1. Introduction
Electricity load forecasting is one of the main challenges in smart meter technology. Accurate load forecasting at various temporal granularity can help utilities design flexible energy supply strategies (e.g., by applying load switch schemes [1]) to meet the supply-demand balance, and directly benefit individual households by offering a transparent view on energy consumption, thus enabling learning mechanisms to compare and eventually reduce energy waste [2], [3], [4], [5], [6].