Short-term wind power prediction based on Markov chain and numerical weather prediction models: A case study of Fakken wind farm
Permanent link
https://hdl.handle.net/10037/6791Date
2014-06-02Type
Master thesisMastergradsoppgave
Author
Jacobsen, MortenAbstract
Rising energy demands and a growing focus on sustainable development have
made electricity production from wind energy an attractive alternative to
fossil fuels. However the natural variability of wind makes it challenging to
implement wind energy into the electrical grid. Accurate and reliable wind
power predictions are seen as a key element for an increased penetration of
wind energy.
This study presents a set of statistical power prediction models using
the concept of Markov chains, based on various input parameters, such as
wind speed, direction and power output. The models have been trained
and tested using numerical weather predictions and historical data obtained
from a meteorological station and wind turbine at Fakken wind farm in the
time period 2. May 2013 - 31. March 2014. Several of the models were found
to have lower NRMSE than the currently used persistent model (19.08 %),
with the best performing model having a NRMSE of 16.84 %. This 2.25 %
lower NRMSE corresponds to approximately 3 100 000 kWh of the anually
electricity production from Fakken wind farm.
A statistical analysis of Fakken wind farm showed the majority of winds
occurring from the straits between Arnøya and Lenangsøyra to the southeast and between Reinøya and Lenangsøyra to the south. Winds were also
commonly seen from southwest and to the northwest, while eastern and
northeastern winds were rarely observed. Westerly winds were found to be
much more tubulent than other directions, with a generally lower power
output observed. This is most likely due to the occurerence of mountain
waves for winds crossing the mountain range to the west.
Publisher
UiT The Arctic University of NorwayUiT Norges arktiske universitet
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