TY - RPRT A1 - Tiedemann, Silvana A1 - Sanchez Canales, Jorge A1 - Schur, Felix A1 - Sgarlato, Raffaele A1 - Hirth, Lion A1 - Ruhnau, Oliver A1 - Peters, Jonas T1 - Identifying Elasticities in Autocorrelated Time Series Using Causal Graphs N2 - The price elasticity of demand can be estimated from observational data using instrumental variables (IV). However, naive IV estimators may be inconsistent in settings with autocorrelated time series. We argue that causal time graphs can simplify IV identification and help select consistent estimators. To do so, we propose to first model the equilibrium condition by an unobserved confounder, deriving a directed acyclic graph (DAG) while maintaining the assumption of a simultaneous determination of prices and quantities. We then exploit recent advances in graphical inference to derive valid IV estimators, including estimators that achieve consistency by simultaneously estimating nuisance effects. We further argue that observing significant differences between the estimates of presumably valid estimators can help to reject false model assumptions, thereby improving our understanding of underlying economic dynamics. We apply this approach to the German electricity market, estimating the price elasticity of demand on simulated and real-world data. The findings underscore the importance of accounting for structural autocorrelation in IV-based analysis. Y1 - 2024 U6 - https://doi.org/10.48550/arXiv.2409.15530 PB - arXiv ER - TY - RPRT A1 - Bucksteeg, Michael A1 - Wiedmann, Michael A1 - Pöstges, Arne A1 - Haller, Markus A1 - Böttger, Diana A1 - Ruhnau, Oliver A1 - Schmitz, Richard T1 - The transformation of integrated electricity and heat systems—Assessing mid-term policies using a model comparison approach N2 - The development of European power markets is highly influenced by integrated electricity and heat systems. Therefore, decarbonization policies for the electricity and heat sectors, as well as numerical models that are used to guide such policies, should consider cross-sectoral interdependencies. However, although many model-based policy assessments for the highly interconnected European electricity system exist, international studies that consider interactions with the heat sector are rare. In this contribution, we systematically study the potential benefits of integrated heat and power systems by conducting a model comparison experiment. Five large-scale market models covering electricity and heat supply were utilized to study the interactions between a rather simple coal replacement scenario and a more ambitious policy that supports decarbonization through power-to-heat. With a focus on flexibility provision, emissions reduction, and economic efficiency, although the models agree on the qualitative effects, there are considerable quantitative differences. For example, the estimated reductions in overall CO2 emissions range between 0.2 and 9.0 MtCO2/a for a coal replacement scenario and between 0.2 and 25.0 MtCO2/a for a power-to-heat scenario. Model differences can be attributed mainly to the level of detail of CHP modeling and the endogeneity of generation investments. Based on a detailed comparison of the modeling results, implications for modeling choices and political decisions are discussed. KW - Combined heat and power power-to-heat coal phase-out renewable energy energy system transformation electricity market modeling model comparison KW - Centre for Sustainability Y1 - 2021 UR - https://www.econstor.eu/handle/10419/242981 ER - TY - JOUR A1 - Hirth, Lion A1 - Khanna, Tarun M. A1 - Ruhnau, Oliver T1 - How aggregate electricity demand responds to hourly wholesale price fluctuations JF - Energy Economics N2 - Electricity needs to be consumed at the very moment of production, leading wholesale prices to fluctuate widely at (sub-)hourly time scales. This article investigates the response of aggregate electricity demand to such price variations. Using wind energy as an instrument, we estimate a significant and robust short-term price elasticity of about −0.05 in Germany and attribute this to industrial consumers. As the share of consumption that is exposed to real-time prices (currently less than 25%) expands, we expect the aggregated price elasticity to grow. Y1 - 2024 U6 - https://doi.org/10.1016/j.eneco.2024.107652 SN - 0140-9883 VL - 135 PB - Elsevier BV ER - 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 - 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 - RPRT A1 - Ruhnau, Oliver A1 - Muessel, Jarusch T1 - Update and extension of the When2Heat dataset N2 - The “When2Heat” dataset comprises synthetic national time series for heat demand and heat pumps’ coefficient of performance (COP) in hourly resolution. Heat demands for space and water heating are