Open AccessCopula Correlation Modeling of Wind Farms Generation and Its Application in Power Dispatching
Author(s) -
Ning Nan,
Xiaokang Wu,
Qianwen Shao,
Ming Xie,
Binbin Huang,
Shujia Li
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 - 10.1088/1755-1315/766/1/012045
Subject(s) - copula (linguistics) , randomness , wind power , econometrics , correlation , joint probability distribution , entropy (arrow of time) , correlation coefficient , computer science , mathematics , statistics , engineering , physics , geometry , electrical engineering , quantum mechanics
With the large-scale integration of wind power into the grid, a model that can accurately describe the randomness of wind farm output and the correlation between them is of great significance to be constructed. A joint distribution function of multiple wind plants output model based on Copula theory is constructed. By introducing correlation and fitting coefficient, the attribute recognition theory is put forward to select the optimal model based on entropy weight method. Finally, the validity of Copula modeling is verified by using the synchronized historical data of California coastal wind farms as a sample. The results show that t-copula can not only describe the correlation between the original variables well, but also fit the empirical distribution function of the original samples accurately.