TY - GEN A1 - Möbius, Thomas A1 - Riepin, Iegor T1 - Regret analysis of investment decisions under uncertainty in an integrated energy system T2 - 17th International Conference on the European Energy Market (EEM), 16-18 Sept. 2020 Y1 - 2020 UR - https://ieeexplore.ieee.org/document/9221935 SN - 978-1-7281-6919-4 SN - 978-1-7281-6920-0 U6 - https://doi.org/10.1109/EEM49802.2020.9221935 SN - 2165-4093 N1 - EEM Best Paper Award 3rd place PB - IEEE CY - Piscataway, NJ ER - TY - GEN A1 - Riepin, Iegor A1 - Möbius, Thomas A1 - Müsgens, Felix T1 - Modelling uncertainty in coupled electricity and gas systems - is it worth the effort? T2 - Applied Energy N2 - The interdependence of electricity and natural gas markets is becoming a major topic in energy research. Integrated energy models are used to assist decision-making for businesses and policymakers addressing challenges of energy transition and climate change. The analysis of complex energy systems requires large-scale models, which are based on extensive databases, intertemporal dynamics and a multitude of decision variables. Integrating such energy system models results in increased system complexity. This complexity poses a challenge for energy modellers to address multiple uncertainties that affect both markets. Stochastic optimisation approaches enable an adequate consideration of uncertainties in investment and operation planning; however, stochastic modelling of integrated large-scale energy systems further scales the level of complexity. In this paper, we combine integrated and stochastic optimisation problems and parametrise our model for European electricity and gas markets. We analyse and compare the impact of uncertain input parameters, such as gas and electricity demand, renewable energy capacities and fuel and CO2 prices, on the quality of the solution obtained in the integrated optimisation problem. Our results quantify the value of encoding uncertainty as a part of a model. While the methodological contribution should be of interest for energy modellers, our findings are relevant for industry experts and stakeholders with an empirical interest in the European energy system. KW - Energy markets and pricing Y1 - 2021 UR - https://www.sciencedirect.com/science/article/abs/pii/S0306261920317426?via%3Dihub U6 - https://doi.org/10.1016/j.apenergy.2020.116363 SN - 1872-9118 VL - 285 ER - TY - GEN A1 - Möbius, Thomas A1 - Watermeyer, Mira A1 - Grothe, Oliver A1 - Müsgens, Felix T1 - Enhancing energy system models using better load forecasts T2 - Energy Systems N2 - Since energy system models require a large amount of technical and economic data, their quality significantly affects the reliability of the results. However, some publicly available data sets, such as the transmission system operators’ day-ahead load forecasts, are known to be biased and inaccurate, leading to lower energy system model performance. We propose a time series model that enhances the accuracy of transmission system operators’ load forecast data in real-time, using only the load forecast error’s history as input. We further present an energy system model developed specifically for price forecasts of the short-term day-ahead market. We demonstrate the effectiveness of the improved load data as input by applying it to this model, which shows a strong reduction in pricing errors, particularly during periods of high prices and tight markets. Our results highlight the potential of our method the enhance the accuracy of energy system models using improved input data. KW - Data pre-processing KW - Day-ahead electricity prices KW - Energy system modelling Y1 - 2023 U6 - https://doi.org/10.1007/s12667-023-00590-3 SN - 1868-3975 SP - 1 EP - 30 ER - TY - GEN A1 - Möbius, Thomas A1 - Riepin, Iegor A1 - Müsgens, Felix A1 - van der Weijde, Adriaan H. T1 - Risk aversion and flexibility options in electricity markets T2 - Energy Economics N2 - Investments in electricity transmission and generation capacity must be made despite significant uncertainty about the future developments. The sources of this uncertainty include, among others, the future levels and spatiotemporal distribution of electricity demand, fuel costs and future energy policy. In recent years, these uncertainties have increased due to the ongoing evolution of supply- and demand-side technologies and rapid policy changes designed to encourage a transition to low-carbon energy systems. Because transmission and generation investments have long lead times and are difficult to reverse, they are subject to a considerable – and arguably growing – amount of risk. KW - Flexibility KW - Storage KW - Demand response KW - Generation and transmission KW - expansion KW - Investment KW - Risk aversion KW - Stochastic programming Y1 - 2023 SN - 0140-9883 SN - 1873-6181 VL - 126 ER - TY - CHAP A1 - Riepin, Iegor A1 - Möbius, Thomas A1 - Müsgens, Felix T1 - Integrated Electricity and Gas Market Modeling – Effects of Gas Demand Uncertainty T2 - 15th International Conference on the European Energy Market (EEM), 27-29 June 2018, Lodz, Poland N2 - This paper develops an integrated fundamental investment model which considers both the gas and electricity sector. Furthermore, we adopt the theory of stochastic programming with recourse in the combined model to account for uncertainty in the gas market. This approach enables us to analyze how uncertain gas demand in other sectors affects decisions to invest in electricity generation capacities. We find an overall decrease and a reallocation of investments in gas-fired power plants. We also quantify the expected costs of ignoring uncertainty. KW - electricity market KW - integrated energy system modeling KW - natural gas market KW - stochastic modeling Y1 - 2018 UR - https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8469790 SN - 978-1-5386-1488-4 U6 - https://doi.org/10.1109/EEM.2018.8469790 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Nacken, Lukas A1 - Möbius, Thomas T1 - The effects of harmonized European climate policy targets in comparison to national targets utilizing a European electricity market model T2 - 14th International Conference on the European Energy Market (EEM), Dresden Germany, 6-9 June 2017 Y1 - 2017 SN - 978-1-5090-5499-2 U6 - https://doi.org/10.1109/EEM.2017.7981987 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Spisto, Amanda A1 - Möbius, Thomas A1 - Quoilin, Sylvain T1 - Demand for flexibility in the power system under different shares of renewable generation T2 - 12th International Conference on the European Energy Market (EEM), Lisbon, Portugal 19-22 May 2015 Y1 - 2015 SN - 978-1-4673-6692-2 U6 - https://doi.org/10.1109/EEM.2015.7216775 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Möbius, Thomas A1 - Müsgens, Felix T1 - Electricity Market Equilibria and Intermittent Renewables – A Stochastic Approach T2 - 14th International Conference on the European Energy Market (EEM), Dresden Germany, 6-9 June 2017 Y1 - 2017 SN - 978-1-5090-5499-2 U6 - https://doi.org/10.1109/EEM.2017.7981988 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Möbius, Thomas A1 - Gunkel, David T1 - The Optimal Placing of Energy Storages in Germany in 2020 - An Implementation of a DC-Load Flow Model T2 - 11th International Conference on the European Energy Market Y1 - 2014 SN - 978-1-4799-6096-5 SP - 245 EP - 249 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Möbius, Thomas A1 - Müsgens, Felix T1 - The Effect of Variable Renewable Energy Sources on the Volatility of Wholesale Electricity Prices - A Stylized Full Cost Approach T2 - Proceedings, 12th International Conference on the European Energy Market (EEM), Lisbon, 19-22 May 2015 Y1 - 2015 SN - 978-1-4673-6692-2 U6 - https://doi.org/10.1109/EEM.2015.7216772 PB - IEEE CY - Piscataway, NJ 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 - 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 -