The main categories of KPIs, taking into account the perspectives of the key AD stakeholders, are the following:
- improving energy sustainability,
- reducing system costs,
- maintaining electricity Distribution network reliability,
- improving affordability,
- improving customer relationship.
Within the aforementioned categories, the following KPIs have been identified measuring benefits at the grid level:
The following KPIs have been identified measuring benefits at the household level:
- Reduction in CO2 emissions;
- Increased customer awareness;
- Increased proportion of consumed electricity produced from intermittent generation;
- Net reduction in power bills;
- Compensation for load flexibility;
- Participant’s satisfaction with AD programs;
- Improved participant’s satisfaction with the energy industry;
- Increased demand flexibility (peak clipping and valley filling);
- Reduction in overall electricity consumption.
The “Increased demand flexibility” and “Change in overall electricity consumption” KPIs are extremely common for AD pilots but the success is always measured for an aggregated pilot or at group level. ADVANCED is unique in defining, measuring and evaluating these KPIs at household level. A methodology to quantify these KPIs in a univocal manner has been developed. KPIs were chosen for validating the hypotheses of the ADVANCED conceptual model for active consumer participation, including all relevant factors influencing the participation of consumers and their interactions in AD programmes. KPIs are of paramount importance as they are the measurements for the actual changes in consumption of the households.
As the “Increased demand flexibility” KPI does not measure behavioural change due to Demand response (DR) signals, an additional KPI: “Signal Compliance: difference in consumption pattern” has been defined. The KPI is calculated by comparing the consumption trend of each consumer after the DR signal comes into force with its habitual one. It is a unique ADVANCED KPI and it can only be calculated using data at household level.