One-day prediction of electricity load reflecting future Ripple Control System schedules

In a West-Bohemian power distribution company, a ripple control system (RCS) is used as a key tool for controlling peaks of electricity load. The RCS enables the dispatcher to switch off some groups of consumers for short periods of time, or to move their loading period in order to flatten the load diagram. Since the RCS connected consumers form about 20% of the whole load, shifts in the schedule have to be reflected in load predictions. Therefore, the load of RCS-connected consumers has been modelled and isolated from the baseload. Several similar categories of the consumers have been considered in the West Bohemian area, particularly direct heating, storage heating and boilers. Each category has been characterized by a few constants and parameters, namely installed load (a known parameter), the slope of charging and uncharging, and a daily profile of group’s load. Thus, a piecewise linear model with jumps was obtained for the RCS part of the load. The baseload was modelled by means of regression on a suitable class of functions. The parameters have been estimated and utilized for a one-day-ahead prediction. This prediction reflects the scheduled times of RCS impulses, and enables dispatchers to influence the predicted diagram by changing this schedule.