Template-Type: ReDIF-Article 1.0
Author-Name:  James McCulloch and Katja Ignatieva
Title:  Intra-day Electricity Demand and Temperature
Classification-JEL: F0
Pages:  161-182
Volume:  Volume 41
Issue:  Number 3
Year:  2020
Abstract:  The objective of this paper is to explain the relationship between high frequency electricity demand, intra-day temperature variation and time. Using the Generalised Additive Model (GAM) framework we link high frequency (5-minute) aggregate electricity demand in Australia to the time of the day, time of the year and intra-day temperature. We document a strong relationship between high frequency electricity demand and intra-day temperature. We show a superior model fit when using Daylight Saving Time (DST), or clock time, instead of the standard (solar) time. We introduce the time weighted temperature model that captures instantaneous electricity demand sensitivity to temperature as a function of the human daily activity cycle, by assigning different temperature signal weighting based on the DST time. The results on DST and time weighted temperature modelling are novel in the literature and are important innovations in high frequency electricity demand forecasting.
Handle: RePEc:aen:journl:ej41-3-Ignatieva
File-URL: http://www.iaee.org/en/publications/ejarticle.aspx?id=3506
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