Weather Data Mixing Models for Day-Ahead PV Forecasting in Small-Scale PV Plants

As a large number of small-scale PV plants have been deployed in distribution systems, generation forecasting such has recently gaining interest. Because the power mainly depends on weather conditions, it is important to accurately collect data for relevant sites enhance accuracy. However, do not often their own measuring apparatus get historical data, so they used datasets from relatively nearby centers (WDCs). Therefore, these difficulty delivering robust and reliable accuracy because inappropriate predicted distance. In this paper, two mixing models are proposed: (a) inverse distance weighting (IDW), (b) correlation (ICW). These acquire adequate mixed day-ahead plants. Furthermore, collected using geographic between site WDCs, or variables WDCs. Interestingly, proposed ICW model outperforms when WDCs located distant plants, whereas IDW performs well with closer The performance was compared those existing collection methods.