TY - JOUR A1 - Ruhnau, Oliver A1 - Stiewe, Clemens A1 - Muessel, Jarusch A1 - Hirth, Lion T1 - Natural gas savings in Germany during the 2022 energy crisis JF - Nature Energy N2 - Russia curbed its natural gas supply to Europe in 2021 and 2022, creating a grave energy crisis. This paper empirically estimates the crisis response of natural gas consumers in Germany—for decades the largest export market for Russian gas. Using a multiple regression model, we estimate the response of small consumers, industry, and power stations separately, controlling for the non-linear temperature-heating relationship, seasonality, and trends. We find significant and substantial gas savings for all consumer groups, but with differences in timing and size. For instance, industry started reducing consumption as early as September 2021, while small consumers saved substantially only since March 2022. Across all sectors, gas consumption during the second half of 2022 was 23% below the temperature-adjusted baseline. We discuss the drivers behind these savings and draw conclusions on their role in coping with the crisis. Y1 - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b1570-opus4-49445 U6 - https://doi.org/10.48462/opus4-4944 N1 - This is a post-peer-review, pre-copyedit version of an article published in Nature Energy. The final authenticated version is available online at: https://doi.org/10.1038/s41560-023-01260-5 ER - TY - JOUR A1 - Schlecht, Ingmar A1 - Maurer, Christoph A1 - Hirth, Lion T1 - Financial contracts for differences: The problems with conventional CfDs in electricity markets and how forward contracts can help solve them JF - Energy Policy N2 - Contracts for differences are widely seen as a cornerstone of Europe's future electricity market design. This paper is about designing such contracts. We identify the dispatch and investment distortions that conventional CfDs cause, the patches used to overcome these shortcomings, and the problems these fixes introduce. We then propose an alternative contract we call “financial” CfD. This hybrid between conventional CfDs and forward contracts mitigates revenue risk to a substantial degree while providing undistorted incentives. Like conventional CfDs, it is long-term and tailored to technology-specific (wind, solar, nuclear) generation patterns but, like forwards, decouples payments from actual generation. The proposed contract mitigates volume risk and avoids margin calls by accepting physical assets as collateral. KW - Management, Monitoring, Policy and Law KW - General Energy Y1 - 2024 U6 - https://doi.org/10.1016/j.enpol.2024.113981 VL - 186 ER - TY - RPRT A1 - Hirth, Lion A1 - Khanna, Tarun A1 - Ruhnau, Oliver T1 - The (very) short-term price elasticity of German electricity demand N2 - Electricity is a peculiar economic good, the most important reason being that it needs to be supplied at the very moment of consumption. As a result, wholesale electricity prices fluctuate widely at hourly or sub-hourly time scales, regularly reaching multiples of their average, and even turn negative. This paper examines whether the demand for electricity responds to such price variations in the very short term. To solve the classical identification problem when estimating a demand curve, we use weather-driven wind energy generation as an instrument. Our robustness checks confirm that wind energy is indeed a strong and valid instrument. Using data from Germany, we estimate that a 1 €/MWh increase in the wholesale electricity price causes the aggregate electricity demand to decline by 67–80 MW or 0.12–0.14%, contradicting the conventional wisdom that electricity demand is highly price-inelastic. These estimates are statistically significant and robust across model specifications, estimators, and sensitivity analyses. At average price and demand, our estimates correspond to a price elasticity of demand of about –0.05. Comparing situations with high and low wind energy (5–95th percentile), we estimate that prices vary by 26 €/MWh, and the corresponding demand response to wholesale electricity prices is about 2 GW, or 2.6% of peak load. Our analysis suggests that the demand response in Germany can be attributed primarily to industrial consumers. KW - Electricity markets KW - Price elasticity KW - Demand response KW - Instrumental variables KW - Centre for Sustainability Y1 - 2022 UR - https://www.econstor.eu/handle/10419/249570 ER - TY - JOUR A1 - Ruhnau, Oliver A1 - Eicke, Anselm A1 - Sgarlato, Raffaele A1 - Tröndle, Tim A1 - Hirth, Lion T1 - Cost-Potential Curves of Onshore Wind Energy: the Role of Disamenity Costs JF - Environmental and Resource Economics N2 - Numerical optimization models are used to develop scenarios of the future energy system. Usually, they optimize the energy mix subject to engineering costs such as equipment and fuel. For onshore wind energy, some of these models use cost-potential curves that indicate how much electricity can be generated at what cost. These curves are upward sloping mainly because windy sites are occupied first and further expanding wind energy means deploying less favorable resources. Meanwhile, real-world wind energy expansion is curbed by local