Improvement of prediction interval estimation algorithm with just-in-time modeling for PV system operation

Tomohide Yamazaki; Shinji Wakao; Yu Fujimoto; Yasuhiro Hayashi

doi:10.1109/PVSC.2015.7355994

Improvement of prediction interval estimation algorithm with just-in-time modeling for PV system operation

Tomohide Yamazaki, Shinji Wakao, Yu Fujimoto, Yasuhiro Hayashi

Advanced Collaborative Research Organization for SmartSociety

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

5 Citations (Scopus)

Abstract

Output of the photovoltaic (PV) system drastically fluctuates depending on weather conditions. Therefore users of PV systems should manage their energy usage with forecast information of the PV output. Due to the reasons above, we have developed an estimation method of X% prediction interval of solar irradiance. We have achieved a high-accuracy prediction interval for any prediction coefficient X%. However, we found that there are some errors in a case where the prediction coefficient is high. In this paper, we improve the estimation algorithm of the prediction interval.

Original language	English
Title of host publication	2015 IEEE 42nd Photovoltaic Specialist Conference, PVSC 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	9781479979448
DOIs	https://doi.org/10.1109/PVSC.2015.7355994
Publication status	Published - 2015 Dec 14
Event	42nd IEEE Photovoltaic Specialist Conference, PVSC 2015 - New Orleans, United States Duration: 2015 Jun 14 → 2015 Jun 19

Other

Other	42nd IEEE Photovoltaic Specialist Conference, PVSC 2015
Country/Territory	United States
City	New Orleans
Period	15/6/14 → 15/6/19

ASJC Scopus subject areas

Electrical and Electronic Engineering
Electronic, Optical and Magnetic Materials

UN SDGs

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

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10.1109/PVSC.2015.7355994

Cite this

Improvement of prediction interval estimation algorithm with just-in-time modeling for PV system operation. / Yamazaki, Tomohide; Wakao, Shinji; Fujimoto, Yu et al.
2015 IEEE 42nd Photovoltaic Specialist Conference, PVSC 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7355994.

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

Yamazaki, T, Wakao, S, Fujimoto, Y & Hayashi, Y 2015, Improvement of prediction interval estimation algorithm with just-in-time modeling for PV system operation. in 2015 IEEE 42nd Photovoltaic Specialist Conference, PVSC 2015., 7355994, Institute of Electrical and Electronics Engineers Inc., 42nd IEEE Photovoltaic Specialist Conference, PVSC 2015, New Orleans, United States, 15/6/14. https://doi.org/10.1109/PVSC.2015.7355994

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abstract = "Output of the photovoltaic (PV) system drastically fluctuates depending on weather conditions. Therefore users of PV systems should manage their energy usage with forecast information of the PV output. Due to the reasons above, we have developed an estimation method of X% prediction interval of solar irradiance. We have achieved a high-accuracy prediction interval for any prediction coefficient X%. However, we found that there are some errors in a case where the prediction coefficient is high. In this paper, we improve the estimation algorithm of the prediction interval.",

author = "Tomohide Yamazaki and Shinji Wakao and Yu Fujimoto and Yasuhiro Hayashi",

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N2 - Output of the photovoltaic (PV) system drastically fluctuates depending on weather conditions. Therefore users of PV systems should manage their energy usage with forecast information of the PV output. Due to the reasons above, we have developed an estimation method of X% prediction interval of solar irradiance. We have achieved a high-accuracy prediction interval for any prediction coefficient X%. However, we found that there are some errors in a case where the prediction coefficient is high. In this paper, we improve the estimation algorithm of the prediction interval.

AB - Output of the photovoltaic (PV) system drastically fluctuates depending on weather conditions. Therefore users of PV systems should manage their energy usage with forecast information of the PV output. Due to the reasons above, we have developed an estimation method of X% prediction interval of solar irradiance. We have achieved a high-accuracy prediction interval for any prediction coefficient X%. However, we found that there are some errors in a case where the prediction coefficient is high. In this paper, we improve the estimation algorithm of the prediction interval.

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Improvement of prediction interval estimation algorithm with just-in-time modeling for PV system operation

Abstract

Other

ASJC Scopus subject areas

UN SDGs

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