TY - GEN
T1 - Load forecasting via low rank plus sparse matrix factorization
AU - Kim, Seung Jun
AU - Giannakis, Geogios B.
PY - 2013
Y1 - 2013
N2 - Accurate imputation and prediction of load data are important prerequisites for many tasks of power systems, especially as renewables and plug-in electric vehicles penetrate the grid. A low-rank and sparse matrix factorization model is considered for load inference tasks to capture spatial as well as temporal structures in multi-site load data. The low-rank structure captures periodic patterns, and sparse matrix factors explain localized and clustered signatures. In order to predict load values for future time instants (and possibly for unforeseen sites), prior knowledge on correlations is necessarily incorporated in a nonparametric kernel-based learning framework. An efficient learning algorithm is also derived. Tests with real load data verify the efficacy of the proposed approach.
AB - Accurate imputation and prediction of load data are important prerequisites for many tasks of power systems, especially as renewables and plug-in electric vehicles penetrate the grid. A low-rank and sparse matrix factorization model is considered for load inference tasks to capture spatial as well as temporal structures in multi-site load data. The low-rank structure captures periodic patterns, and sparse matrix factors explain localized and clustered signatures. In order to predict load values for future time instants (and possibly for unforeseen sites), prior knowledge on correlations is necessarily incorporated in a nonparametric kernel-based learning framework. An efficient learning algorithm is also derived. Tests with real load data verify the efficacy of the proposed approach.
UR - http://www.scopus.com/inward/record.url?scp=84901285190&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84901285190&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.2013.6810586
DO - 10.1109/ACSSC.2013.6810586
M3 - Conference contribution
AN - SCOPUS:84901285190
SN - 9781479923908
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 1682
EP - 1686
BT - Conference Record of the 47th Asilomar Conference on Signals, Systems and Computers
PB - IEEE Computer Society
T2 - 2013 47th Asilomar Conference on Signals, Systems and Computers
Y2 - 3 November 2013 through 6 November 2013
ER -