Abstract
In Finland, as there is no feed-in tariff, the wind power producers have
to make contracts on how the electricity is sold and also make contracts for
balance settlement. For this paper, wind power production is estimated 1–38
hours ahead for wind turbines located in 4 small clusters about 380 km apart
on the West coast of Finland. Wind speed forecasts from the
very-high-resolution ETA meteorological forecast model run by Foreca Ltd are
used together with two production forecast models, which employ neural
networks developed by Cybersoft and time series modeling by VTT. To show the
effect of even more spread wind power production in Finland, prediction errors
are determined for both one site, one producer and for the whole West Coast
of Finland. Balancing costs resulting from day-ahead forecasts are estimated
with year 2004 price data. Some example weeks are taken to examine the
possibilities of improving the meteorological prediction for wind speeds.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 6th International Workshop on Large-scale Integration of Wind Power and Transmission Networks for Offshore Wind Farms |
| Subtitle of host publication | Delft, Netherland, 26-28 October 2006 |
| Pages | 113-120 |
| Publication status | Published - 2006 |
| MoE publication type | A4 Article in a conference publication |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Keywords
- Forecasting
- neural network applications
- time series
- wind energy
- weather forecasting
- electricity markets
- balancing costs
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