Analysis of household electricity consumption behaviours: Impact of domestic electricity generation

Adoption of renewable electricity generation technologies such as photovoltaic (PV) systems is at the early majority stage in most developed countries. Depending on solar capacity, applied feed-in tariff, and other factors, households exhibit different electricity consumption behaviours which can potentially assist in Demand Side Management (DSM) of electricity usage. This article presents three univariate analysis methods to infer deliberative behavioural patterns at households with solar electricity generation capacity. Analysis methods include qualitative Principal Component Analysis (PCA), unsupervised Hebbian-based clustering, and clustering using a semi-supervised Self-Organising Map (SOM). The techniques are individually applied to 300 sample households with rooftop PV panels operating under a Gross Metering (GM) scheme. According to the PCA, the dominant behaviours are often general among most households, and therefore reveal themselves on first and second principal components. However, on the third and fourth components some specific household behaviours related to load-shifting and self-consumption, are observed. The Hebbian model differentiates between at least eight behaviour types, some of which indicate deliberative behaviours by the households. Most effectively, SOM clustering clearly detects a self-consumption behaviour attributed to domestic electricity generation. A control group of 400 households is analysed to ensure uniqueness of the self-consumption behaviour to customers with solar PV installed. The techniques developed herein may be able to be used by electricity utilities to assess the influence that future tariff and technology offerings will have on behavioural aspects of customer electricity consumption.