TY - GEN A1 - Engelhorn, Thorsten A1 - Müsgens, Felix T1 - How to estimate wind-turbine infeed with incomplete stock data: A general framework with an application to turbine-specific market values in Germany T2 - Energy Economics N2 - This paper analyses market values of wind energy converters at the individual turbine level on a very large scale. Such an analysis is usually precluded by the lack of detailed public data on the stock of wind turbines. We therefore present a general method to estimate incomplete turbine stock data and generate hourly yields of individual turbines based on completed turbine stock data and highly disaggregated hourly wind speed data. On this basis, we calculate hourly infeed and annual market values of up to 25,700 wind turbines in Germany from 2005 to 2015. We show the spread in market values on turbine level, quantify regional differences and discuss the effect of turbine age on market values. We show that turbines in central Germany have, on average, lower market values than turbines in the north, south or far west of Germany. Furthermore, we show that modern turbines reach higher market values than older turbines. We also analyse the drivers of market values, differentiating between infeed-price correlation and standard deviation. KW - renewable energy sources KW - wind energy KW - bottom-up modeling KW - cost minimization KW - market value KW - power curves Y1 - 2018 UR - https://doi.org/10.1016/j.eneco.2018.04.022 UR - https://www-docs.b-tu.de/fg-energiewirtschaft/public/Veroeffentlichungen/WP_Engelhorn_Muesgens_2017.pdf UR - https://www.youtube.com/watch?v=tX4x3kUQBlk&t=15s SN - 0140-9883 VL - 72 SP - 542 EP - 557 ER - TY - GEN A1 - Engelhorn, Thorsten A1 - Müsgens, Felix T1 - Why is Germany’s energy transition so expensive? Quantifying costs from wind energy decentralisation T2 - Resource and Energy Economics N2 - This paper discusses the efficiency of promotion schemes for renewable energy sources using the example of onshore wind energy in Germany. We analyse whether the scheme incentivised a cost-minimal capacity build-up by developing a model to derive two cost-minimal benchmark scenarios, which are then compared to the historical capacity build-up between 1995 and 2015. The costs of the two cost-minimising benchmark scenarios are significantly lower than those of the historical build-up. The benchmark cost reduction largely stems from greater efficiency—fewer turbines are being constructed overall but they are being placed at better wind sites so the annual production of wind energy remains unchanged. Hence, aggregated turbine land use is also significantly down in these scenarios. Furthermore, we compare costs for consumers, as protecting consumers from price discrimination of producers is sometimes used to justify higher payments for low-wind sites. However, our results show that the efficiency gain from building at high wind sites outweighs the distributional effect, even from a consumer’s perspective. KW - Energy markets and pricing Y1 - 2021 UR - https://www.sciencedirect.com/science/article/pii/S0928765521000269 U6 - https://doi.org/10.1016/j.reseneeco.2021.101241 SN - 1873-0221 VL - 65 ER - TY - GEN A1 - Engelhorn, Thorsten A1 - Möbius, Thomas T1 - On the Development of Wind Market Values and the Influence of Technology and Weather: a German Case Study T2 - Zeitschrift für Energiewirtschaft N2 - Research into renewable energy market values is a popular field in energy economics. However, most contributions abstract from market values being highly individual and mostly study (nationwide) averages, usually based on a single or a “normal” wind year, if specifying wind conditions at all, and a limited set of technologies. However, market values of renewable energy resources are not monolithic but highly diverse. In this article, to shed light on this diversity, we illustrate the historical development of onshore wind’s market value in Germany, from 2001 to 2019, for the fleet and all operating wind energy converters. We use highly granular wind speed data and a comprehensive database of wind capacities. Our results show the downward trend, the distributions, and the variance of market values. In this context, we explain why the performance of a single wind energy converter (compared to the fleet’s performance) matters in the market premium model. Hereby, we also assess the magnitude of the outperformance of technologically advanced wind turbines as compared to less advanced turbines. In the second part of our research, we analyse the effect of the inter-annual weather variability on wholesale electricity prices, and market values. Our analysis is based on 19 different years of wind speeds, corresponding offshore and solar infeed, and an electricity market model to generate weather-congruent wholesale electricity prices. KW - Energy markets and pricing Y1 - 2022 UR - https://link.springer.com/article/10.1007/s12398-022-00319-2 U6 - https://doi.org/10.1007/s12398-022-00319-2 SN - 1866-2765 VL - 46 IS - 1 SP - 61 EP - 83 ER - TY - RPRT A1 - Engelhorn, Thorsten A1 - Müsgens, Felix T1 - Why is Germany’s energy transition so expensive? Quantifying costs from wind energy decentralisation KW - costs from wind energy KW - germany’s energy transition KW - wind power KW - energy policy KW - support scheme KW - market design KW - cost minimisation KW - efficiency Y1 - 2019 UR - https://www.b-tu.de/fg-energiewirtschaft/publikationen/publikationsliste PB - Brandenburgische Technische Universität CY - Cottbus ; Senftenberg ER -