@techreport{XuSanchezCanalesFusarBassinietal., type = {Working Paper}, author = {Xu, Alice Lixuan and S{\´a}nchez Canales, Jorge and Fusar Bassini, Chiara and Kaack, Lynn H. and Hirth, Lion}, title = {Market power abuse in wholesale electricity markets}, publisher = {arXiv}, doi = {10.48550/arXiv.2506.03808}, pages = {39}, abstract = {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.}, language = {en} } @techreport{FusarBassiniXuSanchezCanalesetal., type = {Working Paper}, author = {Fusar Bassini, Chiara and Xu, Alice Lixuan and S{\´a}nchez Canales, Jorge and Hirth, Lion and Kaack, Lynn}, title = {Revealing the empirical flexibility of gas units through deep clustering}, publisher = {arXiv}, doi = {10.48550/arXiv.2504.16943}, pages = {19}, abstract = {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.}, language = {en} } @techreport{FusarBassiniXuSanchezCanalesetal., type = {Working Paper}, author = {Fusar Bassini, Chiara and Xu, Alice Lixuan and S{\´a}nchez Canales, Jorge and Hirth, Lion and Kaack, Lynn H.}, title = {Flexibility of German gas-fired generation: evidence from clustering empirical operation}, publisher = {arXiv}, doi = {10.48550/arXiv.2504.16943}, pages = {29}, abstract = {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.}, language = {en} } @techreport{TiedemannSgarlatoHirth, type = {Working Paper}, author = {Tiedemann, Silvana and Sgarlato, Raffaele and Hirth, Lion}, title = {Price elasticity of electricity demand: Using instrumental variable regressions to address endogeneity and autocorrelation of high-frequency time series}, publisher = {arXiv}, doi = {10.48550/arXiv.2306.12863}, pages = {25}, abstract = {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.}, language = {en} } @techreport{SanchezCanalesXuFusarBassinietal., type = {Working Paper}, author = {S{\´a}nchez Canales, Jorge and Xu, Alice Lixuan and Fusar Bassini, Chiara and Kaack, Lynn H. and Hirth, Lion}, title = {An empirical estimate of the electricity supply curve from market outcomes}, publisher = {arXiv}, doi = {10.48550/arXiv.2511.23068}, pages = {33}, abstract = {Researchers and electricity sector practitioners frequently require the supply curve of electricity markets and the price elasticity of supply for purposes such as price forecasting, policy analyses or market power assessment. It is common practice to construct supply curves from engineering data such as installed capacity and fuel prices. In this study, we propose a data-driven methodology to estimate the supply curve of electricity market empirically, i.e. from observed prices and quantities without further modeling assumptions. Due to the massive swings in fuel prices during the European energy crisis, a central task is detecting periods of stable supply curves. To this end, we implement two alternative clustering methods, one based on the fundamental drivers of electricity supply and the other directly on observed market outcomes. We apply our methods to the German electricity market between 2019 and 2024. We find that both approaches identify almost identical regimes shifts, supporting the idea of stable supply regimes stemming from stable drivers. Supply conditions are often stable for extended periods, but evolved rapidly during the energy crisis, triggering a rapid succession of regimes. Fuel prices were the dominant drivers of regime shifts, while conventional plant availability and the nuclear phase-out play a comparatively minor role. Our approach produces empirical supply curves suitable for causal inference and counterfactual analysis of market outcomes.