Quality Analysis of Photovoltaic System Using Descriptive Statistics of Power Performance Index

Abstract

The performance evaluation (PE) of the Photovoltaic(PV) system is an index representing the efficiency and reliability of the system. Most PE indicators evaluate the ratio of theoretically calculated power generation to actually measured power generation. The closer the ratio is to 1, the more ideal the PV system is. PV system varies depending on weather conditions and regional characteristics, especially on the types of sensors and measuring variables. Floating Photovoltaics(FPVs) and Marine photovoltaics(MPVs) vary with the environmental variables more as it is installed on the water and sea. In this paper, on the contrary to the existing PE methods, the most accurate regression model considering ambient temperature, relative humidity, and wind speed was used to predict the power in order to improve the accuracy. The optimal PE method for the PV system to easily and accurately detect failures of the PV system is proposed. Data from three FPVs in the same environment were analyzed for 1 year. The PV power prediction model including the wind speed and relative humidity was used to improve accuracy. The quality diagnosis was performed with an improved PE and the impact of various events can be represented through this. In this paper, the distribution of the corresponding Power Performance Index (PPI) values was analyzed using a descriptive statistic method, and indicators in terms of quality control were presented. The PV power generation state can be determined by the location of the average and median values of the boxplot. The fluctuation of PV power generation was identified using the size change of Inter Quartile Range (IQR), which represents the degree of data scattering. As a result, it was confirmed that failure occurred in the system when the IQR value is 2 times bigger than the normal IQR value.