The competition overview clearly addresses the t+1 problem!
“This challenge focuses on identifying and estimating demand response activity. Participants are to develop a machine learning model that back-cast (from historic time-series data from buildings) to:
- determine when demand response events were activated and for how long,
- determine how much energy was increased or decreased (over the event duration), compared with normal consumption, as a result of activating demand response mode.
Participants will use ground truth time-series data with known observed demand response events (identified in the form of demand response flags) to learn site consumption behaviour both (i) when demand response mode is not active and (ii) when demand response mode is activated.”
Backcasting in machine learning is the process of generating or predicting unknown historical data using present information. How exactly are we supposed to interpret the quoted text???