@misc{EngelhornMuesgens, author = {Engelhorn, Thorsten and M{\"u}sgens, Felix}, title = {Why is Germany's energy transition so expensive? Quantifying costs from wind energy decentralisation}, series = {Resource and Energy Economics}, volume = {65}, journal = {Resource and Energy Economics}, issn = {1873-0221}, doi = {10.1016/j.reseneeco.2021.101241}, pages = {18}, abstract = {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.}, language = {en} } @misc{AntweilerMuesgens, author = {Antweiler, Werner and M{\"u}sgens, Felix}, title = {On the long-term merit order effect of renewable energies}, series = {Energy Economics}, volume = {99}, journal = {Energy Economics}, issn = {0140-9883}, doi = {10.1016/j.eneco.2021.105275}, pages = {19}, abstract = {The merit order effect describes the lowering of the average wholesale electricity price due to increased capacity of renewable energies. This effect has been observed in many places. While it is beneficial for consumers, it has triggered concerns about the economic viability of legacy plants. Is this merit order effect a permanent feature of high shares of renewable energy, or merely a transitory phase? This article develops a simple theoretical model to shed light on this question. It introduces intermittent renewable energies into a conventional mix of base load and peak load and investigates the effect when base and peak load remain unchanged in the short-term, and when they fully adjust in the long-term. We find that the merit order effect is a temporary phenomenon that is caused by the slow pace of capacity adjustments. We also find that the introduction of renewables has a mild beneficial long-term effect when base load is provided monopolistically, as renewables compete with base load to a limited extent. Consequently, concerns about the adverse consequences for conventional power plants resulting from renewable capacity are only partially justified. While in the short-term the generation portfolio suffers from "stranded assets", market forces will gradually reduce overcapacity. We also confirm that renewable expansion can be complemented by energy-only markets to incentivize efficient investment in conventional capacity.}, language = {en} } @misc{RiepinMuesgens, author = {Riepin, Iegor and M{\"u}sgens, Felix}, title = {Seasonal flexibility in the European natural gas market}, series = {The Energy Journal}, volume = {43}, journal = {The Energy Journal}, number = {1}, issn = {1944-9089}, doi = {10.5547/01956574.43.1.irie}, pages = {117 -- 138}, abstract = {This paper focuses on seasonal demand swings in the European natural gas market. We quantify and compare the role of different flexibility options (domestic production, gas storage, and pipeline and LNG imports) to assess European demand fluctuations in monthly resolution. We contribute to the existing literature on seasonal flexibility by addressing the problem with a mathematical gas market optimization model. Our paper provides valuable empirical insights into the decline of gas production in northwestern Europe. Furthermore, we focus on how specific flexibility features differ between pipeline supplies and LNG supplies and between gas imports and storage dispatch. In terms of methodology, we construct a bottom-up market optimization model and publish the complete source code (which is uncommon for gas market models). Furthermore, we propose a new metric—the scaled coefficient of variation—to quantify the importance of supply sources for seasonal flexibility provision.}, language = {en} } @misc{NikodinoskaKaesoMuesgens, author = {Nikodinoska, Dragana and K{\"a}so, Mathias and M{\"u}sgens, Felix}, title = {Solar and wind power generation forecasts using elastic net in time-varying forecast combinations}, series = {Applied Energy}, volume = {306, Part A}, journal = {Applied Energy}, issn = {1872-9118}, doi = {10.1016/j.apenergy.2021.117983}, pages = {17}, abstract = {Precise renewable energy feed-in forecasts are essential for an effective and efficient integration of renewables into energy systems, and research contributions that help to reduce the uncertainty related to renewables are in high demand. This importance will increase in the future, as renewable energies are the world's fastest growing electricity generation capacities. Forecast combinations have been empirically proven to outperform individual forecasting models in many disciplines. Our work uses an elastic net method, with cross-validation and rolling window estimation, in the context of renewable energy forecasts. Namely, the forecast combinations are obtained using regional data from Germany for both solar photovoltaic and wind feed-in during the period 2010-2018, with quarter-hourly frequency. The dynamic elastic net estimation, preceded by dynamic data pre-processing, improves forecasting accuracy for both photovoltaic and wind power feed-in forecasts. Moreover, our forecasting framework outperforms benchmarks such as simple average and individual forecasts. Our forecasting framework can be applied widely to estimate renewable power in other countries, systems, or individual power plants.