Day-Ahead Hourly Forecasting of Power Generation from Photovoltaic Plants
This addresses the need for improved power system operation through better renewable energy forecasting, but it is incremental as it focuses on comparison and evaluation rather than introducing a new method.
The paper tackled the problem of accurately forecasting day-ahead hourly power generation from photovoltaic plants by comparing simple and sophisticated methodologies across 32 plants over a year, and evaluated the impact of weather conditions and forecasts, but did not report specific numerical results.
The ability to accurately forecast power generation from renewable sources is nowadays recognised as a fundamental skill to improve the operation of power systems. Despite the general interest of the power community in this topic, it is not always simple to compare different forecasting methodologies, and infer the impact of single components in providing accurate predictions. In this paper we extensively compare simple forecasting methodologies with more sophisticated ones over 32 photovoltaic plants of different size and technology over a whole year. Also, we try to evaluate the impact of weather conditions and weather forecasts on the prediction of PV power generation.