Where the wind blows: Assessing the effect of fixed and premium based feed-in tariffs on the spatial diversification of wind turbines

Schmidt, Johannes; Lehecka, Georg V.; Gass, V.; Schmid, Erwin

doi:10.1016/j.eneco.2013.07.004

Cited by 67 publications

(27 citation statements)

References 15 publications

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“…Following Schmidt et al (2013), treating ω i,t,h as a random variable, it is possible to express the investor's expected NPV as in figure 6.…”

Section: Fixed Feed-in Tariffmentioning

confidence: 99%

“…This implies that investors choose to maximize output under a fixed FIT, as assumed in Schmidt et al (2013), and Deutsche WindGuard (2014).…”

Section: Fixed Feed-in Tariffmentioning

confidence: 99%

“…Again following Schmidt et al (2013), I take expectations of the NPV. For simplicity, I apply them to equation 9, the NPVs of single turbines, rather than the overall optimization problem in equation 10:…”

Section: Floating Market Premium Schemementioning

confidence: 99%

“…However, they also find that such deviations from the general German wind production do not appear to occur consistently, as "no location is persistently, i.e., in every calendar month of the year, above the average" (p. 1). Schmidt et al (2013) analyze the covariance between the generation at Austrian sites with overall generation, and find that an MPS leads to a different allocation of turbines.…”

Section: Introductionmentioning

confidence: 99%

“…Grothe and Müsgens (2013) assume a standard 1.5 MW wind turbine for all locations, which cannot be altered. Similarly, Schmidt et al (2013) assume a 2 MW turbine across all locations. Yet, different locations require different turbine technologies.…”

Section: Introductionmentioning

confidence: 99%

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The impact of wind power support schemes on technology choices

May

2017

Energy Economics

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractGermany changed renewable remuneration for wind power from a fixed Feed-In Tariff (FIT) to a floating Market Premium Scheme (MPS) in 2012. One aim of this adjustment was to better align the supply of generated wind electricity with the demand for it, e.g. through more system-friendly wind turbine technology choices. In energy systems with a high share of variable renewable energies, such turbines produce a higher share of their production at lower wind speeds and thus can reduce the need for alternative flexibility options like back-up capacity, storage, grid extensions and demand side measures. However, based on a wind power investment model, I show that the MPS fails to convey strong enough incentives to project developers to significantly alter their investment decisions as long as these base their investments on current electricity market price profiles and are limited by their access to risk-averse project finance. One reform proposal to support the installation of system-friendly turbines is a change in the production volume-based benchmark approach which plays an integral part in both the fixed FIT and the MPS. The investment model indicates that such a revised policy can incentivize the deployment of moderately more system-friendly wind power technologies at some locations. An alternative option is to shift to a production value-based benchmark approach. It directly reflects the future additional market value of system-friendly turbines in today's remuneration structure. Thus, this approach sets incentives also for investors without perfect foresight -or with financing constraints -to deploy more systemfriendly turbines that meet the requirements of power systems with increasing shares of wind power.

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“…Following Schmidt et al (2013), treating ω i,t,h as a random variable, it is possible to express the investor's expected NPV as in figure 6.…”

Section: Fixed Feed-in Tariffmentioning

confidence: 99%

“…This implies that investors choose to maximize output under a fixed FIT, as assumed in Schmidt et al (2013), and Deutsche WindGuard (2014).…”

Section: Fixed Feed-in Tariffmentioning

confidence: 99%

Section: Floating Market Premium Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The impact of wind power support schemes on technology choices

May

2017

Energy Economics

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Policies and Modeling of Energy Systems for Reaching European Bioenergy Targets

Leduc

Wetterlund

Dotzauer

et al. 2015

Handbook of Clean Energy Systems

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To mitigate carbon dioxide emissions, the European Union ( EU ) and many countries around the world have set into action different policy tools such as a carbon tax or feed‐in tariffs. Most instruments have, directly or indirectly, an impact on the use of biomass for energy purposes. The principal policy tools relevant to bioenergy production and applied in the EU are described in this article and their observed impact on bioenergy production levels is assessed. In addition, a model application on the policy tools is presented to assess future impact of policies on production of energy carriers from lignocellulosic biomass at the EU level and at the international level. This model application is based on the optimization model BeWhere , which determines the optimal location and technology of a set a bioenergy conversion plants, minimizing the cost of the supply chain. Sweden, Austria, and Finland are the three countries that are highlighted in the EU . An international perspective is also included by presenting a Brazilian case study. From the modeling results, it can be derived that integrated biofuel production would be the most competitive way for biofuel production and that a carbon tax and the emission trading scheme are the most cost‐efficient solutions to decrease emissions.

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