Research Article
A Regression Model to Assess the Social Acceptance of Demand Response Programs
@INPROCEEDINGS{10.1007/978-3-030-73585-2_6, author={Paula Ferreira and Ana Rocha and Madalena Ara\^{u}jo}, title={A Regression Model to Assess the Social Acceptance of Demand Response Programs}, proceedings={Sustainable Energy for Smart Cities. Second EAI International Conference, SESC 2020, Viana do Castelo, Portugal, December 4, 2020, Proceedings}, proceedings_a={SESC}, year={2021}, month={4}, keywords={Demand response Social acceptance Heterogeneous choice model (oglm) Ordered logit regression (ologit) Residential consumers}, doi={10.1007/978-3-030-73585-2_6} }- Paula Ferreira
Ana Rocha
Madalena Araújo
Year: 2021
A Regression Model to Assess the Social Acceptance of Demand Response Programs
SESC
Springer
DOI: 10.1007/978-3-030-73585-2_6
Abstract
Residential demand response has been playing an important role in the low carbon energy system transition. Although this is not a new concept, the popularity of Demand Response (DR) programs is growing, driven by the increasing opportunities that emerged with smart grid appliances as well as by their potential to support the integration of variable renewables generation. The end-user plays a key role in the successful deployment and dissemination of these DR programs. This study aims to assess social awareness and acceptance of DR programs, based on a survey for data collection and complemented with the regression models. The results suggest that the economic determinants, contribution to environmental protection as well as the extent of urbanization are important motivating drivers, to be explored in the future to encourage the residential consumers’ participation in DR programs.
