Smart Energy

11 Apr 2019

13:40 — 14:00

Hari Seldon Stage

Data-Driven Prediction of the Evolution of Distributed Energy Resources

The photovoltaic technology (PV) has spread all over the world on private household rooftops and contributes to a regenerative energy system. Here, a data-driven approach for the prediction of spatio-temporal evolution of PV is presented. Based on time series describing the past PV evolution as well as data on socioeconomics and households two neural nets are trained. Their output reveals detailed predictions on future spreading of PV. In contrast to standard Monte Carlo techniques this approach captures spatial correlations due to collective behavior. The resulting clusters are highly relevant in practice, i.e. for adequate planning of the distribution grid.