Peak demand is an issue in power supply system when demand exceeds the available capacity. Continuous growth in peak demand increases the risk of power failures, and increases the marginal cost of supply. The contribution of the residential sector to the system peak is quite substantial and has been a subject of discussion internationally. For example, a study done in New Zealand in 2007 attributed about half of system peak load to the residential sector. International research has attributed a significant influence of human behaviour on households energy use. “Demand Response” is a demand side management tool aimed at achieving peak energy demand reduction by eliciting behaviour change. It encompasses energy needs analysis, information provision to customers, behaviour induction, smart metering, and new signalling and feedback concepts. Demand response is far advanced in the industrial and commercial demand sectors. In the residential sector, information barriers and a lack of proper understanding of consumers’ behaviour have impeded the development of effective response strategies and new enabling technologies in the sector. To date, efforts to understanding residential sector behaviour for the purpose of peak demand analysis has been based on pricing mechanism. However, not much is known about the significance of other factors in influencing household customers’ peak electricity demand behaviour. There is a tremendous amount of data that can be analyzed and fed back to the user to influence behaviour. These may include information about energy shortages, supply security and environmental concerns during the peak hours.

This research is intended to begin the process of understanding the importance of some of these factors in the arena of peak energy consumption behaviour.

Using stated preference survey and focus group discussions, information about household customers’ energy use activities during winter morning and evening peak hours was collected. Data about how customers would modify their usage behaviour when they receive enhanced supply constraint information was also collected. The thesis further explores households’ customer demand response motivation with respect to three factors: cost (price), environment (CO2-intensity) and security (risk of black-outs). Householders were first informed about the relationship between these factors and peak demand. Their responses were analyzed as multi-mode motivation to energy use behaviour change.

Overall, the findings suggest that, household customers would be willing to reduce their peak electricity demand when they are given clear and enhanced information. In terms of motivation to reduce demand the results show customers response to the security factor to be on par with the price factor. The Environmental factor also produced a strong response; nearly two-thirds of that of price or security.

A generic modelling methodology was developed to estimate the impact of households’ activity demand response on the load curve of the utility using a combination of published literature reviews and resources, and own research work. This modelling methodology was applied in a case study in Halswell, a small neighbourhood in Christchurch, New Zealand, with approximately 400 households. The results show that a program to develop the necessary technology and provide credible information and understandable signals about risks and consequences of peak demand could provide up to about 13% voluntary demand reduction during the morning peak hours and 8% during the evening peak hours.