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Prediction Intervals for Day-Ahead Photovoltaic Power Forecasts with Non-Parametric and Parametric Distributions
http://hdl.handle.net/2261/00074819
http://hdl.handle.net/2261/000748192b4b8054-fc05-4692-92d2-3ae1370ed1ce
名前 / ファイル | ライセンス | アクション |
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Published-10-04-259.pdf (2.3 MB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2018-06-22 | |||||
タイトル | ||||||
タイトル | Prediction Intervals for Day-Ahead Photovoltaic Power Forecasts with Non-Parametric and Parametric Distributions | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Photovoltaic power | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Day-ahead forecasting | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Forecast error | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Prediction intervals | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Maximum likelihood estimation | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Parametric versus non-parametric distributions | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
著者 |
Fonseca, Joao Gari da Silva Junior
× Fonseca, Joao Gari da Silva Junior× Ohtake, Hideaki× Oozeki, Takashi× Ogimoto, Kazuhiko |
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著者所属 | ||||||
値 | The University of Tokyo, Institute of Industrial Science | |||||
著者所属 | ||||||
値 | National Institute of Advanced Industrial Science and Technology, Research Center for Photovoltaics | |||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | The objective of this study is to compare the suitability of a non-parametric and 3 parametric distributions in the characterization of prediction intervals of photovoltaic power forecasts with high confidence levels. The prediction intervals of the forecasts are calculated using a method based on recent past data similar to the target forecast input data, and on a distribution assumption for the forecast error. To compare the suitability of the distributions, prediction intervals were calculated using the proposed method and each of the 4 distributions. The calculations were done for one year of day-ahead forecasts of hourly power generation of 432 PV systems. The systems have different sizes and specifications, and are installed in different locations in Japan. The results show that, in general, the non-parametric distribution assumption for the forecast error yielded the best prediction intervals. For example, with a confidence level of 85% the use of the non-parametric distribution assumption yielded a median annual forecast error coverage of 86.9%. This result was close to the one obtained with the Laplacian distribution assumption (87.8% of coverage for the same confidence level). Contrasting with that, using a Gaussian and Hyperbolic distributions yielded median annual forecast error coverage of 89.5% and 90.5%. | |||||
書誌情報 |
Journal of Electrical Engineering and Technology 巻 13, 号 4, p. 1504-1514, 発行日 2018-07 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 1975-0102 | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 2093-7423 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | info:doi/10.5370/JEET.2018.13.4.1504 | |||||
権利 | ||||||
権利情報 | CC BY-NC | |||||
著者版フラグ | ||||||
値 | publisher | |||||
出版者 | ||||||
出版者 | The Korean Institute of Electrical Engineers | |||||
関係URI | ||||||
識別子タイプ | URI | |||||
関連識別子 | http://home.jeet.or.kr/archives/view_articles.asp?seq=2110 |