i-EM at The Smarter E Europe restart with two digital events
We are very proud to announce that our Technical Sales Engineer Lorenzo Gigoni along with our Chief Technical Officer Ciro Lanzetta will be speakers in two webinars at THE SMARTER E INDUSTRY DAYS, the Digital Event on July 21-23, 2021. Two i-EM digital events to get...
Decentralized systems for e-Vehicles charging: the future of smart cities
A decentralized algorithm to help drivers find the best charging station
e-Vehicles home-charging: an algorithm to protect power systems
Home charging stations and power system stability
NREL Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications
AUTHORS:
Lorenzo Gigoni, Alessandro Betti, Emanuele Crisostomi, Alessandro Franco, Mauro Tucci, Fabrizio Bizzarri and Debora Mucci.
ABSTRACT:
The ability to accurately forecast power generation from renewable sources is nowadays recognized 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 (PV) plants of different sizes 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.
