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Reduced Model for Power System State Estimation Using Artificial Neural Networks
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作者 amamihe onwuachumba Yunhui Wu Mohamad Musavi 《Journal of Energy and Power Engineering》 2014年第5期957-965,共9页
In this paper, a new technique using artificial neural networks for power system state estimation is presented. This method does not require network observability analysis and uses fewer measurement variables than con... In this paper, a new technique using artificial neural networks for power system state estimation is presented. This method does not require network observability analysis and uses fewer measurement variables than conventional techniques. This approach has been successfully implemented on six-bus, 18-bus, IEEE 14-bus and IEEE 57-bus power systems and the results show that this method is very accurate and a lot faster than conventional techniques making it ideal for smart grid applications. 展开更多
关键词 Artificial neural networks network observability power systems state estimation.
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