사우디아라비아 태양광 발전 시스템의 성능 분석
We have analyzed the performance of 58 kWp photovoltaic (PV) power systems installed in Jeddah, Saudi Arabia. Performance ratio (PR) of 3 PV systems with 3 desert-type PV modules using monitoring data for 1 year showed 85.5% on average. Annual degradation rate of 5 individual modules achieved 0.26%,...
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| Published in | 한국태양에너지학회 논문집 Vol. 37; no. 1; pp. 81 - 90 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | Korean |
| Published |
한국태양에너지학회
2017
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1598-6411 2508-3562 |
| DOI | 10.7836/kses.2017.37.1.081 |
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| Abstract | We have analyzed the performance of 58 kWp photovoltaic (PV) power systems installed in Jeddah, Saudi Arabia. Performance ratio (PR) of 3 PV systems with 3 desert-type PV modules using monitoring data for 1 year showed 85.5% on average. Annual degradation rate of 5 individual modules achieved 0.26%, the regression model using monitoring data for the specified interval of one year showed 0.22%. Root mean square error (RMSE) of 6 big data analysis models for power output prediction in May 2016 was analyzed 2.94% using a support vector regression model. |
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| AbstractList | We have analyzed the performance of 58 kWp photovoltaic (PV) power systems installed in Jeddah, Saudi Arabia. Performance ratio (PR) of 3 PV systems with 3 desert-type PV modules using monitoring data for 1 year showed 85.5% on average. Annual degradation rate of 5 individual modules achieved 0.26%, the regression model using monitoring data for the specified interval of one year showed 0.22%. Root mean square error (RMSE) of 6 big data analysis models for power output prediction in May 2016 was analyzed 2.94% using a support vector regression model. We have analyzed the performance of 58 kWp photovoltaic (PV) power systems installed in Jeddah, Saudi Arabia. Performance ratio (PR) of 3 PV systems with 3 desert-type PV modules using monitoring data for 1 year showed 85.5% on average. Annual degradation rate of 5 individual modules achieved 0.26%, the regression model using monitoring data for the specified interval of one year showed 0.22%. Root mean square error (RMSE) of 6 big data analysis models for power output prediction in May 2016 was analyzed 2.94% using a support vector regression model. KCI Citation Count: 0 |
| Author | 오원욱(Oh Wonwook) 천성일(Chan Sung-Il) 강소연(Kang Soyeon) |
| Author_xml | – sequence: 1 fullname: 오원욱(Oh Wonwook) – sequence: 2 fullname: 강소연(Kang Soyeon) – sequence: 3 fullname: 천성일(Chan Sung-Il) |
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| DocumentTitleAlternate | Performance Analysis of Photovoltaic Power System in Saudi Arabia |
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| Keywords | 사막형(Desert type) 태양광 발전 시스템(PV power system) 빅데이터 분석(Big data analysis) 발전성능(Performance Ratio) 소일링(Soiling) 발전량 예측(Power prediction) |
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| PublicationTitle | 한국태양에너지학회 논문집 |
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| Title | 사우디아라비아 태양광 발전 시스템의 성능 분석 |
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