일사량 직산분리 모델에 따른 표준기상연도 데이터와 태양광 발전 예측량의 불확실성
Variation of Solar Photovoltaic Power Estimation due to Solar Irradiance Decomposition Models
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초록
Long-term solar irradiance data are required for reliable performance evaluation and feasibility analysis of solar photovoltaic systems. However, measurement data of the global horizontal irradiance (GHI) are only available for major cities in Korea. Neither the direct normal irradiance (DNI) nor the diffuse horizontal irradiance (DHI) are available, which are also needed to calculate the irradiance on the tilted surface of PV array. It is a simple approach to take advantage of the decomposition model that extracts DNI and DHI from GHI. In this study, we investigate variations of solar PV power estimation due to the choice of decomposition model. The GHI data from Korea Meteorological Administration (KMA) were used and different sets of typical meteorological year (TMY) data using some well-known decomposition models were generated. Then, power outputs with the different TMY data were calculated, and a variation of 3.7% was estimated due to the choice of decomposition model.
Abstract
Long-term solar irradiance data are required for reliable performance evaluation and feasibility analysis of solar photovoltaic systems. However, measurement data of the global horizontal irradiance (GHI) are only available for major cities in Korea. Neither the direct normal irradiance (DNI) nor the diffuse horizontal irradiance (DHI) are available, which are also needed to calculate the irradiance on the tilted surface of PV array. It is a simple approach to take advantage of the decomposition model that extracts DNI and DHI from GHI. In this study, we investigate variations of solar PV power estimation due to the choice of decomposition model. The GHI data from Korea Meteorological Administration (KMA) were used and different sets of typical meteorological year (TMY) data using some well-known decomposition models were generated. Then, power outputs with the different TMY data were calculated, and a variation of 3.7% was estimated due to the choice of decomposition model.
참고문헌 (7)
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- 유호천, "건물에너지 평가를 위한 다양한 표준기상데이터 산출모델의 비교분석", 대한건축학회논문집, 30(3), pp.215~222 (2014), 대한건축학회
- Users manual for TMY3 data sets, "Wilcox, S.", NREL, ~, pp.NREL (2008), TP-581-43156
- 이현진, "태양에너지 시스템에 적합한 표준기상데이터의 제작과 일사량 데이터 분석", 신재생에너지, 13(3), pp.24~33 (2017), 한국신·재생에너지학회
- "SAM(System Advisor Model)"[URL]