Abstract
One of the critical challenges of wind power integration
is the variable and uncertain nature of the resource.
This paper investigates the variability and uncertainty
in wind forecasting for multiple power systems in six
countries. An extensive comparison of wind forecasting is
performed among the six power systems by analyzing the
following scenarios: (i) wind forecast errors throughout
a year; (ii) forecast errors at a specific time of day
throughout a year; (iii) forecast errors at peak and
off-peak hours of a day; (iv) forecast errors in
different seasons; (v) extreme forecasts with large
overforecast or underforecast errors; and (vi) forecast
errors when wind power generation is at different
percentages of the total wind capacity. The kernel
density estimation method is adopted to characterize the
distribution of forecast errors. The results show that
the level of uncertainty and the forecast error
distribution vary among different power systems and
scenarios. In addition, for most power systems, (i) there
is a tendency to underforecast in winter; and (ii) the
forecasts in winter generally have more uncertainty than
the forecasts in summer
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 12th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms, WIW2013 |
| Editors | Uta Betancourt, Thomas Ackermann |
| Place of Publication | Darmstadt |
| Publisher | Energynautics GmbH |
| Number of pages | 7 |
| ISBN (Print) | 978-3-9813870-7-0 |
| Publication status | Published - 2013 |
| MoE publication type | B3 Non-refereed article in conference proceedings |
| Event | 12th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms, WIW13 - London, United Kingdom Duration: 22 Oct 2013 → 24 Oct 2013 Conference number: 12 |
Conference
| Conference | 12th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Farms, WIW13 |
|---|---|
| Abbreviated title | WIW13 |
| Country/Territory | United Kingdom |
| City | London |
| Period | 22/10/13 → 24/10/13 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy
Keywords
- Wind forecasting
- reliability
- power systems
- uncertainty
- variability
- wind power
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