Abstract
This paper presents a wind power forecasting method with confidence interval. Wind speed forecasts are calculated by regression models using GPV (Grid Point Vale) weather forecasts. The forecasts are adjusted by fuzzy inference using the latest error. The wind power forecasts are translated from the wind speed forecasts using two power-curves. They are combined by fuzzy inference depending on wind direction. The error confidence interval models are generated for each forecasting target time. Each confidence interval is combined by another fuzzy inference. The proposed method has been applied to actual power generators, and found that forecasting errors are better than the conventional methods. The results show the effectiveness of the proposed method.
| Original language | English |
|---|---|
| Title of host publication | Midwest Symposium on Circuits and Systems |
| DOIs | |
| Publication status | Published - 2011 |
| Externally published | Yes |
| Event | 54th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2011 - Seoul, Korea, Republic of Duration: 2011 Aug 7 → 2011 Aug 10 |
Other
| Other | 54th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2011 |
|---|---|
| Country | Korea, Republic of |
| City | Seoul |
| Period | 11/8/7 → 11/8/10 |
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ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Electronic, Optical and Magnetic Materials
Cite this
A wind power forecasting method with confidence interval. / Iizaka, Tatsuya; Jintsugawa, Toru; Kondo, Hideyuki; Nakanishi, Yosuke; Fukuyama, Yoshikazu; Mori, Hiroyuki.
Midwest Symposium on Circuits and Systems. 2011. 6026398.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A wind power forecasting method with confidence interval
AU - Iizaka, Tatsuya
AU - Jintsugawa, Toru
AU - Kondo, Hideyuki
AU - Nakanishi, Yosuke
AU - Fukuyama, Yoshikazu
AU - Mori, Hiroyuki
PY - 2011
Y1 - 2011
N2 - This paper presents a wind power forecasting method with confidence interval. Wind speed forecasts are calculated by regression models using GPV (Grid Point Vale) weather forecasts. The forecasts are adjusted by fuzzy inference using the latest error. The wind power forecasts are translated from the wind speed forecasts using two power-curves. They are combined by fuzzy inference depending on wind direction. The error confidence interval models are generated for each forecasting target time. Each confidence interval is combined by another fuzzy inference. The proposed method has been applied to actual power generators, and found that forecasting errors are better than the conventional methods. The results show the effectiveness of the proposed method.
AB - This paper presents a wind power forecasting method with confidence interval. Wind speed forecasts are calculated by regression models using GPV (Grid Point Vale) weather forecasts. The forecasts are adjusted by fuzzy inference using the latest error. The wind power forecasts are translated from the wind speed forecasts using two power-curves. They are combined by fuzzy inference depending on wind direction. The error confidence interval models are generated for each forecasting target time. Each confidence interval is combined by another fuzzy inference. The proposed method has been applied to actual power generators, and found that forecasting errors are better than the conventional methods. The results show the effectiveness of the proposed method.
UR - http://www.scopus.com/inward/record.url?scp=80053651926&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80053651926&partnerID=8YFLogxK
U2 - 10.1109/MWSCAS.2011.6026398
DO - 10.1109/MWSCAS.2011.6026398
M3 - Conference contribution
AN - SCOPUS:80053651926
SN - 9781612848570
BT - Midwest Symposium on Circuits and Systems
ER -