  We introduce a novel functional time series methodology for short-term load
forecasting. The prediction is performed by means of a weighted average of past
daily load segments, the shape of which is similar to the expected shape of the
load segment to be predicted. The past load segments are identified from the
available history of the observed load segments by means of their closeness to
a so-called reference load segment, the later being selected in a manner that
captures the expected qualitative and quantitative characteristics of the load
segment to be predicted. Weak consistency of the suggested functional similar
shape predictor is established. As an illustration, we apply the suggested
functional time series forecasting methodology to historical daily load data in
Cyprus and compare its performance to that of a recently proposed alternative
functional time series methodology for short-term load forecasting.
