Energy Forecasting in Smart Grid Systems: A Review of the State-of-the-art Techniques. (arXiv:2011.12598v3 [cs.LG] UPDATED)

Energy forecasting has a vital role to play in smart grid (SG) systems
involving various applications such as demand-side management, load shedding,
and optimum dispatch. Managing efficient forecasting while ensuring the least
possible prediction error is one of the main challenges posed in the grid
today, considering the uncertainty and granularity in SG data. This paper
presents a comprehensive and application-oriented review of state-of-the-art
forecasting methods for SG systems along with recent developments in
probabilistic deep learning (PDL) considering different …

art arxiv energy forecasting review smart state systems