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Wind power prediction is of great importance for the safety, stabilization and economic efficiency of electric power grids, especially when the wind power penetration level of the gird is high. ANN (Artificial Neural Network) is an appropriate method for wind power prediction. But the generalization of common ANN is poor and the prediction precision is not stable. Neural network ensemble can enhance...
Considering distinct locations and inhomogeneous power plants playing different roles and effecting on the interconnected power system, as well as the purpose of pursuing best efficiency and stability for the whole interconnected power system, this paper presents a new method based on sensitivity analysis and neural network to solve the power regulation on tie-line in the interconnected power system...
In order to reduce accident and enhance reliability of system, a new safety assessment approach combining with system safety engineering, factor analysis and neural network is proposed for transmission grid system in this paper. The safety assessment objective architecture was established by analyzing a variety of factors affecting transmission grid system safety using system safety principle. Factor...
In order to overcome the inherent flaws of artificial neural networks (ANN), such as long training time, slow convergence and low diagnosis accuracy, a novel evolutionary ANN combining with rough set (RS), named as RSANN, is suggested, and it's proposed to apply in power grid fault diagnosis. The ANN used is a three-layer back-propagation (BP) neural network. RS can reduce the dimensionality of attributes...
With the continuous deepening of the power system reform and the blackouts of someplace on the world, the safety of the power grid has received high attention from all sections of the society. The former researches on the power grid safety are mostly about special parts, the method to estimate the whole power grid safety should be improved in the future. In this paper, according to the characters...
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