AD programs aim at changing the energy use behaviour of the consumers either by reducing their total electricity consumption (Energy efficiency (EE) programs) or by shifting load in time (Demand response (DR) programs).
Various factors (determinants) influence consumer behaviour:
do they know they need to change their behaviour, do they know how to change it, are they motivated to change, and able to change, etc. ? Users always act in both a physical environment (e.g. their home with controllable appliances and the climate in their region) and a social environment (e.g. friends that act sustainable or not, government policy) that strongly influence their behaviour: This conceptual model is depicted in Figure 1.
Figure 1. The conceptual model (residential consumers)
In order to stimulate active end-user participation and the desired behaviour, interventions are designed (e.g. providing feedback on energy consumption via an in-home display) and implemented in a pilot with given characteristics (duration, number of participants, etc.)
The building blocks of the conceptual model proposed in the ADVANCED project are:
- the desired behavioural change of actors who live in,
- physical environments and
- social environments
- upon whom interventions are targeted
- of which the success will be measured by Key Performance Indicators.
By formulating generic concepts within these blocks (derived from both the scientific literature as the practical experience in real-life pilots), numerous context-specific conceptual models can be formulated and tested. Hypotheses are formulated as a causal association (i.e. testable correlations), between at least two concepts (e.g. household size is directly associated with total energy consumption) to provide insight in the mechanisms behind user behaviour and the way interventions for behavioural change can work.
These hypotheses are validated in the project (for each ADVANCED pilot) by using the consumption data gathering within the ADVANCED sites (at household level) to uncover which profiles of household consumers adjust their consumption the most or the least and to what extent . Designers of new AD-pilots or roll-outs can benefit from the lessons learned from these analyses which will identify and make explicit the psycho-social drivers of household behavioural change when it comes to energy consumption (and therefore increasing their chances to successfully change behaviour) and determining which consumption data have to be collected.
For validating the aforementioned hypotheses a set of KPIs is needed to determine the success of the demand response services and identify the best practices for active end-user participation under certain conditions.
Moreover, a large pool of comparable data is required within the ADVANCED knowledge database and it has been organized in the form of a “target matrix” of variables. It was designed in such a manner that data from a wide range of pilots (differing in terms of recruitment strategies, incentives, communication strategies, functionalities and applied technologies, etc.) and consumer segments can be compared in a logical, comparable manner.
The target matrix was designed following both a top-down and a bottom-up approach. As a basis, an operationalization was made on the concepts identified in the conceptual model, turning them into variables (with corresponding units) that can be collected in the ADVANCED sites and the VaasaETT database or through the surveys of the project aimed at additional data gathering (top-down). On top of this operationalized concepts, an extended set of variables that could be collected within the ADVANCED sites or gained from the VaasaETT database was identified for use for a bottom-up explorative analysis.
About 250 variables have been identified and included within the target matrix. They have been grouped into four main categories:
- “Generic variables”; that describe the main features of the pilots under analysis.
- “Pilot variables (subject to data privacy concerns)”.
- “Personal variables (subject to data privacy)” that are directly related to the customer’s behavior, attitude and performance.
- “Other variables”, including all the variables that cannot be collected from any of the ADVANCED information sources (neither from the Advanced sites nor from the VaasaETT database) but that should be taken into consideration in designing other AD initiatives.
As the implementation of the pilots in the ADVANCED sites as well as in the VaasaETT database started before the ADVANCED project, data gathering could not be mutually tuned and the target matrix includes some variables which cannot be collected within the scope of ADVANCED. Other projects however can use this extensive list of variables when designing the data gathering and data analysis for their project.