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Onshore wind and the likelihood of planning acceptance: learning from a Great Britain context

Onshore wind and the likelihood of planning acceptance: learning from a Great Britain context
Onshore wind and the likelihood of planning acceptance: learning from a Great Britain context
Geospatial modelling is extensively used to identify suitable sites for the installation of onshore wind turbines, with the starting point being the estimate of exploitable resource. However, there are concerns that such approaches do not accurately consider the social issues surrounding such projects, resulting in large numbers of projects subsequently being rejected at the planning permission stage. Using the location of 1721 historic wind turbine planning applications in Great Britain, this paper explores whether the planning success of proposed wind turbine projects can be better predicted using a range of geospatial, social and political parameters. The results indicate that the size of the project, local demographics and the proximity to existing wind turbines are key influences affecting planning approval. The paper demonstrates that quantitatively linking local social and political data enhances the prediction of the planning outcome of wind turbine proposals, and highlights that geospatial parameters are necessary but in isolation, not sufficient for assessing the suitability of potential sites. These results also suggest that national policy is restricting the development of onshore wind energy in regions which appear generally supportive of wind energy.
0301-4215
954-966
Harper, Michael
43fc00d4-9458-4c49-a0bf-21a6f4b3844e
Anderson, Ben
01e98bbd-b402-48b0-b83e-142341a39b2d
James, Patrick A.b.
da0be14a-aa63-46a7-8646-a37f9a02a71b
Bahaj, Abubakr S.
a64074cc-2b6e-43df-adac-a8437e7f1b37
Harper, Michael
43fc00d4-9458-4c49-a0bf-21a6f4b3844e
Anderson, Ben
01e98bbd-b402-48b0-b83e-142341a39b2d
James, Patrick A.b.
da0be14a-aa63-46a7-8646-a37f9a02a71b
Bahaj, Abubakr S.
a64074cc-2b6e-43df-adac-a8437e7f1b37

Harper, Michael, Anderson, Ben, James, Patrick A.b. and Bahaj, Abubakr S. (2019) Onshore wind and the likelihood of planning acceptance: learning from a Great Britain context. Energy Policy, 128, 954-966. (doi:10.1016/j.enpol.2019.01.002).

Record type: Article

Abstract

Geospatial modelling is extensively used to identify suitable sites for the installation of onshore wind turbines, with the starting point being the estimate of exploitable resource. However, there are concerns that such approaches do not accurately consider the social issues surrounding such projects, resulting in large numbers of projects subsequently being rejected at the planning permission stage. Using the location of 1721 historic wind turbine planning applications in Great Britain, this paper explores whether the planning success of proposed wind turbine projects can be better predicted using a range of geospatial, social and political parameters. The results indicate that the size of the project, local demographics and the proximity to existing wind turbines are key influences affecting planning approval. The paper demonstrates that quantitatively linking local social and political data enhances the prediction of the planning outcome of wind turbine proposals, and highlights that geospatial parameters are necessary but in isolation, not sufficient for assessing the suitability of potential sites. These results also suggest that national policy is restricting the development of onshore wind energy in regions which appear generally supportive of wind energy.

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Accepted/In Press date: 2 January 2019
e-pub ahead of print date: 6 March 2019
Published date: May 2019

Identifiers

Local EPrints ID: 428852
URI: http://eprints.soton.ac.uk/id/eprint/428852
ISSN: 0301-4215
PURE UUID: 1059f607-e4bb-44fe-95fc-d2a627290724
ORCID for Ben Anderson: ORCID iD orcid.org/0000-0003-2092-4406
ORCID for Patrick A.b. James: ORCID iD orcid.org/0000-0002-2694-7054
ORCID for Abubakr S. Bahaj: ORCID iD orcid.org/0000-0002-0043-6045

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Date deposited: 13 Mar 2019 17:30
Last modified: 16 Mar 2024 02:45

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Contributors

Author: Michael Harper
Author: Ben Anderson ORCID iD

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