Predicting peak-demand days in the ontario peak reduction program for large consumers

In this paper, we propose a heuristic algorithm for day-ahead prediction of the top $K$ days having the highest peak hourly demand for electricity over a given year. This problem, which arises in the context of critical peak pricing in Ontario, Canada, is difficult because we may have to wait till the end of the year to find out which $K$ days ended up being the peak days. Our solution is to leverage short-term load forecasts and call tomorrow a peak day if it has sufficiently high probability of being a peak day in the time window covered by the forecast. Using Ontario demand data from 2007 till 2013, we show that our algorithm may need to call about 2K peak days to ensure that most if not all of the actual $K$ peak days are included.