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  1. 134 生産技術研究所
  2. 45 エネルギー工学連携研究センター
  3. 1344510 学術雑誌論文
  1. 0 資料タイプ別
  2. 10 学術雑誌論文
  3. 014 自然科学

Regional Forecasts of Photovoltaic Power Generation According to Different Data Availability Scenarios: A Study of 4 Methods

http://hdl.handle.net/2261/00076318
http://hdl.handle.net/2261/00076318
2197e9e2-9baa-4a98-994b-9f72941211dd
名前 / ファイル ライセンス アクション
PiP_format-Rep.pdf PiP_format-Rep.pdf (2.1 MB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2018-10-10
タイトル
タイトル Regional Forecasts of Photovoltaic Power Generation According to Different Data Availability Scenarios: A Study of 4 Methods
言語
言語 eng
キーワード
主題Scheme Other
主題 photovoltaic systems
キーワード
主題Scheme Other
主題 regional power generation
キーワード
主題Scheme Other
主題 support vector regression
キーワード
主題Scheme Other
主題 stratified sampling
キーワード
主題Scheme Other
主題 principal component analysis
資源タイプ
資源 http://purl.org/coar/resource_type/c_6501
タイプ journal article
著者 Fonseca, Joao Gari da Silva Junior

× Fonseca, Joao Gari da Silva Junior

WEKO 152318

Fonseca, Joao Gari da Silva Junior

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Oozeki, Takashi

× Oozeki, Takashi

WEKO 152319

Oozeki, Takashi

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Ohtake, Hideaki

× Ohtake, Hideaki

WEKO 152320

Ohtake, Hideaki

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Takashima, Takumi

× Takashima, Takumi

WEKO 152321

Takashima, Takumi

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Ogimoto, Kazuhiko

× Ogimoto, Kazuhiko

WEKO 152322

Ogimoto, Kazuhiko

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著者所属
著者所属 National Institute of Advanced Industrial Science and Technology
著者所属
著者所属 Institute of Industrial Science (IIS), Collaborative Research Center for Energy Engineering (CEE), Tokyo University
抄録
内容記述タイプ Abstract
内容記述 The development of methods to forecast PV power generation regionally is of utmost importance to support the spread of such power systems in current power grids. The objective of this study is to propose and to evaluate methods to forecast regional PV power one-day ahead of time and to compare their performances. Four forecast methods were regarded of which 2 are new ones proposed in this study. Together they characterize a set of forecast methods that can be applied in different scenarios regarding availability of data and infrastructure to make the forecasts. The forecast methods were based on the use of support vector regression and weather prediction data. Evaluations were done for 1 year of hourly forecasts using data of 273 PV systems installed in 2 adjacent regions in Japan, Kanto and Chubu. The results show the importance of selecting the proper forecast method regarding the region characteristics. For Chubu, the region with a variety of weather conditions, the forecast methods based on single systems’ forecasts and the one based on stratified sampling provided the best results. In this case the best annual normalized RMSE and MAE were 0.25 kWh/kWhavg and 0.15 kWh/kWhavg. For Kanto, with homogeneous weather conditions, the 4 methods performed similarly. In this case, the lowest annual forecast errors were 0.33 kWh/kWhavg for the normalized RMSE and 0.202 kWh/kWhavg for the normalized MAE.
書誌情報 Progress in Photovoltaics

巻 23, 号 10, p. 1203-1218, 発行日 2015-10
ISSN
収録物識別子タイプ ISSN
収録物識別子 1062-7995
ISSN
収録物識別子タイプ ISSN
収録物識別子 1099-159X
DOI
識別子タイプ DOI
関連識別子 info:doi/10.1002/pip.2528
権利
権利情報 Copyright © 2014 John Wiley & Sons, Ltd.
著者版フラグ
値 author
出版者
出版者 John Wiley & Sons
異版である
関連タイプ isVersionOf
識別子タイプ URI
関連識別子 https://doi.org/10.1002/pip.2528.
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