An Estimation Method of Photovoltaics Power Output using Satellite Images and Power Flow
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- Yasunami Kazuhiro
- Advanced Technology R&D Center, Mitsubishi Electric Corporation
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- Yatsubo Osamu
- Power System Technology Laboratory, R&D Center, The Kansai Electric Power Co., Inc.
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- Washio Takashi
- Department of Reasoning for Intelligence, Division of Information and Quantum Science, The Institute of Scientific and Industrial Research, Osaka University
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- Takada Nozomu
- Meteorological Engineering Center, Inc.
Bibliographic Information
- Other Title
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- 衛星画像と電力潮流を利用した太陽光発電出力推定手法
- エイセイ ガゾウ ト デンリョク チョウリュウ オ リヨウ シタ タイヨウコウ ハツデン シュツリョク スイテイ シュホウ
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Abstract
<p>There is a growing need to use photovoltaic (PV) technology to mitigate global warming and the depletion of fossil fuels. However, the high network penetration of PVs potentially lessen the stability and the reliability of electrical power systems in various ways. Under its high network penetration, monitoring of the unmeasurable power outputs of PVs is needed for the proper operations of an electrical power system. To suffice this need, a novel method was proposed to estimate the PV power output of the system using the measured power flow and solar radiation intensity estimated from satellite image in our previous work. However, it occasionally causes large estimation errors of the PV power output based on the wrong estimation of parameters induced by a large data sampling interval. To address this issue, in this paper, we improved our proposed method by introducing an parameter estimation procedure to exclude outliers of estimated values and increase the number of data used for estimation. We confirmed its enhanced accuracy using data observed from The Kansai Electric Power Co., Inc.</p>
Journal
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- IEEJ Transactions on Electronics, Information and Systems
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IEEJ Transactions on Electronics, Information and Systems 140 (2), 129-136, 2020-02-01
The Institute of Electrical Engineers of Japan
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Keywords
Details 詳細情報について
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- CRID
- 1390002184871757056
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- NII Article ID
- 130007793751
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- NII Book ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL BIB ID
- 030245070
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed