Assessment of PV system performance with incomplete monitoring data

An analysis of PV system performance requires both meteorological and electrical data for the assessment period. However, actual in-field data acquisition is rarely 100%, often resulting in a significant amount of incomplete data sets for performance assessment. These gaps, if not taken into account, may add noticeable bias in yield assessment and thus estimations of the lacking data need to be made. An approach of back-filling the required data is given and validated here. Three different categories of data loss are identified and case-specific methods of synthesising missing data are developed. The integrity of the performance assessment process is assessed. The three cases of data loss are defined as: missing meteorological data only, missing electrical monitoring data only and missing both electrical and meteorological data. Case-specific methods are proposed and their performance against measured data is evaluated statistically by means of: root mean square error (RMSE), mean absolute error (MAE) and mean bias error (MBE). The inferred monthly performance ratio on two of the selected cases showed accurate agreement against measured data presenting significantly low MBE values, equal or less than -0.01.