  This paper provides a description of the approach and methodology I used in
winning the European Union Big Data Technologies Horizon Prize on data-driven
prediction of electricity grid traffic. The methodology relies on identifying
typical short-term recurrent fluctuations, which is subsequently refined
through a regression-of-fluctuations approach. The key points and strategic
considerations that led to selecting or discarding different methodological
aspects are also discussed. The criteria include adaptability to changing
conditions, reliability with outliers and missing data, robustness to noise,
and efficiency in implementation.