}, language = {en} } @misc{JansenBeiterRiepinetal., author = {Jansen, Malte and Beiter, Philipp and Riepin, Iegor and M{\"u}sgens, Felix and Guajardo-Fajardo, Victor Juarez and Staffell, Iain and Bulder, Bernard and Kitzing, Lena}, title = {Policy choices and outcomes for the competitive procurement of offshore wind energy globally}, series = {Energy Policy}, volume = {167}, journal = {Energy Policy}, issn = {0301-4215}, doi = {10.1016/j.enpol.2022.113000}, abstract = {Offshore wind energy is rapidly expanding, facilitated largely through auctions run by governments. We provide a detailed quantified overview of utilised auction schemes, including geographical spread, volumes, results, and design specifications. Our comprehensive global dataset reveals heterogeneous designs. Although most auction designs provide some form of revenue stabilisation, their specific instrument choices vary and include feed-in tariffs, one-sided and two-sided contracts for difference, mandated power purchase agreements, and mandated renewable energy certificates. We review the schemes used in all eight major offshore wind jurisdictions across Europe, Asia, and North America and evaluate bids in their jurisdictional context. We analyse cost competitiveness, likelihood of timely construction, occurrence of strategic bidding, and identify jurisdictional aspects that might have influenced auction results. We find that auctions are embedded within their respective regulatory and market design context, and are remarkably diverse, though with regional similarities. Auctions in each jurisdiction have evolved and tend to become more exposed to market price risks over time. Less mature markets are more prone to make use of lower-risk designs. Still, some form of revenue stabilisation is employed for all auctioned offshore wind energy farms analysed here, regardless of the specific policy choices. Our data confirm a coincidence of declining costs and growing diffusion of auction regimes.}, language = {en} } @misc{NguyenMuesgens, author = {Nguyen, Thi Ngoc and M{\"u}sgens, Felix}, title = {What drives the accuracy of PV output forecasts?}, series = {Applied Energy}, volume = {323}, journal = {Applied Energy}, issn = {1872-9118}, doi = {10.1016/j.apenergy.2022.119603}, abstract = {In this paper, 180 papers on photovoltaic (PV) output forecasting were reviewed and a database of forecast errors was extracted for statistical analysis. The paper shows that among the forecast models, hybrid models are most likely to become the primary form of PV output forecasting in the future. The use of data processing techniques is positively correlated with the forecast quality, while the lengths of the forecast horizons and out-of-sample test sets have negative effects on the forecast accuracy. The paper also found that the use of data normalization, the wavelet transform, and the inclusion of clear sky index and numerical weather prediction variables are the most effective data processing techniques. Furthermore, the paper found some evidence of "cherry picking" in the reporting of errors and we recommend that the test sets be at least one year long to avoid any distortion in the performance of the models.}, language = {en} } @misc{RiepinSchmidtBaringoetal., author = {Riepin, Iegor and Schmidt, Matthew and Baringo, Luis and M{\"u}sgens, Felix}, title = {Adaptive robust optimization for European strategic gas infrastructure planning}, series = {Applied Energy}, volume = {324}, journal = {Applied Energy}, issn = {1872-9118}, doi = {10.1016/j.apenergy.2022.119686}, abstract = {An adaptive robust optimization model for a gas transmission expansion problem. Analysis of Projects of Common Interests' value in maintaining gas system resilience. Endogenous realizations of cold-winter demand spikes and supply shortages. Publicly available source code for the entire project.}, language = {en} } @misc{JalboutGengeRiepinetal., author = {Jalbout, Eddy and Genge, Lucien and Riepin, Iegor and M{\"u}sgens, Felix}, title = {What do we know about green hydrogen supply costs?