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成果報告書詳細
管理番号20170000000731
タイトル*平成28年度中間年報 太陽光発電システム効率向上・維持管理技術開発プロジェクト 太陽光発電システム維持管理技術の開発 HEMSを用いたPV発電電力量の遠隔自動診断と故障部位把握方法の開発
公開日2017/8/29
報告書年度2016 - 2016
委託先名京セラ株式会社
プロジェクト番号P14019
部署名新エネルギー部
和文要約
英文要約Title : Photovoltaic system efficiency improvement / the maintenance management developing technologies project. Development of the maintenance management technologies of Photovoltaic system. / Development of an automated remote diagnosis of Photovoltaic output and a method to identify faulty module with using HEMS(Home Energy Management System) controller. (FY2014-FY2017) FY2016 Annal Report

Following is contents and accomplishment of research & development.
(1) Development of an automated remote diagnosis system of Photovoltaic Generation
(a)We have installed the diagnosis algorithm to identify sun shadow that has been investigated in 2016
and 2017 into the an automated remote diagnosis system of Photovoltaic Generation to utilize
pyranometers installed into the meteorological offices and an image of clouds from a weather satellite
(b) Research with regard to reliability of automated remote diagnosis system of Photovoltaic Generation.
We have acknowledged that the operation index showing power generation characteristic (= actual
power generation/ideal power generation) fluctuates very much depending on the date. We have
engaged in research of reliability of the operation index since fluctuation of it makes judgment to
conduct check & maintenance be difficult.
   We extracted main factors that have an effect of an error of calculating solar radiation by machine
learning technique. It results in that solar radiation intensity and clearness index (ground solar
radiation / extraterrestrial solar radiation) and their fluctuations every time at the PV site
have much effect on it.
(2) Research of diagnosis system to recognize the module of which Photovoltaic Generation characteristics
is degraded.
(a) We have made trial production of diagnosis system that locates in front of PCS and makes it
possible to take a measurement IV of multiple strings simultaneously. We confirmed its measurement
accuracy is almost the same as accuracy of IV curve tracer offered commercially.
b) Research of algorithm to recognize the module of which Photovoltaic Generation characteristics is
degraded by analyzing characteristics data of power generation.
We have conducted a fault simulation experiment in following 3 patterns: a) Isc(Short Circuit Current)
decrease b) Series resistance increase c) Parallel resistance decrease
where we were able to detect the strings as fault that includes a module of which generation
characteristics was degraded by 30% and detect the strings as normal that includes a module of
which generation characteristics was degraded by 15%, confirmed this algorithm was effective.
(3) Verification test of an automated remote diagnosis system of Photovoltaic Generation.
(a) Installation of HEMS into houses where Photovoltaic Generation were already installed.
We have installed 520 HEMS until 31th March that are connected to the server into houses where
Photovoltaic Generation were already installed and are collecting generation data via the server.
(b) Verification test.
There is so far no house of which generation characteristics of PV system is degraded .
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