The volume of data becoming available from smart meters is opening up new opportunities via analytics for better understanding and managing energy use through programmes aimed to impact on customer behaviour.
Hourly meter data
As an example, the US State and Local Energy Efficiency Action Network (SEE Action) investigated the potential of such a behaviour-based programme to impact on peak-hour savings. The aim was to find out, based on calculated hourly data, if savings were being made during the peak hours when most valuable, or if they were occurring primarily during off-peak hours.
The data was drawn from PG&E’s pilot home energy report program Wave One, which included 500,000 households in the top-three quartiles of energy use, drawn from most geographic regions in the company’s service territories. Just three months of data were included in the analysis, from August 1– October 31, 2012 (rollout began in February 2012), but includes six of the 10 highest hourly consumption levels of 2012.
Among the findings:
● Statistically significant electricity savings during every hour, on average 0.014kWh per hour per household, or around 2% of total energy consumption
● Higher kWh savings during peak hours, on average more than double the savings during off-peak hours (0.023kWh savings per hour per household for on-peak versus 0.010kWh for off-peak)
● A higher percentage of savings during peak hours, relative to the energy usage in each hour
● Higher peak savings during the 10 highest system peak days, on average more than three times as much as during the 10 lowest days (0.033kWh peak-hour savings per hour per household for the highest days versus 0.012kWh for the lowest)
● Slightly higher proportional peak savings during the ten highest system peak days.
Potential for savings
Taken together, SEE Action concludes: “This implies that behavior-based programmes have the potential to induce electricity savings exactly when they are most needed; the savings are disproportionately high during peak hours on peak days.”
This in turn implies that peak-hour savings could be considered as a potential (non-dispatchable) resource for improving short-run reliability. Further, if the peak-hour energy savings could be maintained and accurately predicted over time, this type of program potentially could be treated as a planning capacity resource.
SEE Action cautions, however, that while showing the feasibility of behaviour-based programmes to provide peak-hour savings, the results may be specific to this particular programme in this specific situation. Without a better understanding of what is driving the savings levels and their differences across different populations and under different circumstances, it is not possible at this time to conclude definitively that all behaviour-based programs will produce peak-hour savings.
What is becoming clear, however, from the work by Opower and other companies, is behaviour-based energy programmes do hold considerable potential for achieving energy savings. [Engerati-Unlocking the Potential of Behavioral Energy Efficiency]