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 locating abnormal operating conditions. The proposed algorithm has been applied to a real case and results are presented.
Cumulative statistical monitoring and fault forecasting for PV plants / Vergura, Silvano. - STAMPA. - (2016), pp. 66-71. (Intervento presentato al convegno 14th IMEKO TC10 Workshop on Technical Diagnostics 2016 tenutosi a Milano, Italy nel June 27-28, 2016).
Cumulative statistical monitoring and fault forecasting for PV plants
Silvano Vergura
2016-01-01
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 locating abnormal operating conditions. The proposed algorithm has been applied to a real case and results are presented.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
