TY - GEN A1 - Nguyen, Thi Ngoc A1 - Müsgens, Felix T1 - A Meta-Analysis of Solar Forecasting Based on Skill Score T2 - arXiv N2 - 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. Y1 - 2023 U6 - https://doi.org/10.48550/arXiv.2208.10536 SP - 1 EP - 55 ER - TY - GEN A1 - Jalbout, Eddy A1 - Genge, Lucien A1 - Müsgens, Felix T1 - H2Europe: an analysis of long-term hydrogen import-potentials from the MENA region T2 - 18th International Conference on the European Energy Market (EEM), 13-15 September 2022, Ljubljana, Slovenia N2 - 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 . KW - Renewable energy sources KW - Costs KW - Pipelines KW - Supply chains KW - Green products KW - Europe KW - Hydrogen Y1 - 2022 SN - 978-1-6654-0896-7 SN - 978-1-6654-0897-4 U6 - https://doi.org/10.1109/EEM54602.2022.9921055 SN - 2165-4093 SN - 2165-4077 SP - 1 EP - 7 PB - IEEE CY - Piscataway, NJ ER - TY - GEN A1 - Riepin, Iegor A1 - Sgarciu, Smaranda A1 - Bernecker, Maximilian A1 - Möbius, Thomas A1 - Müsgens, Felix T1 - Grok It and Use It: Teaching Energy Systems Modeling T2 - SSRN eLibrary N2 - This article details our experience developing and teaching an “Energy Systems Modeling” course, which sought to introduce graduate-level students to operations research, energy economics, and system modeling using the General Algebraic Modeling System (GAMS). In this paper, we focus on (i) the mathematical problems discussed in the course, (ii) the energy-related empirical interpretations of these mathematical problems, and (iii) the best teaching practices (i.e., our experiences regarding how to make the content interesting and accessible for students). KW - Energy Systems KW - Mathematical Programming KW - Optimization KW - Teaching Y1 - 2023 U6 - https://doi.org/10.2139/ssrn.4320978 SN - 1556-5068 ER - TY - GEN A1 - Watermeyer, Mira A1 - Möbius, Thomas A1 - Grothe, Oliver A1 - Müsgens, Felix T1 - A hybrid model for day-ahead electricity price forecasting: Combining fundamental and stochastic modelling T2 - arXiv N2 - The accurate prediction of short-term electricity prices is vital for effective trading strategies, power plant scheduling, profit maximisation and efficient system operation. However, uncertainties in supply and demand make such predictions challenging. We propose a hybrid model that combines a techno-economic energy system model with stochastic models to address this challenge. The techno-economic model in our hybrid approach provides a deep understanding of the market. It captures the underlying factors and their impacts on electricity prices, which is impossible with statistical models alone. The statistical models incorporate non-techno-economic aspects, such as the expectations and speculative behaviour of market participants, through the interpretation of prices. The hybrid model generates both conventional point predictions and probabilistic forecasts, providing a comprehensive understanding of the market landscape. Probabilistic forecasts are particularly valuable because they account for market uncertainty, facilitating informed decision-making and risk management. Our model delivers state-of-the-art results, helping market participants to make informed decisions and operate their systems more efficiently. Y1 - 2023 U6 - https://doi.org/10.48550/arXiv.2304.09336 SP - 1 EP - 38 ER - TY - GEN A1 - Müsgens, Felix A1 - Ockenfels, Axel T1 - Design von Informationsfeedback in Regelenergiemärkten T2 - Zeitschrift für Energiewirtschaft N2 - Auf vielen kontinentaleuropäischen Energiemärkten werden derzeit die Regeln für das Feedback auf Regelenergiemärkten diskutiert: welche Informationen zu vergangenen Auktionen sollen wann veröffentlicht werden? Dieser Artikel beleuchtet Vor- und Nachteile verschiedener Feedbackpolitiken am Beispiel der Schweizer Regelenergiemärkte. Die Veröffentlichung des Grenzleistungspreises ist in der Regel zu empfehlen. Dies gilt jedoch nicht für weitere Informationen (insbesondere extramarginale Gebote). Die optimale Feedbackpolitik hängt allerdings vom jeweiligen Marktdesign und von der Marktstruktur ab KW - Strommärkte KW - Regelenergie KW - Marktdesign Y1 - 2011 U6 - https://doi.org/10.1007/s12398-011-0062-0 SN - 1866-2765 VL - 35 IS - 4 SP - 249 EP - 256 ER - TY - GEN A1 - Kreuz, Sebastian A1 - Müsgens, Felix T1 - Asymmetric Diesel Retail Pricing Strategies: Depending on Brands and Population Densities? T2 - Zeitschrift für Energiewirtschaft KW - Diesel price KW - Error correction model KW - Oil price KW - Retail fuel KW - Rockets and feathers KW - Spatial analysis Y1 - 2019 U6 - https://doi.org/10.1007/s12398-019-00252-x SN - 0343-5377 SN - 1866-2765 VL - 43 IS - 2 SP - 117 EP - 130 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 - TY - RPRT A1 - Riepin, Iegor A1 - Müsgens, Felix T1 - Seasonal Flexibility in the European Natural Gas Market KW - European gas market KW - market modelling KW - seasonality Y1 - 2019 UR - https://www.eprg.group.cam.ac.uk/eprg-working-paper-1931/ PB - University of Cambridge, Energy Policy Research Group CY - Cambridge ER - TY - THES A1 - Müsgens, Felix T1 - The Economics of Wholesale Electricity Markets N2 - Die Dissertation analysiert die ökonomischen Zusammenhänge und Wechselwirkungen auf Großhandelsmärkten für Strom. KW - Energy Economics KW - Electricity Price KW - Competitive Benchmarking KW - Optimization Model KW - Market Power Y1 - 2005 PB - Universität CY - Köln ER - TY - RPRT A1 - Müsgens, Felix A1 - Neuhoff, Karsten T1 - Modelling Dynamic Constraints in Electricity Markets and the Costs of Uncertain Wind Output Y1 - 2006 UR - https://www.eprg.group.cam.ac.uk/wp-content/uploads/2014/01/eprg0514.pdf PB - University of Cambridge, Electricity Policy Research Group CY - Cambridge ER -