Open AccessProbabilistic Load Flow Analysis for Power System Containing Wind Farms Based on Cumulant Method
Author(s) -
Ming Gao,
Pan Lv,
Zhuan Zhou,
Jingya Li,
Jingjie Xue,
Bo Zhang,
Donglei Sun
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 - 10.1088/1755-1315/647/1/012048
Subject(s) - weibull distribution , cumulant , probabilistic logic , wind power , monte carlo method , wind speed , computation , electric power system , control theory (sociology) , generator (circuit theory) , induction generator , power (physics) , computer science , mathematics , engineering , statistics , algorithm , electrical engineering , meteorology , physics , quantum mechanics , control (management) , artificial intelligence
In this paper, a probabilistic load flow computation method based on the cumulants and Edgeworth expansion theory is put forward, and is used in the analysis of system containing wind farms composed of doubly-fed induction generator. Firstly a 2-parameter Weibull function is adopted to fit the random distribution of wind speed, and then the probabilistic model for wind power generator can be established based on active power output characteristic of wind power generator. Based on the linearized AC load flow model, analysis for IEEE 30-node system with wind farm is carried out. Finally the method is compared with Monte-Carlo simulation method, and the effects of wind farms integrated to the operation of power system is analysed in detail.