Distribution Grid Condition Monitoring Based on BP Neural Network


Article Preview

Intelligentialize of distribution networking technology will become an important trend as the development of the electric power industry in future. In order to build the integration platform of intelligent power grid, the SCADA technology of distribution grid, the advancing technical method of condition monitoring are introduced into the distribution grid monitoring system. Meanwhile, the autocorrelation function is introduced into load forecasting and established the power load forecasting model which is examined based on the MATLAB BP neural network tools of load simulation software. Monitoring distribution network structure state and knowing state clearly of forecasting distribution network node load will provide effective information to establish platform of smart grid information integration. Through the simulation examples, proving the effectiveness and practicability of the scheme.



Advanced Materials Research (Volumes 588-589)

Edited by:

Lawrence Lim




L. L. Zhang et al., "Distribution Grid Condition Monitoring Based on BP Neural Network", Advanced Materials Research, Vols. 588-589, pp. 1037-1041, 2012

Online since:

November 2012




[1] CongShuang. (2009). Facing MATLAB toolbox of neural network theory and application. Hefei. China Science And Technology University Press.

[2] LiuJian, BiPengXiang, YangWenYu and ChengGongLi. (2007). Distribution theory and application. Beijing. China Water Power Press.

[3] LiuZhenYa. (2010). Smart grid technology . Beijing. China Electric Power Press.

[4] power transmission and transformation equipment condition monitoring system technology norms Q/GDW XXX ─ 20 XX.

[5] TianLin, YanFeng and LiuWenXuan. (2011)Based on neural network load forecast simulation study . The System Simulation Technology. 7(3) : 223-228.

[6] ZhangDeFeng. (2009). MATLAB neural network simulation and application . Beijing. Publishing House of ElectronicsIndustry.