is an efficient tool to assess the performance of a power network considering random variables. In this paper, an improved Latin hypercube sampling (LHS) is proposed to solve PLF considering correlated input random variables. The permutation of samples in LHS is treated as a combinatorial optimization problem and handled by a designed genetic algorithm combined with local...
Trust plays an important role in software usage. It helps users overcome perceptions of uncertainty and risk and engages in trust behaviors. In this position paper, we propose using the trust behavior as a main characteristic to provide software recommendations. We explore a model of trust behavior that contains three root constructs: using behavior, reflection behavior and correlation behavior. The...
Aimed at the problem of resident-government conflict during the course of tourism development in world natural heritage site in China, and within the Attitude-Behavior-Situation analysis frame work, the research explored the major internal and external factors that influence local residents' interest conflict handling style on the base of the conflict handling model of Callanan et al. (2006) and Rahim(2000)...
This paper presents a new algorithm for the identification of spectral properties of power system oscillations using an improved Hilbert-Huang transform. Firstly, a relevant vector machine is used as a preprocessor to extend the length of the signal at both ends. Secondly, the empirical mode decomposition method is utilized to decompose the power system oscillation signal into a set of intrinsic mode...
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