Prediction interval estimation of 10 second fluctuation of PV output with just-in-time modeling

Nao Kumekawa; Hayato Honma; Shinji Wakao

doi:10.1109/PVSC.2016.7749937

Prediction interval estimation of 10 second fluctuation of PV output with just-in-time modeling

Nao Kumekawa, Hayato Honma, Shinji Wakao

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

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	2016 IEEE 43rd Photovoltaic Specialists Conference, PVSC 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1825-1830
Number of pages	6
Volume	2016-November
ISBN (Electronic)	9781509027248
DOIs	https://doi.org/10.1109/PVSC.2016.7749937
Publication status	Published - 2016 Nov 18
Event	43rd IEEE Photovoltaic Specialists Conference, PVSC 2016 - Portland, United States Duration: 2016 Jun 5 → 2016 Jun 10

Other

Other	43rd IEEE Photovoltaic Specialists Conference, PVSC 2016
Country/Territory	United States
City	Portland
Period	16/6/5 → 16/6/10

ASJC Scopus subject areas

Control and Systems Engineering
Industrial and Manufacturing Engineering
Electrical and Electronic Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/PVSC.2016.7749937

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Prediction interval estimation of 10 second fluctuation of PV output with just-in-time modeling. / Kumekawa, Nao; Honma, Hayato; Wakao, Shinji.
2016 IEEE 43rd Photovoltaic Specialists Conference, PVSC 2016. Vol. 2016-November Institute of Electrical and Electronics Engineers Inc., 2016. p. 1825-1830 7749937.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kumekawa, N, Honma, H & Wakao, S 2016, Prediction interval estimation of 10 second fluctuation of PV output with just-in-time modeling. in 2016 IEEE 43rd Photovoltaic Specialists Conference, PVSC 2016. vol. 2016-November, 7749937, Institute of Electrical and Electronics Engineers Inc., pp. 1825-1830, 43rd IEEE Photovoltaic Specialists Conference, PVSC 2016, Portland, United States, 16/6/5. https://doi.org/10.1109/PVSC.2016.7749937

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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.",

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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.

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Prediction interval estimation of 10 second fluctuation of PV output with just-in-time modeling

Abstract

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ASJC Scopus subject areas

UN SDGs

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