Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/90456
Título: | A regression model to assess the social acceptance of demand response programs |
Autor(es): | Ferreira, Paula Varandas Rocha, Ana Isabel Carneiro Araújo, Maria Madalena Teixeira de |
Palavras-chave: | Demand response Heterogeneous choice model (oglm) Ordered logit regression (ologit) Residential consumers Social acceptance |
Data: | Abr-2021 |
Editora: | Springer |
Revista: | Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (LNICST) |
Resumo(s): | 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. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/90456 |
ISBN: | 978-3-030-73584-5 |
e-ISBN: | 978-3-030-73585-2 |
DOI: | 10.1007/978-3-030-73585-2_6 |
ISSN: | 1867-8211 |
e-ISSN: | 1867-822X |
Versão da editora: | https://link.springer.com/chapter/10.1007/978-3-030-73585-2_6 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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sesc_2020_31_08_20.pdf | 392,04 kB | Adobe PDF | Ver/Abrir |