computed by combining gas standard load profiles with spatial temperature reanalysis data and population geodata. With this update, we extend the dataset to 28 European countries and the period from 2008 to 2019, including new, state-of-the-art data sources. For the geographical extension, we propose a novel approach, shifting established German heat demand curves based on country-specific heating thresholds to account for regional differences in thermal insulation and user behavior. Using the example of Italy, we illustrate the effect of shifting heat demand curves. The dataset, scripts, and input parameters are publicly available under an open-source license on the Open Power System Data platform. KW - Heat demand KW - Heat pumps KW - Coefficient of performance KW - Europe KW - Centre for Sustainability Y1 - 2022 UR - https://www.econstor.eu/handle/10419/249997 ER - TY - JOUR A1 - Ruhnau, Oliver T1 - How flexible electricity demand stabilizes wind and solar market values: the case of hydrogen electrolyzers JF - Applied Energy, Elsevier N2 - Wind and solar energy are often expected to fall victim to their own success: the higher their share in electricity production, the more their revenue on electricity markets (their “market value”) declines. While in conventional power systems, the market value may converge to zero, this study demonstrates that “green” hydrogen production, through adding electricity demand in low-price hours, can effectively and permanently halt the decline. With an analytical derivation, a Monte Carlo simulation, and a numerical electricity market model, I find that – due to flexible hydrogen production alone – market values across Europe likely converge above €19 ± 9 MWh-1 for solar energy and above €27 ± 8 MWh-1 for wind energy in 2050 (annual mean estimate ± standard deviation). This lower boundary is in the range of the projected levelized costs of renewables and has profound implications. Market-based renewables may hence be within reach. simulation, and a numerical electricity market model, I find that – due to flexible hydrogen production alone – market values across Europe likely converge above €19 ± 9 MWh-1 for solar energy and above €27 ± 8 MWh-1 for wind energy in 2050 (annual mean estimate ± standard deviation). This lower boundary is in the range of the projected levelized costs of renewables and has profound implications. Market-based renewables may hence be within reach. KW - renewable energy KW - hydrogen electrolysis KW - electricity market KW - electricity economics KW - integrated energy system KW - flexible electricity demand KW - Centre for Sustainability Y1 - 2022 U6 - https://doi.org/10.1016/j.apenergy.2021.118194 VL - 307 ER - TY - JOUR A1 - Ruhnau, Oliver A1 - Qvist, Staffan T1 - Storage requirements in a 100% renewable electricity system: Extreme events and inter-annual variability JF - Environmental Research Letters N2 - In the context of 100% renewable electricity systems, prolonged periods with persistently scarce supply from wind and solar resources have received increasing academic and political attention. This article explores how such scarcity periods relate to energy storage requirements. To this end, we contrast results from a time series analysis with those from a system cost optimization model, based on a German 100% renewable case study using 35 years of hourly time series data. While our time series analysis supports previous findings that periods with persistently scarce supply last no longer than two weeks, we find that the maximum energy deficit occurs over a much longer period of nine weeks. This is because multiple scarce periods can closely follow each other. When considering storage losses and charging limitations, the period defining storage requirements extends over as much as 12 weeks. For this longer period, the cost-optimal storage capacity is about three times larger compared to the energy deficit of the scarcest two weeks. Adding other sources of flexibility for the example of bioenergy, the duration of period that defines storage requirements lengthens to more than one year. When optimizing system costs based on single years rather than a multi-year time series, we find substantial inter-annual variation in storage requirements with the most extreme year needing more than twice as much storage as the average year. We conclude that focusing on short-duration extreme events or single years can lead to an underestimation of storage requirements and costs of a 100 % renewable system. KW - Renewable energy Wind and solar power Inter-annual variability Low-wind events Dunkelflaute Electricity system Energy storage Hydrogen Batteries KW - Centre for Sustainability Y1 - 2022 U6 - https://doi.org/10.1088/1748-9326/ac4dc8 PB - IOP Publishing ER -