The ongoing world-wide increase of installed photovoltaic (PV) power attracts notice to
weather-induced PV power output variability. Understanding the underlying spatiotemporal …

As the share of renewable energy sources in the energy mix is increasing, new challenges
arise regarding the grid integration. This research focuses on a solution for one of these …

In this study, we analyzed annual production data from 100 000 photovoltaic systems as well
as comments relating to their performance and maintenance. Our analysis revealed that …

This monograph summarizes and analyzes recent research by the authors and others to
understand, characterize, and model solar resource variability. This research shows that …

Using many years of high-quality measurements from a variety of radiometers at both 1-min
and 1-s resolution, this study provides a detailed analysis of cloud enhancement (CE) and …

We develop a hybrid, real-time solar forecasting computational model to construct prediction
intervals (PIs) of one-minute averaged direct normal irradiance for four intra-hour forecasting …

A k-nearest neighbor (kNN) ensemble model has been developed to generate Probability
Density Function (PDF) forecasts for intra-hour Direct Normal Irradiance (DNI). This …

The cloud enhancement (CE) of solar irradiance is a well-known phenomenon, but its effects
on PV power plants are not thoroughly understood. Because of scalability, the diameters of …

In contrast to the decades-long accumulated experience of photovoltaic (PV) installations in
more temperate climates, the effects of some extreme operating temperatures and extreme …

Characterizing short-term variability of generated solar power is important for the integration
of photovoltaic (PV) systems into the electrical grid. Using different kinds of high frequency …