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
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017
Y1 - 2017
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
AN - SCOPUS:85048464465
T3 - 2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017
SP - 3494
EP - 3499
BT - 2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 44th IEEE Photovoltaic Specialist Conference, PVSC 2017
Y2 - 25 June 2017 through 30 June 2017
ER -