TY - CHAP A1 - Cunha Montenegro, Roland A1 - Riepin, Iegor A1 - Hauser, Philipp T1 - Modelling of world LNG market development: focus on US investments and supplies T2 - IEEE Conference Proceedings EEM 2016 Y1 - 2016 UR - http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7521361 SN - 978-1-5090-1298-5 PB - IEEE CY - Piscataway, NJ ER - 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 - RPRT A1 - Riepin, Iegor A1 - Jansen, Malte A1 - Staffell, Iain A1 - Müsgens, Felix T1 - The era of ‘negative-subsidy’ offshore wind power has almost arrived KW - offshore wind farms KW - Nature Energy KW - Offshore wind auctions KW - offshore wind Y1 - 2020 UR - https://www.carbonbrief.org/guest-post-the-era-of-negative-subsidy-offshore-wind-power-has-almost-arrived 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 - Riepin, Iegor A1 - Müsgens, Felix T1 - Seasonal flexibility in the European natural gas market T2 - The Energy Journal N2 - 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. KW - Energy markets and pricing Y1 - 2022 UR - https://www.iaee.org/energyjournal/article/3779 U6 - https://doi.org/10.5547/01956574.43.1.irie SN - 1944-9089 SN - 0195-6574 VL - 43 IS - 1 SP - 117 EP - 138 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 - GEN A1 - Jalbout, Eddy A1 - Genge, Lucien A1 - Riepin, Iegor A1 - Müsgens, Felix T1 - What do we know about green hydrogen supply costs? T2 - 18th International Conference on the European Energy Market (EEM), 13-15 September 2022, Ljubljana, Slovenia N2 - 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. KW - Industries KW - Costs KW - Uncertainty KW - Hydrogen KW - Supply chains KW - Europe KW - IEEE Fellows Y1 - 2022 SN - 978-1-6654-0896-7 SN - 978-1-6654-0897-4 U6 - https://doi.org/10.1109/EEM54602.2022.9921127 SN - 2165-4093 SN - 2165-4077 SP - 1 EP - 7 PB - IEEE CY - Piscataway, NJ ER - TY - GEN A1 - Bernecker, Maximilian A1 - Riepin, Iegor A1 - Müsgens, Felix T1 - Modeling of Extreme Weather Events—Towards Resilient Transmission Expansion Planning T2 - 18th International Conference on the European Energy Market (EEM), 13-15 September 2022, Ljubljana, Slovenia N2 - 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. KW - Adaptation models KW - Renewable energy sources KW - Wind KW - Uncertainty KW - Mathematical models KW - Power systems KW - Planning Y1 - 2022 SN - 978-1-6654-0896-7 SN - 978-1-6654-0897-4 U6 - https://doi.org/10.1109/EEM54602.2022.9921145 SN - 2165-4093 SN - 2165-4077 SP - 1 EP - 7 PB - IEEE CY - Piscataway, NJ ER - TY - GEN A1 - Riepin, Iegor A1 - Schmidt, Matthew A1 - Baringo, Luis A1 - Müsgens, Felix T1 - Adaptive robust optimization for European strategic gas infrastructure planning T2 - Applied Energy N2 - 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. KW - Adaptive robust optimization KW - Capacity planning KW - European gas market KW - Uncertainty Y1 - 2022 U6 - https://doi.org/10.1016/j.apenergy.2022.119686 SN - 1872-9118 SN - 0306-2619 VL - 324 ER - TY - GEN A1 - Jansen, Malte A1 - Beiter, Philipp A1 - Riepin, Iegor A1 - Müsgens, Felix A1 - Guajardo-Fajardo, Victor Juarez A1 - Staffell, Iain A1 - Bulder, Bernard A1 - Kitzing, Lena T1 - Policy choices and outcomes for the competitive procurement of offshore wind energy globally T2 - Energy Policy N2 - 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. KW - Renewable energy KW - Tender design KW - Auction database KW - Support scheme KW - Policy analysis KW - Remuneration Mechanism KW - Revenue stabilisation Y1 - 2022 U6 - https://doi.org/10.1016/j.enpol.2022.113000 SN - 0301-4215 VL - 167 ER - TY - CHAP A1 - Müsgens, Felix A1 - Riepin, Iegor T1 - Is Offshore Already Competitive? Analyzing German Offshore Wind Auctions T2 - 15th International Conference on the European Energy Market (EEM), 27-29 June 2018, Lodz, Poland N2 - Two German offshore wind auctions in 2017 and 2018 saw more than 50% of winning capacity with “zero bids”. The nature of these surprisingly low bids is, however, not yet clear. In our paper, we discuss four hypotheses for possible causes for the auction results: (i) the bids are expected to be profitable due to market development and technological progress, (ii) bids can be perceived as “options to build” that can be realized if projects are profitable, (iii) bids are adjusted to secure grid access, and (iv) other long term reasons not primarily driven by the profitability of the winning bids. Our results suggest that there is evidence for all hypotheses to influence the decision making of auction bidders. In fact, we suggest to see the four hypothesis as cumulative value components, which reveal the true value of winning the auction at “zero cost” in aggregate. KW - renewable energy auction KW - offshore wind Y1 - 2018 UR - https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8469851 SN - 978-1-5386-1488-4 U6 - https://doi.org/10.1109/EEM.2018.8469851 PB - IEEE CY - Piscataway, NJ 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 - GEN A1 - Müsgens, Felix A1 - Riepin, Iegor T1 - Offshore-Windenergie - subventionsfrei? T2 - e|m|w.Trends : das Innovationsmagazin von ener|gate KW - Offshore-Windenergie KW - Nature Energy KW - Offshore-Windtechnologien Y1 - 2020 UR - https://www.emw-online.com/trends/artikel/205364/offshore-windenergie-subventionsfrei SN - 1611-2997 IS - 5 ER - TY - GEN A1 - Jansen, Malte A1 - Staffell, Iain A1 - Kitzing, Lena A1 - Quoilin, Sylvain A1 - Wiggelinkhuizen, Edwin A1 - Bulder, Bernard A1 - Riepin, Iegor A1 - Müsgens, Felix T1 - Offshore wind competitiveness in mature markets without subsidy T2 - Nature Energy Y1 - 2020 UR - https://www.nature.com/articles/s41560-020-0661-2 U6 - https://doi.org/10.1038/s41560-020-0661-2 SN - 2058-7546 VL - 5 IS - 8 SP - 614 EP - 622 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 - 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 - RPRT A1 - Müsgens, Felix A1 - Riepin, Iegor A1 - Poudineh, Rahmat T1 - A Note on Climate Policy Negotiations at the Threshold of COP-21 in Paris KW - climate change KW - global warming KW - carbon price KW - cap-and-trade Y1 - 2015 UR - https://www-docs.b-tu.de/fg-energiewirtschaft/public/Veroeffentlichungen/A_Note_on_Climate_Policy_Negotiations.pdf ER -