Spatial economic potential of post feed-in tariff wind turbines in Germany
Authors: Dede Christine , Eising Manuel 
Published: March 2021

&lt;p&gt;&lt;strong&gt;Keywords:&lt;/strong&gt; direct marketing, post-FiT, wind, spatial analysis&lt;/p&gt;&lt;p&gt;Within the coming ten years, more than 25 GW of onshore wind will reach the end of 20 year feed-in tariff (FiT) scheme according to the German Renewable Energy Law (EEG). This urges operators to take decision on repowering, lifetime extension or shutdown. In order to support the operators&amp;#8217; decision this study discusses and analyses the economic potential of lifetime extension or shutdown. Due to the limited lifetime extension of post-FiT turbines, rather short-term alternative revenue schemes on the day-ahead market, either via direct marketing or via a merchant PPA, appear as a reasonable option.&lt;/p&gt;&lt;p&gt;For these post-FiT business models, the methodology at hand introduces a revenue and cost cascade. The value and cost categories derive from a power system perspective cascade introduced by Hirth et al. (2015) complemented by transaction costs and additional revenue streams, e.g. from Guaranties of Origin (GoO).&lt;/p&gt;&lt;p&gt;The applied spatial economic analysis calculates region-specific contribution margins for post-FiT wind turbines in Germany in two steps:&lt;/p&gt;&lt;ul&gt;&lt;li&gt;Calculation of regionally dispersed value factors [%], market values [&amp;#8364;/MWh&lt;sub&gt;el&lt;/sub&gt;] and annual market revenues [&amp;#8364;/MW] using hourly day-ahead price time series and hourly wind feed-in time series for German NUTS2 regions.&lt;/li&gt;
&lt;li&gt;Identifying the distribution of wind turbine operational expenditures (OPEX) from the literature and analysing their regional-specific magnitude. Capital expenditures from the initial wind turbine investment or grid connection are considered as sunk costs and can be neglected.&lt;/li&gt;
&lt;/ul&gt;&lt;p&gt;Subtracting spatial OPEX from spatial market values reveals region-specific contribution margins and the economic potential for continuing wind turbine operation. The conclusion is threefold:&lt;/p&gt;&lt;ul&gt;&lt;li&gt;Location-specific market values strongly affect the contribution margin: year-to-year evolution of day-ahead price levels translates into high volatility of contribution margin. Capacity-dense regions show lower empirical market values. This trend of regional disparities will increase (Eising et al., 2020) due to increasing cannibalisation effect at ever-increasing wind market shares.&lt;/li&gt;
&lt;li&gt;Variation in OPEX assumptions influence the locational contribution margins: the literature review on wind turbine OPEX levels reveals a wide assumption range between 21,4 &amp;#8211; 46 &amp;#8364;/MWh&lt;sub&gt;el&lt;/sub&gt; and a data gap on actual OPEX for post-FiT wind turbines. In addition, the level distribution of cost causation in energy driven [&amp;#8364;/MWh&lt;sub&gt;el&lt;/sub&gt;] and capacity driven [&amp;#8364;/MW] OPEX together with the regional variation in wind speeds leads to a significant regional OPEX sensitivity.&lt;/li&gt;
&lt;li&gt;In general, wind-intense sites nowadays deliver higher contribution margins. This overperformance arises from higher absolute market revenues [&amp;#8364;/MW] and relatively lower OPEX [&amp;#8364;/MWh&lt;sub&gt;el&lt;/sub&gt;]. However, relatively lower market values already appear in the observed timeframe 2006 - 2016 at capacity-dense regions in central-northern Germany.&lt;/li&gt;
&lt;/ul&gt;&lt;p&gt;Overall, this study highlights the importance of acknowledging the spatial distribution of market values for analysis of business models, in particular for post-FiT wind turbines, instead of power system analysis as in the vast majority of market value studies.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;Eising, Hobbie, M&amp;#246;st, 2020. Future wind and solar power market values in Germany &amp;#8212; Evidence of spatial and technological dependencies? Energy Econ. 86. https://doi.org/10.1016/j.eneco.2019.104638&lt;/p&gt;&lt;p&gt;Hirth, Ueckerdt, Edenhofer, 2015. Integration costs revisited &amp;#8211; An economic framework for wind and solar variability. Renew. Energy 74. https://doi.org/10.1016/j.renene.2014.08.065&lt;/p&gt;