TY - GEN

T1 - Missing and outlier of PV electric power

T2 - 38th ASES National Solar Conference 2009, SOLAR 2009

AU - Hsu, Kun Jung

AU - Lai, Chi Ming

PY - 2009

Y1 - 2009

N2 - In practice, we often encounter some missing and outlier data of a Building Integrated Photovoltaic system (BIPVs) among the data acquisitions. It may because of computer shut down, the electric pulse to sensitive sensor, thus affect the reliability of the whole data. Without complete data, we cannot catch the whole picture of the annual electric power generated respect to the BIPV system. The paper constructed a regression model according to the properties of electricity generated theory of photovoltaic, and related it to the characteristic of the data collection. Using the regression model and data collected from a PVs installed on the roof of a house located at Kao-Hsiung, this paper showed how the missing and outlier data can be interpolated properly. By using the seasonal model, the regression analysis showed that all variables in seasonal model are all significance to reject the hypothesis of no effect on the electric yield of the PVs (H0: the coefficient = 0) at 5% significant level. Finally, using the estimates coefficient of the estimators the missing and outlier data were interpolated, the daily yields of the BIPV system of the whole year were plotted.

AB - In practice, we often encounter some missing and outlier data of a Building Integrated Photovoltaic system (BIPVs) among the data acquisitions. It may because of computer shut down, the electric pulse to sensitive sensor, thus affect the reliability of the whole data. Without complete data, we cannot catch the whole picture of the annual electric power generated respect to the BIPV system. The paper constructed a regression model according to the properties of electricity generated theory of photovoltaic, and related it to the characteristic of the data collection. Using the regression model and data collected from a PVs installed on the roof of a house located at Kao-Hsiung, this paper showed how the missing and outlier data can be interpolated properly. By using the seasonal model, the regression analysis showed that all variables in seasonal model are all significance to reject the hypothesis of no effect on the electric yield of the PVs (H0: the coefficient = 0) at 5% significant level. Finally, using the estimates coefficient of the estimators the missing and outlier data were interpolated, the daily yields of the BIPV system of the whole year were plotted.

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M3 - Conference contribution

AN - SCOPUS:84867266678

SN - 9781615673636

T3 - 38th ASES National Solar Conference 2009, SOLAR 2009

SP - 3766

EP - 3809

BT - 38th ASES National Solar Conference 2009, SOLAR 2009

Y2 - 11 May 2009 through 16 May 2009

ER -