Energy Feedback and Demand Response Strategies : Exploring Household Engagement and Response Using a Mixed Methods Approach

Real-time energy feedback (EF) and demand response using dynamic pricing tariffs (DR) have been suggested as effective intervention strategies to meet the need for increased energy efficiency and demand flexibility in the residential sector. Although previous studies provide some empirical support for the effectiveness of EF and DR, evaluation approaches used in practical experiments and field trials commonly suffer from several methodological shortcomings, preventing deeper of knowledge on the potential and barriers for EF and DR to influence household energy consumption. This thesis explored the potential of employing a mixed methods approach for evaluation of household energy consumption to provide improved understanding on how and why households engage and respond to EF and DR strategies. Three research objectives were set: 1) Analysis of the potential for using high-resolution data from smart meters in evaluation of household energy consumption and response to DR strategies, 2) development of a conceptual framework for evaluation of household responses to EF and DR strategies and analysis of its potential to increase understanding of household responsiveness, and 3) identification and analysis of household motivations, perceptions, and obstacles to engaging in EF and DR strategies. The work to achieve these objectives followed a mixed methods research methodology grounded on literature reviews and empirical studies in real-life settings in a single case study, an EF/DR field trial taking place in Stockholm Royal Seaport. A combination of quantitative and qualitative methods was used for data collection and analysis, comprising interviews, surveys, and statistical analysis of smart meter energy data. The results suggest that the mixed methods approach addresses several of the limitations and challenges associated with previous evaluation approaches. As regards objective (1), it was found that high-resolution data from smart energy meters can provide evaluation outcomes with increased transparency and accuracy. Regarding objective (2), it was found that the proposed framework can increase understanding of variations in household responsiveness to EF and DR strategies and reveal the relationship between impacts on electricity use and factors influencing energy consumption behavior. As regards objective (3), several obstacles for households to engaging in EF and DR strategies were identified, primarily related to household-individual factors such as knowledge, sense of control, and personal values and attitudes. Based on these findings, key issues and areas for further research are proposed.QC 20181120