}, series = {18th International Conference on the European Energy Market (EEM), 13-15 September 2022, Ljubljana, Slovenia}, journal = {18th International Conference on the European Energy Market (EEM), 13-15 September 2022, Ljubljana, Slovenia}, publisher = {IEEE}, address = {Piscataway, NJ}, isbn = {978-1-6654-0896-7}, issn = {2165-4093}, doi = {10.1109/EEM54602.2022.9921127}, pages = {1 -- 7}, abstract = {This paper is set up to answer the question: What do we know about future hydrogen import costs on the European border? Our work focuses on breaking down, structuring and analysing the body of literature on hydrogen supply chains. We provide a comprehensive analysis on (i) What ranges of costs exist in the literature for specific steps of hydrogen supply chains? (ii) Which assumptions show the highest uncertainty? (iii) Related, what assumption seems to have the most substantial effect on the resulting EUR/kgH2 import cost estimate? While we narrow our discussion focus on North Africa and Australia to Europe in 2050, we hope policymakers, research fellows and energy-sector stakeholders around the globe might be interested in our results.}, language = {en} } @misc{BerneckerRiepinMuesgens, author = {Bernecker, Maximilian and Riepin, Iegor and M{\"u}sgens, Felix}, title = {Modeling of Extreme Weather Events—Towards Resilient Transmission Expansion Planning}, series = {18th International Conference on the European Energy Market (EEM), 13-15 September 2022, Ljubljana, Slovenia}, journal = {18th International Conference on the European Energy Market (EEM), 13-15 September 2022, Ljubljana, Slovenia}, publisher = {IEEE}, address = {Piscataway, NJ}, isbn = {978-1-6654-0896-7}, issn = {2165-4093}, doi = {10.1109/EEM54602.2022.9921145}, pages = {1 -- 7}, abstract = {In this paper, we endogenously compute worst-case weather events in a transmission system expansion planning problem using the robust optimization approach. Mathematically, we formulate a three-level mixed-integer optimization problem, which we convert to a bi-level problem via the strong duality concept. We solve the problem using a constraint-and-column generation algorithm. We use cardinality-constrained uncertainty sets to model the effects of extreme weather realizations on supply from renewable generators.}, language = {en} } @misc{NguyenMuesgens, author = {Nguyen, Thi Ngoc and M{\"u}sgens, Felix}, title = {A Meta-Analysis of Solar Forecasting Based on Skill Score}, series = {arXiv}, journal = {arXiv}, doi = {10.48550/arXiv.2208.10536}, pages = {1 -- 55}, abstract = {We conduct the first comprehensive meta-analysis of deterministic solar forecasting based on skill score, screening 1,447 papers from Google Scholar and reviewing the full texts of 320 papers for data extraction. A database of 4,687 points was built and analyzed with multivariate adaptive regression spline modelling, partial dependence plots, and linear regression. The marginal impacts on skill score of ten factors were quantified. The analysis shows the non-linearity and complex interaction between variables in the database. Forecast horizon has a central impact and dominates other factors' impacts. Therefore, the analysis of solar forecasts should be done separately for each horizon. Climate zone variables have statistically significant correlation with skill score. Regarding inputs, historical data and spatial temporal information are highly helpful. For intra-day, sky and satellite images show the most importance. For day-ahead, numerical weather predictions and locally measured meteorological data are very efficient. All forecast models were compared. Ensemble-hybrid models achieve the most accurate forecasts for all horizons. Hybrid models show superiority for intra-hour while image-based methods are the most efficient for intra-day forecasts. More training data can enhance skill score. However, over-fitting is observed when there is too much training data (longer than 2000 days). There has been a substantial improvement in solar forecast accuracy, especially in recent years. More improvement is observed for intra-hour and intra-day than day-ahead forecasts. By controlling for the key differences between forecasts, including location variables, our findings can be applied globally.