resistance, regulatory constraints, and legal challenges. This presumably reflects the perceived adverse effect that onshore wind energy has on the local human population, as well as other negative external effects. These disamenity costs are at the core of this paper. We provide a comprehensive and consistent set of cost-potential curves of wind energy for all European countries that include disamenity costs, and which can be used in energy system modeling. We combine existing valuation of disamenity costs from the literature that describe the costs as a function of the distance between turbine and households with gridded population data, granular geospatial data of wind speeds, and additional land-use constraints to calculate such curves. We find that disamenity costs are not a game changer: for most countries and assumptions, the marginal levelized cost of onshore wind energy increase by 0.2–12.5 €/MWh. KW - Centre for Sustainability Y1 - 2022 U6 - https://doi.org/10.1007/s10640-022-00746-2 ER - TY - RPRT A1 - Stiewe, Clemens A1 - Ruhnau, Oliver A1 - Hirth, Lion T1 - European industry responds to high energy prices: The case of German ammonia production. N2 - Since September 2021, European natural gas prices are at record-high levels. On average, they have been six to seven times higher than pre-pandemic price levels. While the post-pandemic recovery of global natural gas demand has driven up prices around the world, the most important drivers for European gas prices were Russia's less-than-usual supply since mid-2021 and its invasion of Ukraine in February 2022. Western efforts to abandon Russian gas imports altogether mean that high natural gas prices are likely to stay for longer. While high gas prices may be the new normal, there is uncertainty about the economic reaction to this shock. How do energy-intensive industries react? Do global value chains collapse if intermediate goods produced in Europe become uneconomic because of high energy prices? Our preliminary analysis shows that industry response to has in fact been visible from the very onset of the energy crisis. A closer look at German fertilizer production, which heavily relies on natural gas as fuel and feedstock to produce ammonia as an intermediate product, reveals that increased ammonia imports have allowed domestic fertilizer production to remain remarkably stable. KW - Energy Demand KW - Demand response KW - European energy crisis KW - Natural gas KW - Centre for Sustainability Y1 - 2022 UR - https://www.econstor.eu/handle/10419/253251 ER - TY - JOUR A1 - Winzer, Christian A1 - Ramírez-Molina, Héctor A1 - Hirth, Lion A1 - Schlecht, Ingmar T1 - Profile contracts for electricity retail customers JF - Energy Policy N2 - Decarbonization involves a large-scale expansion of low-carbon generators such as wind and solar and the electrification of heating and transport. Both space heating and battery-electric cars have significant embedded flexibility potential. Granular price signals that convey abundance or scarcity of electricity are a precondition for customers or aggregators acting on their behalf to exploit this flexibility. However, unmitigated real-time prices expose customers to electricity price risks. To tackle the dual need of providing flexibility incentives while protecting customers from cost shocks, real-time tariffs with a hedging component can be a solution. In such contracts customers pre-agree an amount of energy and a consumption profile, while hourly deviations are charged at spot prices. In this paper we analyze design options by using a dataset of anonymized smart meter data and show that profile tariffs can bring electricity bill volatility to similarly low levels as fixed tariffs while providing full flexibility incentives from spot prices. Y1 - 2024 U6 - https://doi.org/10.1016/j.enpol.2024.114358 SN - 0301-4215 VL - 195 PB - Elsevier BV ER - TY - RPRT A1 - Xu, Alice Lixuan A1 - Sánchez Canales, Jorge A1 - Fusar Bassini, Chiara A1 - Kaack, Lynn H. A1 - Hirth, Lion T1 - Market power abuse in wholesale electricity markets N2 - In wholesale electricity markets, prices fluctuate widely from hour to hour and electricity generators price-hedge their output using longer-term contracts, such as monthly base futures. Consequently, the incentives they face to drive up the power prices by reducing supply has a high hourly specificity, and because of hedging, they regularly also face an incentive to depress prices by inflating supply. In this study, we explain the dynamics between hedging and market power abuse in wholesale electricity markets and use this framework to identify market power abuse in real markets. We estimate the hourly economic incentives to deviate from competitive behavior and examine the empirical association between such incentives and observed generation patterns. Exploiting hourly variation also controls for potential estimation bias that do not correlate with economic incentives at the hourly level, such as unobserved cost factors. Using data of individual generation units in Germany in a six-year period 2019-2024, we find that in hours where it is more profitable to inflate prices, companies indeed tend to withhold