統計学輪講（第２６回）

日時      2010年11月2日(火)    15時～16時40分
場所      経済学部新棟３階第３教室
講演者    Marc G. Genton (Texas A&M University)
演題      Powering Up With Space-Time Wind Forecasting

概要

The technology to harvest electricity from wind energy
is now advanced enough to make entire cities powered
by it a reality. High-quality, short-term forecasts of
wind speed are vital to making this a more reliable
energy source. Gneiting et al. (2006) have introduced a
model for the average wind speed two hours ahead based
on both spatial and temporal information. The forecasts
produced by this model are accurate, and subject to accuracy,
the predictive distribution is sharp, that is, highly
concentrated around its center. However, this model is
split into nonunique regimes based on the wind direction
at an offsite location. This project both generalizes and
improves upon this model by treating wind direction as a
circular variable and including it in the model. It is robust
in many experiments, such as predicting wind at other locations.
We compare this with the more common approach of modeling wind
speeds and directions in the Cartesian space and use a skew-t
distribution for the errors. The quality of the predictions from
all of these models can be more realistically assessed with a
loss measure that depends upon the power curve relating wind
speed to power output. This proposed loss measure yields more
insight into the true value of each model's predictions.
This talk is based on joint work with Amanda Hering.