}, language = {en} } @misc{JalboutGengeMuesgens, author = {Jalbout, Eddy and Genge, Lucien and M{\"u}sgens, Felix}, title = {H2Europe: an analysis of long-term hydrogen import-potentials from the MENA region}, series = {18th International Conference on the European Energy Market (EEM), 13-15 September 2022, Ljubljana, Slovenia}, journal = {18th International Conference on the European Energy Market (EEM), 13-15 September 2022, Ljubljana, Slovenia}, publisher = {IEEE}, address = {Piscataway, NJ}, isbn = {978-1-6654-0896-7}, issn = {2165-4093}, doi = {10.1109/EEM54602.2022.9921055}, pages = {1 -- 7}, abstract = {Our paper assesses the economic viability of green hydrogen exports from the middle east and north Africa to the EU in the long-term (for the year 2050). For this purpose, we simulate a techno-economic hydrogen supply chain based on generation from renewable energy sources. The chain of production, conversion, and transportation costs, in combination with potentials, yields a merit order of hydrogen supply. The paper focuses on one low-cost option for imports from the middle east and north Africa region. In addition, it provides a classification of additional options. We find that due to proximity, retrofitting and potentially even installing new pipelines from Morocco, Algeria and Tunisia could provide nearly half the expected European demand of 60 million tons p.a. by 2050. Based on our assumptions, the costs would be around 2 €/kgH 2 .}, language = {en} } @incollection{MuesgensRadke, author = {M{\"u}sgens, Felix and Radke, Silvian}, title = {Warmer Lichtsturm - Umgang mit Erzeugungsspitzen aus PV und Wind : Arbeitspaket 1}, series = {Warmer Lichtsturm - Umgang mit Erzeugungsspitzen aus PV und Wind}, volume = {2024}, booktitle = {Warmer Lichtsturm - Umgang mit Erzeugungsspitzen aus PV und Wind}, pages = {13 -- 30}, abstract = {{\"U}ber das Scientific Advisory \& Project Board Die vorliegende Kurzstudie wurde von einem Konsortium entwickelt, das sich aus Mitgliedern des 50Hertz Scientific Advisory and Project Boards (SAPB) zusammensetzt. Das SAPB ist ein Kreis von Professorinnen und Professoren, die 50Hertz darin unterst{\"u}tzen, neue Denk- und L{\"o}sungsans{\"a}tze zu entwickeln und Erkenntnisse aus der Forschung - wo angemessen - in die Praxis von 50Hertz zu {\"u}bernehmen. Disclaimer Im Kontext der durch 50Hertz beauftragten SAPB-Studien forschen die beteiligten Wissenschaftlerinnen und Wissenschaftler frei und ergebnisoffen. Alle durch das Konsortium entwickelten Handlungsempfehlungen werden von 50Hertz eingehend gepr{\"u}ft und diskutiert, letztendlich entsprechen aber nicht alle Positionen denen von 50Hertz.}, language = {de} } @misc{MuesgensGenge, author = {M{\"u}sgens, Felix and Genge, Lucien}, title = {European hydrogen infrastructure planning : insights from the TransHyDE project system analysis}, series = {Flagship Project TransHyDE}, volume = {2024}, journal = {Flagship Project TransHyDE}, pages = {67}, abstract = {The white paper was developed by a selected authorship of the TransHyDE Project System Analysis. The contents of the TransHyDE publications are produced in the project independently of the Federal Ministry of Education and Research.}, language = {en} } @book{MuesgensBade, author = {M{\"u}sgens, Felix and Bade, Alexander}, title = {Energy trading and risk management}, edition = {1. Auflage}, publisher = {Springer Link}, address = {Schweiz}, isbn = {978-3-031-57237-1}, doi = {10.1007/978-3-031-57238-8}, pages = {211}, abstract = {This book offers important insights into the intricacies of energy trading and risk management to students and professionals in the liberalized electricity and natural gas markets. In its opening chapter, the book delves into fundamental concepts, including price formation on wholesale markets. The various market places and trading products are presented, and the distinguishing characteristics of electricity and natural gas compared to other commodities are emphasised. Moving forward, the next chapter concentrates on portfolio management, offering insights into the trading process through the perspectives of various agents. It begins with proprietary traders and progresses to encompass the portfolio management activities of integrated companies responsible for both generation assets and a retail client base. The book then looks at risk management, explaining the diverse risks that impact the value of energy portfolios inthe market. It places emphasis on credit risk, price risk, quantity risk, and product liquidity risk as the most influential factors and presents effective practices for their management. Furthermore, readers will gain a comprehensive understanding of how to manage quantity risk and its interconnectedness with price risk. Additionally, the book addresses the measurement of product liquidity and its disparities across different energy market products. The book then looks at risk management, explaining the diverse risks that impact the value of energy portfolios inthe market. It places emphasis on credit risk, price risk, quantity risk, and product liquidity risk as the most influential factors and presents effective practices for their management. Furthermore, readers will gain a comprehensive understanding of how to manage quantity risk and its interconnectedness with price risk. Additionally, the book addresses the measurement of product liquidity and its disparities across different energy market products. In summary, this book is an accessible introduction and a concise reference for students and professionals across all fields of energy.