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Modelling perception and attitudes towards renewable energy technologies

Fernando Ribeiro, Paula Ferreira, Madalena Araújo and Ana Cristina Braga

Renewable Energy, 2018, vol. 122, issue C, 688-697

Abstract: While renewable energy technologies (RET) increase their share in power generation systems worldwide, some questions remain open, namely those concerning the opinion of the populations on new projects of these technologies. Given the long period of planning and large capital sums required by RET and, in some cases, the fact of being subsidized, it is desirable for decision-makers to acknowledge the public opinion and at least perceive if the opinions are rooted on biased perceptions. In this paper we propose a methodology for public perception and awareness assessment, involving an initial phase of data collection by means of a survey, followed by a phase of regression models construction resulting in predictive models of expected perceptions and attitudes towards RET. The models were translated in a free and easy to use computational Excel application and its usefulness was demonstrated for the case of four electricity RET in Portugal: hydro, wind, biomass and solar.

Keywords: Renewable energy technologies; Public opinion; Ordered logistic regression; Binary logistic regression; Excel simulation tool (search for similar items in EconPapers)
Date: 2018
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