Reply to ‘The perils of automated fitting of datasets: the case of a wind turbine cost model’

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Abstract

Assessing the investment costs of wind power plants with different technological
parameters is a challenging task. Previously, a cost model to predict specific investment costs using chosen technology parameters was created by fitting a function to cost data. The model, however, shows incorrect scaling behaviour with large installed capacity. A new model was tested with the original data, but it is difficult to estimate its quality without an extensive analysis.
Original languageEnglish
JournalNature Energy
Publication statusSubmitted - 13 Aug 2019
MoE publication typeA1 Journal article-refereed

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Wind turbines
Costs
Wind power
Power plants

Cite this

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title = "Reply to ‘The perils of automated fitting of datasets: the case of a wind turbine cost model’",
abstract = "Assessing the investment costs of wind power plants with different technologicalparameters is a challenging task. Previously, a cost model to predict specific investment costs using chosen technology parameters was created by fitting a function to cost data. The model, however, shows incorrect scaling behaviour with large installed capacity. A new model was tested with the original data, but it is difficult to estimate its quality without an extensive analysis.",
author = "Erkka Rinne",
year = "2019",
month = "8",
day = "13",
language = "English",
journal = "Nature Energy",
issn = "2058-7546",
publisher = "Nature Publishing Group",

}

Reply to ‘The perils of automated fitting of datasets: the case of a wind turbine cost model’. / Rinne, Erkka.

In: Nature Energy, 13.08.2019.

Research output: Contribution to journalArticleScientificpeer-review

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PY - 2019/8/13

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AB - Assessing the investment costs of wind power plants with different technologicalparameters is a challenging task. Previously, a cost model to predict specific investment costs using chosen technology parameters was created by fitting a function to cost data. The model, however, shows incorrect scaling behaviour with large installed capacity. A new model was tested with the original data, but it is difficult to estimate its quality without an extensive analysis.

M3 - Article

JO - Nature Energy

JF - Nature Energy

SN - 2058-7546

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