Detalhes
Nome
Kamalanathan GanesanCluster
EnergiaDesde
17 julho 2017
Nacionalidade
ÍndiaCentro
Centro de Sistemas de EnergiaContactos
+351222094230
kamalanathan.ganesan@inesctec.pt
2019
Autores
Ganesan, K; Saraiva, JT; Bessa, RJ;
Publicação
2019 IEEE Milan PowerTech, PowerTech 2019
Abstract
Engaging the residential consumers and providing the best tariffs for their randomized behavior is one of the major barriers to demand response (DR) implementation. Additionally, DR offers submitted by aggregators or retailers are not consumer-specific, which turns it even more difficult for the engagement of consumers in these programs. In order to address this issue, this paper describes a methodology based on causal inference between dynamic DR tariffs and observed residential electricity consumption (resolution of 30 minutes) to estimate consumers' consumption elasticity. Ultimately, the aim of this approach is to aid aggregators and retailers to better tune DR offers to consumer needs and so to enlarge the response rate to their DR programs. © 2019 IEEE.
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