A new combined model is proposed to obtain predictive data value applied in state estimation for radial power distribution networks. The time delay part of the model is calculated by a recursive least squares algorith...A new combined model is proposed to obtain predictive data value applied in state estimation for radial power distribution networks. The time delay part of the model is calculated by a recursive least squares algorithm of system identification, which can gradually forget past information. The grey series part of the model uses an equal dimension new information model (EDNIM) and it applies 3 points smoothing method to preprocess the original data and modify remnant difference by GM(1,1). Through the optimization of the coefficient of the model, we are able to minimize the error variance of predictive data. A case study shows that the proposed method achieved high calculation precision and speed and it can be used to obtain the predictive value in real time state estimation of power distribution networks.展开更多
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
文摘A new combined model is proposed to obtain predictive data value applied in state estimation for radial power distribution networks. The time delay part of the model is calculated by a recursive least squares algorithm of system identification, which can gradually forget past information. The grey series part of the model uses an equal dimension new information model (EDNIM) and it applies 3 points smoothing method to preprocess the original data and modify remnant difference by GM(1,1). Through the optimization of the coefficient of the model, we are able to minimize the error variance of predictive data. A case study shows that the proposed method achieved high calculation precision and speed and it can be used to obtain the predictive value in real time state estimation of power distribution networks.
文摘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.
