TY - GEN
T1 - Bayesian separation of wind power generation signals
AU - Yoon, Ji Won
AU - Fusco, Francesco
AU - Wurst, Michael
PY - 2012
Y1 - 2012
N2 - One of most challenging and important tasks for electricity grid operators and utility companies is to predict and estimate the precise energy consumption and generation of individual households which have their own decentralized production system. This is a under-determined source separation problem since only the difference between energy production and consumption in the micro-generation system is visible. Therefore, we present a latent variable model with a polynomial regression form for the separation and then the model is used by several statistical algorithms to explore the underlying energy consumption and production from the differenced signals. In order to efficiently find global optima of the hidden variables of the model, we develop a source separation algorithm based on the Integrated Nested Laplace Approximation (INLA).
AB - One of most challenging and important tasks for electricity grid operators and utility companies is to predict and estimate the precise energy consumption and generation of individual households which have their own decentralized production system. This is a under-determined source separation problem since only the difference between energy production and consumption in the micro-generation system is visible. Therefore, we present a latent variable model with a polynomial regression form for the separation and then the model is used by several statistical algorithms to explore the underlying energy consumption and production from the differenced signals. In order to efficiently find global optima of the hidden variables of the model, we develop a source separation algorithm based on the Integrated Nested Laplace Approximation (INLA).
UR - http://www.scopus.com/inward/record.url?scp=84874570345&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84874570345
SN - 9784990644109
T3 - Proceedings - International Conference on Pattern Recognition
SP - 2660
EP - 2663
BT - ICPR 2012 - 21st International Conference on Pattern Recognition
T2 - 21st International Conference on Pattern Recognition, ICPR 2012
Y2 - 11 November 2012 through 15 November 2012
ER -