@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} } @misc{HoffmannThommes, author = {Hoffmann, Christin and Thommes, Kirsten}, title = {Can leaders motivate employees' energy-efficient behavior with thoughtful communication?}, series = {Journal of Environmental Economics and Management}, volume = {125}, journal = {Journal of Environmental Economics and Management}, pages = {24}, abstract = {We study the effect of an employer's communication concerning energy-efficient behavior on a firm's employees' behavioral responses. The management aims to enhance energy-efficient behavior performance by irregularly sending online messages to remote employees. We break down each message, analyzing the positive or negative emotions conveyed, collective or individual orientation, and ease of language. Comparing employees' daily energy efficiency after receiving a message to their daily performance without a previous message, we find that messages generally result in an immediate increase in efficiency. Messages conveying negative emotions and those making a distinction between the manager and the employees have a smaller effect than messages conveying positive emotions and emphasizing a collective orientation that includes both the management and employees. Additionally, shorter messages are more likely to induce improved efficiency. Sending messages significantly impacts driver performance for up to six days after the message, resulting in economically relevant cost reductions.}, 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{MuhammadHoffmann, author = {Muhammad, Sulaman and Hoffmann, Christin}, title = {From investment to impact: The role of green finance and technological innovation on German energy transition}, series = {Renewable Energy}, volume = {237 Part B}, journal = {Renewable Energy}, publisher = {Elsevier}, doi = {10.1016/j.renene.2024.121665}, pages = {1 -- 12}, abstract = {Germany is a global leader in environmental protection and has embraced a fast-track transition towards renewable energy adaptation. To support the continuous energy transition, an approximate sum of EUR 3000 billion needs to be mobilized by 2050, making it an exemplary case for examining the influence of green finance on renewable energy consumption and technological innovation. The objective of this study is to investigate the impact of green finance and technological innovation on renewable energy consumption across 16 federal German states, utilizing panel data from 2008 to 2021. Two novel financial proxies, green investment and environmental protection-related sales, are introduced to capture the financial mechanisms underpinning the energy transition. MMQ (method of moments quantile) regression is employed to explore the short and long-run relationship among variables. The results reveal that while environmental protection-related sales consistently increase renewable energy consumption, the positive effects of green investment manifest only in the long term. Furthermore, the results indicate that solely increasing R\&D funds does not necessarily boost renewable energy consumption. However, the positive interplay between R\&D and patent applications significantly increases electricity generation from renewable sources. Indicating that integrated financial and technological strategies are essential for advancing Germany's renewable energy goals.}, language = {en} } @misc{Hoffmann, author = {Hoffmann, Christin}, title = {Inter- and intragenerational differences in corrupt behavior: The development of morals after German reunification}, series = {European Journal of Comparative Economics}, volume = {21 (2024)}, journal = {European Journal of Comparative Economics}, issn = {1824-2979}, doi = {10.25428/1824-2979/032}, pages = {211 -- 264}, abstract = {We investigate differences in bribing decisions among two generations from East and West Germany in a bribery game conducted as an online study (N=168). This way, we aim to explore moral considerations of individuals influenced by two formerly different institutional systems. We find a higher propensity to bribe among young Germans compared to the older generation. Young East Germans even reveal a slightly greater inclination to bribe than their West German counterparts. We conclude that preferences for personal favors may be induced among young East Germans given the tense relationship between market opportunities and conveyed cultural traits of a socialist imprint.}, 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{HoffmannThommes, author = {Hoffmann, Christin and Thommes, Kirsten}, title = {Can leaders motivate employees' energy-efficient behavior with thoughtful communication?}, series = {Journal of Environmental Economics and Management}, volume = {125}, journal = {Journal of Environmental Economics and Management}, issn = {0095-0696}, doi = {10.1016/j.jeem.2024.102990}, pages = {1 -- 24}, abstract = {We study the effect of an employer's communication concerning energy-efficient behavior on a firm's employees' behavioral responses. The management aims to enhance energy-efficient behavior performance by irregularly sending online messages to remote employees. We break down each message, analyzing the positive or negative emotions conveyed, collective or individual orientation, and ease of language. Comparing employees' daily energy efficiency after receiving a message to their daily performance without a previous message, we find that messages generally result in an immediate increase in efficiency. Messages conveying negative emotions and those making a distinction between the manager and the employees have a smaller effect than messages conveying positive emotions and emphasizing a collective orientation that includes both the management and employees. Additionally, shorter messages are more likely to induce improved efficiency. Sending messages significantly impacts driver performance for up to six days after the message, resulting in economically relevant cost reductions.}, language = {en} }