capacity. We find that the probability of a generation unit being withheld increases by about 1 % per euro increase in the net profit from withholding one megawatt of capacity. The opposite is also true for hours in which companies benefit financially from lower prices, where we find units being more likely to be pushed into the market by 0.3 % per euro increase in the net profit from capacity push-in. We interpret the result as empirical evidence of systematic market power abuse. Y1 - 2025 U6 - https://doi.org/10.48550/arXiv.2506.03808 PB - arXiv ER - TY - RPRT A1 - Fusar Bassini, Chiara A1 - Xu, Alice Lixuan A1 - Sánchez Canales, Jorge A1 - Hirth, Lion A1 - Kaack, Lynn T1 - Revealing the empirical flexibility of gas units through deep clustering N2 - The flexibility of a power generation unit determines how quickly and often it can ramp up or down. In energy models, it depends on assumptions on the technical characteristics of the unit, such as its installed capacity or turbine technology. In this paper, we learn the empirical flexibility of gas units from their electricity generation, revealing how real-world limitations can lead to substantial differences between units with similar technical characteristics. Using a novel deep clustering approach, we transform 5 years (2019-2023) of unit-level hourly generation data for 49 German units from 100 MWp of installed capacity into low-dimensional embeddings. Our unsupervised approach identifies two clusters of peaker units (high flexibility) and two clusters of non-peaker units (low flexibility). The estimated ramp rates of non-peakers, which constitute half of the sample, display a low empirical flexibility, comparable to coal units. Non-peakers, predominantly owned by industry and municipal utilities, show limited response to low residual load and negative prices, generating on average 1.3 GWh during those hours. As the transition to renewables increases market variability, regulatory changes will be needed to unlock this flexibility potential. Y1 - 2025 U6 - https://doi.org/10.48550/arXiv.2504.16943 PB - arXiv ER - TY - RPRT A1 - Fusar Bassini, Chiara A1 - Xu, Alice Lixuan A1 - Sánchez Canales, Jorge A1 - Hirth, Lion A1 - Kaack, Lynn H. T1 - Flexibility of German gas-fired generation: evidence from clustering empirical operation N2 - A key input to energy models are assumptions about the flexibility of power generation units, i.e., how quickly and often they can start up. These assumptions are usually calibrated on the technical characteristics of the units, such as installed capacity or technology type. However, even if power generation units technically can dispatch flexibly, service obligations and market incentives may constrain their operation. Here, we cluster over 60% of German national gas generation (generation units of 100 MWp or above) based on their empirical flexibility. We process the hourly dispatch of sample units between 2019 and 2023 using a novel deep learning approach, that transforms time series into easy-to-cluster representations. We identify two clusters of peaker units and two clusters of non-peaker units, whose different empirical flexibility is quantified by cluster-level ramp rates. Non-peaker units, around half of the sample, are empirically less flexible than peakers, and make up for more than 83% of sample must-run generation. Regulatory changes addressing the low market responsiveness of non-peakers are needed to unlock their flexibility. Y1 - 2025 U6 - https://doi.org/10.48550/arXiv.2504.16943 PB - arXiv ER - TY - RPRT A1 - Tiedemann, Silvana A1 - Sgarlato, Raffaele A1 - Hirth, Lion T1 - Price elasticity of electricity demand: Using instrumental variable regressions to address endogeneity and autocorrelation of high-frequency time series N2 - This paper examines empirical methods for estimating the response of aggregated electricity demand to high-frequency price signals, the short-term elasticity of electricity demand. We investigate how the endogeneity of prices and the autocorrelation of the time series, which are particularly pronounced at hourly granularity, affect and distort common estimators. After developing a controlled test environment with synthetic data that replicate key statistical properties of electricity demand, we show that not only the ordinary least square (OLS) estimator is inconsistent (due to simultaneity), but so is a regular instrumental variable (IV) regression (due to autocorrelation). Using wind as an instrument, as it is commonly done, may result in an estimate of the demand elasticity that is inflated by an order of magnitude. We visualize the reason for the Thams bias using causal graphs and show that its magnitude depends on the autocorrelation of both the instrument, and the dependent variable. We further incorporate and adapt two extensions of the IV estimation, conditional IV and nuisance IV, which have recently been proposed by Thams et al. (2022). We show that these extensions can identify the true short-term elasticity in a synthetic setting and are thus particularly promising for future empirical research in this field. Y1 - 2023 U6 - https://doi.org/10.48550/arXiv.2306.12863 PB - arXiv ER -