Title :
A DTW and BPN Based Approach for Modeling Nonlinear Load
Author :
Xu, Gang ; Tian, Shiyang
Author_Institution :
Sch. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing, China
Abstract :
It is known that a direct application of artificial neural network (ANN) for modeling high power, nonlinear, and impact load may lead to inaccuracies. This paper proposes an approach that the characteristic of the high power, nonlinear and time varying load is modeled by advanced ANN, which is implemented by using back propagation network (BPN) and dynamic time warping (DTW) algorithms. The model of the nonlinear load can be accurately established, the consumption of the voltage, reactive power and the precision of the model can be obtained. Then the type of the reactive power compensation devices and the capacity of the reactive power compensation equipments can be effectively determined.
Keywords :
backpropagation; load (electric); neural nets; power system simulation; reactive power; time warp simulation; artificial neural network; back propagation network; dynamic time warping algorithm; high power load; nonlinear load modeling; reactive power compensation device; reactive power compensation equipment; time varying load; voltage consumption; Artificial neural networks; Fluctuations; Heuristic algorithms; Load modeling; Reactive power; Voltage fluctuations; Voltage measurement;
Conference_Titel :
Engineering and Technology (S-CET), 2012 Spring Congress on
Conference_Location :
Xian
Print_ISBN :
978-1-4577-1965-3
DOI :
10.1109/SCET.2012.6342068