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Report

Estimating Preferences for Wind Turbine Locations - A Critical Review of Visualisation Approaches

From

Department of Management Engineering, Technical University of Denmark1

Systems Analysis, Department of Management Engineering, Technical University of Denmark2

Danish Institute for Local and Regional Government Research3

As the amount of wind energy installed capacity keeps growing, in Europe and the world in general, the siting of wind projects near population or recreational centres becomes a frequent possibility. Therefore, it is of high interest for policy makers and developers to be able to quantify the effect of wind projects on public acceptance.

Currently, one of the main drivers for acceptance of wind turbines by the public is their level of visual impacts. While recent studies have focused on estimating the welfare loss of visual impacts from wind turbines, a large share of the applied studies have used no or very simple visualisation of the actual visual impacts at stake.

These studies thus rely on the cognitive skills of the respondents to imagine wind turbines of different sizes and locations; and on the prior experience people have had with wind turbines. By extending the economic model of perceived quality developed by Blomquist and Whitehead (1998), this paper provides a theoretical argument for the need of visualisations when describing valuation scenarios for respondents, as well as the relevance to correctly de ne the amount of attributes of the good to be represented on the visualisation, and which visualisation techniques to utilise.

Afterwards, we propose a framework for classifying different visualisation types and utilise it to classify recent studies regarding wind turbines acceptance, highlighting the lack of visualisations in recent studies, as well as the need to raise the bar on scenario descriptions for wind turbine visual impacts valuation.

Language: English
Publisher: Social Science Research Network (SSRN)
Year: 2016
Series: Usaee Working Paper
Types: Report
DOI: 10.2139/ssrn.2848529
ORCIDs: Hevia Koch, Pablo Alejandro

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