}, language = {en} } @techreport{RuhnauStieweMuesseletal., type = {Working Paper}, author = {Ruhnau, Oliver and Stiewe, Clemens and Muessel, Jarusch and Hirth, Lion}, title = {Gas demand in times of crisis. The response of German households and industry to the 2021/22 energy crisis}, pages = {8}, abstract = {Europe is in the midst of the most severe energy crisis in a generation, at the core of which is the continuously plummeting supply of Russian natural gas. With alternative supply options being limited, natural gas prices have surged. This paper empirically estimates the response of natural gas demand to the price increase, using data from Germany—the so far largest consumer of Russian natural gas. We identify the crisis response of small and large consumers separately, controlling for temperature, gas-fired power generation, and economic activity. For small consumers, including mostly households, we find a substantial demand reduction of 6\% from March onwards—most likely due to political and ethical considerations after the start of Russia's invasion of Ukraine. For industrial consumers, demand reductions started much earlier in August 2021, when wholesale prices for natural gas started to surge, with an average reduction of 11\%. We conclude that voluntary industrial demand response has played a significant role in coping with the energy crisis so far.}, language = {en} } @techreport{TiedemannStieweKratzkeetal., type = {Working Paper}, author = {Tiedemann, Silvana and Stiewe, Clemens and Kratzke, Corinna and Hirth, Lion and Jentsch, Mareike and Damm, Nicolai and Gerhardt, Norman and Pape, Carsten}, title = {Gebotszonenteilung: Auswirkungen auf den Marktwert der Erneuerbaren Energien im Jahr 2030}, publisher = {Kopernikus-Projekt Ariadne}, address = {Potsdam}, doi = {10.48485/pik.2024.002}, pages = {49}, abstract = {Eine Teilung des deutschen Marktgebietes w{\"u}rde die Marktwerte erneuerbarer Energien beeinflussen. Wind und Photovoltaik (PV) im S{\"u}den Deutschlands w{\"u}rden an Wert gewinnen, w{\"a}hrend Erneuerbare im Norden Erl{\"o}se einb{\"u}ßen w{\"u}rden. Bei einer auch zuk{\"u}nftig st{\"a}rkeren Konzentration von erneuerbaren Energien im Norden bedeutet dies insgesamt einen h{\"o}heren F{\"o}rderbedarf f{\"u}r PV - Wind w{\"a}re trotz niedriger Marktwerte in den meisten Regionen wirtschaftlich. Wenn eine regionale Steuerung erreicht werden soll, m{\"u}sste die auszuzahlende F{\"o}rderung f{\"u}r neue PV-Anlagen anhand des zonen{\"u}bergreifenden Referenzmarktwertes berechnet werden. Durchschnittliche B{\"o}rsenstrompreise w{\"u}rden durch eine Gebotszonenteilung im S{\"u}den Deutschlands leicht angehoben und im Norden gesenkt, die Effekte auf Endkundenpreise und damit verbundene Anreize zur Standortwahl von Industrieunternehmen sind allerdings als gering einzusch{\"a}tzen.}, language = {de} } @techreport{StieweXuEickeetal., type = {Working Paper}, author = {Stiewe, Clemens and Xu, Alice Lixuan and Eicke, Anselm and Hirth, Lion}, title = {Cross-border cannibalization: Spillover effects of wind and solar energy on interconnected European electricity markets}, publisher = {arXiv}, doi = {10.48550/arXiv.2405.17166}, pages = {25}, abstract = {The average revenue, or market value, of wind and solar energy tends to fall with increasing market shares, as is now evident across European electricity markets. At the same time, these markets have become more interconnected. In this paper, we empirically study the multiple cross-border effects on the value of renewable energy: on one hand, interconnection is a flexibility resource that allows to export energy when it is locally abundant, benefitting renewables. On the other hand, wind and solar radiation are correlated across space, so neighboring supply adds to the local one to depress domestic prices. We estimate both effects, using spatial panel regression on electricity market data from 2015 to 2023 from 30 European bidding zones. We find that domestic wind and solar value is not only depressed by domestic, but also by neighboring renewables expansion. The better interconnected a market is, the smaller the effect of domestic but the larger the effect of neighboring renewables. While wind value is stabilized by interconnection, solar value is not. If wind market share increases both at home and in neighboring markets by one percentage point, the value factor of wind energy is reduced by just above 1 percentage points. For solar, this number is almost 4 percentage points.}, language = {en} } @techreport{HirthTiedemannSchill, type = {Working Paper}, author = {Hirth, Lion and Tiedemann, Silvana and Schill, Wolf-Peter}, title = {Was sind eigentlich Netzentgelte?}, publisher = {Kopernikus-Projekt Ariadne}, address = {Potsdam}, doi = {10.48485/pik.2024.020}, pages = {8}, language = {de} }