Abstract
The Output of photovoltaic (PV) systems depends on weather conditions. Therefore if there is a large introduction of PV systems, the power quality in the distribution system will be affected. One effective solution for this problem is to predict PV output. Although the need for prediction information for short period fluctuation is increasing, it is difficult to directly predict a steep fluctuation on the second time scale. For the prediction information of PV output, we propose the estimation of the prediction interval of the fluctuation widths on a 10 second scale. In this paper, we carry out the prediction by using the conventional method, with one-dimensional kernel density estimation, and the proposed method, with two-dimensional kernel density estimation. Then, we discuss the effectiveness of the proposed method based on several numerical indexes.
| Original language | English |
|---|---|
| Title of host publication | 2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1-6 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781509056057 |
| DOIs | |
| Publication status | Published - 2018 May 25 |
| Event | 44th IEEE Photovoltaic Specialist Conference, PVSC 2017 - Washington, United States Duration: 2017 Jun 25 → 2017 Jun 30 |
Other
| Other | 44th IEEE Photovoltaic Specialist Conference, PVSC 2017 |
|---|---|
| Country | United States |
| City | Washington |
| Period | 17/6/25 → 17/6/30 |
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ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Electrical and Electronic Engineering
- Electronic, Optical and Magnetic Materials
Cite this
Prediction interval estimation of 10 second fluctuation of PV output with just-in-time modeling. / Kumekawa, Nao; Honma, Hayato; Wakao, Shinji.
2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-6.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Prediction interval estimation of 10 second fluctuation of PV output with just-in-time modeling
AU - Kumekawa, Nao
AU - Honma, Hayato
AU - Wakao, Shinji
PY - 2018/5/25
Y1 - 2018/5/25
N2 - The Output of photovoltaic (PV) systems depends on weather conditions. Therefore if there is a large introduction of PV systems, the power quality in the distribution system will be affected. One effective solution for this problem is to predict PV output. Although the need for prediction information for short period fluctuation is increasing, it is difficult to directly predict a steep fluctuation on the second time scale. For the prediction information of PV output, we propose the estimation of the prediction interval of the fluctuation widths on a 10 second scale. In this paper, we carry out the prediction by using the conventional method, with one-dimensional kernel density estimation, and the proposed method, with two-dimensional kernel density estimation. Then, we discuss the effectiveness of the proposed method based on several numerical indexes.
AB - The Output of photovoltaic (PV) systems depends on weather conditions. Therefore if there is a large introduction of PV systems, the power quality in the distribution system will be affected. One effective solution for this problem is to predict PV output. Although the need for prediction information for short period fluctuation is increasing, it is difficult to directly predict a steep fluctuation on the second time scale. For the prediction information of PV output, we propose the estimation of the prediction interval of the fluctuation widths on a 10 second scale. In this paper, we carry out the prediction by using the conventional method, with one-dimensional kernel density estimation, and the proposed method, with two-dimensional kernel density estimation. Then, we discuss the effectiveness of the proposed method based on several numerical indexes.
UR - http://www.scopus.com/inward/record.url?scp=85048464465&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85048464465&partnerID=8YFLogxK
U2 - 10.1109/PVSC.2017.8366397
DO - 10.1109/PVSC.2017.8366397
M3 - Conference contribution
SP - 1
EP - 6
BT - 2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
ER -