Open AccessFast Calculation of Steady-state Voltage in Power System Based on Monte Carlo and Deep Learning
Author(s) -
Ting Zhou,
Xiaochun Xu,
Jianyi Li,
Xian Xu,
Peng Li,
Wenbin Shi,
Jiahao Wang
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/645/1/012068
Subject(s) - computer science , monte carlo method , steady state (chemistry) , voltage , node (physics) , wind power , electric power system , grid , power (physics) , simulation , engineering , electrical engineering , mathematics , physics , statistics , chemistry , structural engineering , quantum mechanics , geometry
It is of great significance to calculate the steady-state voltage of the power grid including the access of complex distributed power sources. To solve the problems of strong intermittent and high volatility of existing wind turbines, photovoltaics and other new energy sources, this paper generates a large number of section data in different scenarios according to the integrated probability model, and uses large data sets to train deep learning models. The steady-state voltage of each node is calculated for the distribution network under different scenarios in the IEEE 39-node system. The results of the calculation example show that the deep learning model trained by the proposed method can achieve 98% accuracy with less time of calculation. It is suitable for calculating the steady-state voltage of the large-scale complex power system.