  Electric generation and consumption are an essential component of
contemporary living, influencing diverse facets of our daily routines,
convenience, and economic progress. There is a high demand for characterizing
the periodic pattern of electricity consumption. VBPBB employs a bandpass
filter aligned to retain the frequency of a PC component and eliminating
interference from other components. This leads to a significant reduction in
the size of bootstrapped confidence intervals. Furthermore, other PC bootstrap
methods preserve one but not multiple periodically correlated components,
resulting in superior performance compared to other methods by providing a more
precise estimation of the sampling distribution for the desired
characteristics. The study of the periodic means of Turkey electricity
consumption using VBPBB is presented and compared with outcomes from
alternative bootstrapping approaches. These findings offer significant evidence
supporting the existence of daily, weekly, and annual PC patterns, along with
information on their timing and confidence intervals for their effects. This
information is valuable for enhancing predictions and preparations for future
responses to electricity consumption.
