Abstract
With the rapid development of modern economy and the increase of urbanization rate, the scale of power grid is expanding, and the installed power grid equipment is increasing. Power grid equipment can produce different models based on different standards. Large scale power flow analysis of power grid needs to unify the model of power grid equipment. However, the traditional conversion method is low, which can not meet a large number of grid models generated by the development of power grid planning. Based on the functions of learning, storage and self-adaptive of artificial neural network, this paper proposes a large-scale transformation method of power grid equipment model based on Improved BP neural network. It can improve the efficiency of model transformation of traditional power grid equipment and meet the needs of rapid development of power grid.
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