Robust 24 Hours ahead Forecast in a Microgrid: A Real Case Study

Alfredo Nespoli, Marco Mussetta, Emanuele Ogliari, Sonia Leva, Luis Fernández-Ramírez, Pablo García-Triviño
2019 Electronics  
Forecasting the power production from renewable energy sources (RESs) has become fundamental in microgrid applications to optimize scheduling and dispatching of the available assets. In this article, a methodology to provide the 24 h ahead Photovoltaic (PV) power forecast based on a Physical Hybrid Artificial Neural Network (PHANN) for microgrids is presented. The goal of this paper is to provide a robust methodology to forecast 24 h in advance the PV power production in a microgrid, addressing
more » ... crogrid, addressing the specific criticalities of this environment. The proposed approach has to validate measured data properly, through an effective algorithm and further refine the power forecast when newer data are available. The procedure is fully implemented in a facility of the Multi-Good Microgrid Laboratory (MG L a b 2 ) of the Politecnico di Milano, Milan, Italy, where new Energy Management Systems (EMSs) are studied. Reported results validate the proposed approach as a robust and accurate procedure for microgrid applications.
doi:10.3390/electronics8121434 fatcat:p7wyca2lqbautdrvrxjpwf4kke