}, language = {en} } @misc{BenAmorAkkalDeviMuesgens, author = {Ben Amor, Souhir and Akkal Devi, Prashanth and M{\"u}sgens, Felix}, title = {Meta-forecasting for solar power generation: algorithm-based swarm intelligence}, series = {20th International Conference on the European Energy Market (EEM)}, journal = {20th International Conference on the European Energy Market (EEM)}, publisher = {IEEE}, issn = {2165-4093}, doi = {10.1109/EEM60825.2024.10608959}, pages = {5}, abstract = {Our paper introduces a dynamic meta-forecasting approach that optimizes the weights of several available forecasts using a swarm intelligence algorithm, named Particle Swarm Optimization. This algorithm was chosen for its efficiency and convergence performance in solving optimization problems. We apply the methodology to solar photovoltaic day-ahead forecasts utilizing regional data from Germany. Our sample covers the period between 2019 and 2022 at a quarter-hourly frequency. We provide day-ahead forecasts using a rolling estimation window. Alongside benchmark models, Particle Swarm Optimization predictive accuracy is comparable to state-of-the-art models, particularly a dynamic elastic net benchmark model. However, there are slight differences. The investor can choose between Particle Swarm Optimization for its simple implementation and computational efficiency, or dynamic elastic net models for its parameters explainability.}, language = {en} } @misc{GrueblerMuesgens, author = {Gr{\"u}bler, Lene Marie and M{\"u}sgens, Felix}, title = {Applying spatial decomposition in energy system models}, series = {20th International Conference on the European Energy Market (EEM)}, volume = {2024}, journal = {20th International Conference on the European Energy Market (EEM)}, issn = {2165-4093}, doi = {10.1109/EEM60825.2024.10608869}, pages = {8}, abstract = {The European energy transition requires the expansion of renewable generators and consequently, the expansion of grid infrastructure and flexibility options. When modelling complex energy systems, the application of decomposition techniques is reasonable to keep models computationally tractable. Our paper focuses on the efficient optimization of energy systems covering large geographic areas. To accelerate the solving process, we apply a variant of Benders decomposition, which does not only apply temporal but also spatial decomposition. We show that by applying our decomposition approach, the solving time decreases up to 75\% compared to the runtime of the equivalent monolithic model solved by a commercial solver and the barrier algorithm. Furthermore, we show that additionally applying spatial decomposition results in time savings compared to an only temporally decomposed approach.}, language = {en} } @misc{BenAmorMoebiusMuesgens, author = {Ben Amor, Souhir and M{\"o}bius, Thonas and M{\"u}sgens, Felix}, title = {Bridging an energy system model with an ensemble deep-learning approach for electricity price forecasting}, series = {General Economics (econ.GN)}, volume = {2024}, journal = {General Economics (econ.GN)}, doi = {10.48550/arXiv.2411.04880}, pages = {1 -- 49}, abstract = {This paper combines a techno-economic energy system model with an econometric model to maximise electricity price forecasting accuracy. The proposed combination model is tested on the German day-ahead wholesale electricity market. Our paper also benchmarks the results against several econometric alternatives. Lastly, we demonstrate the economic value of improved price estimators maximising the revenue from an electric storage resource. The results demonstrate that our integrated model improves overall forecasting accuracy by 18 \%, compared to available literature benchmarks. Furthermore, our robustness checks reveal that a) the Ensemble Deep Neural Network model performs best in our dataset and b) adding output from the techno-economic energy systems model as econometric model input improves the performance of all econometric models. The empirical relevance of the forecast improvement is confirmed by the results of the exemplary storage optimisation, in which the integration of the techno-economic energy syst}, language = {en} } @misc{SgarciuMuesgensOsorioetal., author = {Sgarciu, Smaranda and M{\"u}sgens, Felix and Osorio, Sebastian and Pahle, Michael}, title = {Is Germany on track to achieve 2030 climate and energy targets?