Impact of time resolution averaging analysis on integrated photovoltaic with office buildings and grid interaction metrics: Case study

Abstract

The matching of the photovoltaic (PV) power generation profile with that of the office building is very vital to improving the self-consumption index and the building’s self-sufficiency degree. This study focuses on grid interaction and load matching metrics of office building integrated PV systems. The test system in this study is an 8 kWp grid connected PV system located at the Electronics Research Institute (ERI), Giza, Egypt. Different data on the PV inverter output side and those between the load and the grid are measured at different time steps to investigate the effect of the different time steps on the performance and sizing of the utilized PV array, through estimating the maximum PV power and the load power, as well as the metrics that measure the proper match between the grid interaction and the load. The entire process is based on the application of time series clustering as a data-driven technique in order to examine the average PV and load power profiles. In addition, two technique, which are time series clustering and trailing moving average, are used to compare the resulted hourly average PV output powers for the considered different time steps. Finally, the results of the estimated capacity factor and self-consumption/sufficiency metrics of the considered PV system are indicated to significantly affect the optimal size of the utilized PV array by satisfying the desired requirements of the net zero energy buildings and enhancing the performance of the utilized PV system.