This paper proposes a procedure based on statistical tools for diagnosis of PhotoVoltaic (PV) plants. As the data are acquired, statistical analyses are realized. At every new loop other data are added to the previous ones, implementing a cumulative statistical analysis. In this manner it is possible to follow the trend of some specific parameters and to understand the real operation of the PV plant as the environmental conditions change during the year. The proposed approach, based on ANOVA and Kruskal-Wallis tests, is effective in detecting and locating abnormal operating conditions. The proposed algorithm has been applied to a real case and results are presented

Cumulative Statistical Analysis to Monitor the Energy Performance of PV Plants

Silvano Vergura
2011

Abstract

This paper proposes a procedure based on statistical tools for diagnosis of PhotoVoltaic (PV) plants. As the data are acquired, statistical analyses are realized. At every new loop other data are added to the previous ones, implementing a cumulative statistical analysis. In this manner it is possible to follow the trend of some specific parameters and to understand the real operation of the PV plant as the environmental conditions change during the year. The proposed approach, based on ANOVA and Kruskal-Wallis tests, is effective in detecting and locating abnormal operating conditions. The proposed algorithm has been applied to a real case and results are presented
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11589/10516
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