}, series = {List Forum f{\"u}r Wirtschafts- und Finanzpolitik}, volume = {49}, journal = {List Forum f{\"u}r Wirtschafts- und Finanzpolitik}, issn = {2364-3943}, doi = {10.1007/s41025-023-00255-0}, pages = {93 -- 107}, abstract = {The future development of CO2emissions in the German electricity sector by 2030 is unclear: On the one hand, the amendment to the Climate Protection Act (from August 2021) aims to tighten emission reduction targets in order to promote the path to a decarbonised energy system. On the other hand, the complex interplay between the main instruments for reducing carbon emissions, fuel prices and the current energy shortage as a result of Russia's attack on Ukraine is creating pressure for an increase in emissions. In our study, we examine whether Germany is on track to achieve its climate protection targets for 2030 and which measures can increase the likelihood. To do this, we use an energy system model parameterized to reflect the situation in the energy market in 2021, i.e. before Russia's attack on Ukraine. In addition to the quantitative side, we provide a qualitative analysis of the energy market in the light of recent events. We stress the importance of introducing a carbon price floor that can be dynamically changed in response to the development of other market forces and policies. This instrument would institutionalize a more plausible path to decarbonization and provide reassurance to investors.}, language = {en} } @misc{HoffmannByrukuriGangadharMuesgens, author = {Hoffmann, Christin and Byrukuri Gangadhar, Shanmukha Srinivas and M{\"u}sgens, Felix}, title = {Smells Like Green Energy - Quasi-Experimental Evidence on the Impact of Bioenergy Production on Residential Property Values}, series = {SSRN eLibrary}, journal = {SSRN eLibrary}, issn = {1556-5068}, doi = {10.2139/ssrn.4760312}, pages = {1 -- 26}, abstract = {Residents' acceptance of bioenergy is a prerequisite for its fast and efficient development but is ambiguously discussed in practice and research. We interpret a causal impact of bioenergy plant commissioning on housing prices in their vicinity as the average net external effects for residents. We utilize bioenergy plant construction data in Germany between 2007 and 2022 as a quasi-experiment with naturally occurring control groups in their vicinity and apply recently improved difference-in-difference estimation procedures to analyze instantaneous and heterogeneous treatment effects. We find a significant and negative impact on housing prices if plants use gaseous biofuel, generate electricity on-site, and are medium-sized. The magnitude of the effect is comparable to those for solar fields. In contrast, we find no impact for small and large bioenergy plants and those that use solid or liquid biofuels.}, language = {en} } @misc{SgarciuScholzMuesgens, author = {Sgarciu, Smaranda and Scholz, Daniel and M{\"u}sgens, Felix}, title = {How CO2 prices accelerate decarbonisation - The case of coal-fired generation in Germany}, series = {Energy Policy}, volume = {173}, journal = {Energy Policy}, issn = {0301-4215}, doi = {10.1016/j.enpol.2022.113375}, abstract = {This paper analyses the potential impact of the world's two main coal phase-out instruments: 1) direct regulatory intervention restricting the operation of existing coal-fired generation capacity and prohibiting investment in new capacity and 2) market-based CO2-pricing instruments that make emission-intensive coal-fired generation less competitive. We quantify these instruments' potential effects in the empirical setting of Germany, where both instruments are employed concurrently. However, this paper's approach and methodology can be applied in any jurisdiction or energy system worldwide. Our paper provides quantitative results with a pan-European partial-equilibrium electricity system model. The model applies an innovative three-step approach. Step 1 solves an investment and dispatch problem with reduced technical and temporal complexity for European countries. Step 2 computes the dispatch problem at a bihourly resolution and step 3 solves the investment and dispatch problem for Germany with increased technical complexity. Our results confirm that both a regulated phase-out as well as a price on CO2 emissions can reduce the amount of coal-fired generation in an electricity system. If CO2 prices remain at current levels, coal-fired power plants leave the market significantly before the regulated phase-out date, reducing demand for employees in the Lusatian lignite industry. Regions and federal governments should take this finding into account when planning and preparing for structural change.}, language = {en} }