• Energy Research

Germany has experienced rapid growth in onshore wind capacities over the past two decades. Substantial capacities of offshore wind turbines have been added since 2013. On a local, highly-resolved level, this analysis evaluated if differences in wind speed forecast errors exist for offshore and onshore locations regarding magnitude and variation. A model based on the Extra Trees algorithm is proposed and found to be a viable method to transform local wind speeds and capacities into aggregated wind energy feed-in. This model was used to analyze if offshore and onshore wind power expansion lead to different distributions of day-ahead wind energy forecast errors in Germany. The Extra Trees model results indicate that offshore wind capacity expansion entails an energy forecast error distribution with more frequent medium to high deviations, stemming from larger and more variable wind speed deviations of offshore locations combined with greater geographical concentration of offshore wind turbines and their exposure to high-wind oceanic conditions. The energy forecast error distribution of onshore expansion, however, shows heavier tails and consequently more frequent extreme deviations. The analysis suggests that this can be rooted in the simultaneous over- or underestimation of wind speeds at many onshore locations.

Abstract The trading of electricity across zones relies on cross-border capacities, provided by transmission system operators. The target design of the European Union for capacity calculations is flow-based market coupling, a method that provides trading domains while taking into account grid restrictions. Flow-based market coupling heavily relies on Generation Shift Keys, an essential predictive parameter, translating zonal balance changes that originate from market coupling into nodal injections and consequent line flow changes. This analysis quantifies the effect of different Generation Shift Key strategies on the market coupling domains and individual network elements. A strategy entails suppositions regarding which generating units partake in market changes and to what extent. For this, a novel method for base case computations is proposed that relies on matching historical reference flows of network elements. The results show that different strategies substantially alter the shape and size of flow-based market coupling domains and have a statistically significant impact on individual network elements. For many lines, the average line flow sensitivity to market changes differs between 1% and 5% across strategies and up to 10% for a few lines. Furthermore, the analysis details how the n-1 security criterion influences the composition of domain constraints and to what extent network elements are affected by it. Particularly with regard to the planned geographical expansion of flow-based market coupling and changing regulatory demands for transmission system operators, this work attests to the importance of developing accurate and transparent flow-based market coupling parameters and model-based representations.

In 2019, CO(2) emissions in Germany dropped by 40 Mt compared to the previous year, of which a major share was realized in the power sector. Many factors, such as carbon and fuel prices as well as the capacity expansion of renewable energy sources, influence Germany’s CO(2) emissions. This ex-post regression analysis of the German power market from 2016 to 2019 investigates the contribution of each factor to the CO(2) emissions reduction. The results suggest that short-term market developments for gas prices are responsible for a major share of 2019’s CO(2) emissions reduction when compared to 2018 levels. The sustainable transition of the power system, in form of adequate CO(2) prices and additional renewable energy capacities, becomes the dominating factor when analyzing the CO(2) emissions reductions over the longer time span from 2016 to 2019. Exogenous factors, such as increasing gas prices, could raise Germany’s carbon emissions again. This reversion of carbon emissions reductions can be avoided if the overall-society compromise on the coal phase-out is realized sooner than later.

This paper develops a novel two-step method to establish Generation Shift Keys (GSKs) on any desired aggregation level. Estimates are derived from econometric models, utilizing regression coefficients to measure how net position deviations affect power outputs, isolated from the influence of renewable energy generation and load. This enables GSK estimations based on actual common dispatch decisions, decoupled from fixed generating unit parameters and merit-order assumptions. The method's first step, the Generation Share Key (GShK), is applied to the four German TSOs. The obtained results are robust, suggesting the implementation for other countries with sufficiently stable markets. The second step is conducted for the generating units of 50Hertz's control region. For most analyzed units, size and variability of the estimated GSK values are appropriate regarding capacity and primary energy source. Also, the analysis discusses possibilities to account for the susceptibility of GShKs and GSKs to prevailing market situations.

Abstract Within flow-based market coupling, the EU's preferred method for calculating cross-border trading capacities, recent regulatory changes stipulate minimum trading capacities, so-called minRAMs which have to be provided to electricity markets. Effectively, high predicted flows on considered electricity grid elements have to be reduced to reserve a minimum of the elements' capacities for cross-zonal trading. This analysis investigates if the adjustments made to meet this criterion, in the form of augmented trading domains, lead to higher amounts of curative congestion management. To quantify the effect of increasing minRAMs on overall welfare, the markets and grids of Central Western Europe are analyzed during two representative weeks of 2016. The results show the increasing market coupling welfare is more than offset by rising congestion management costs, leading to net welfare losses. In the best case, the generation plus congestion management costs within Central Western Europe rise by 7.25% when increasing the minRAMs from the current 20%–45% and a minRAM of 70% is 6.28% more expensive compared to a minRAM of 20%. The analysis derives policy recommendations for implementing the minRAM stipulation, with a particular focus on a cost-minimizing selection of generation shift keys, in general as well as situation-dependent terms.

Covid-19 affects the personal lives of millions and led to an economic crisis. Changed behavioral patterns and a reduction of industrial activity result in a reduction in power demand, and thus Covid-19 impacts the power systems around the world. Bottom-up mapping of the effect of Covid-19 on the energy demand is challenging, if not impossible. In order to analyze the impact of the pandemic on power demand, we instead propose a simplified approach based on an econometric analysis that quantifies the country-wide load reduction of Covid-19, using the number of active cases as well as the specific lockdown period as proxies. The time span covered is from 1 January 2016 to 31 August 2020. This long time span allows us to investigate the effect of Covid-19 on the power demand. We find that in Germany (DE) and Great Britain (GB) the power demand is reduced by about 1–1.7 MW per case, while in France the demand increased by 1 MW per case during times outside of the lockdown. On the other hand, in France the lockdown itself has a much higher load reduction effect in France than in GB and DE. Based on the elasticity of power demand regarding Covid-19 cases, we calculate the impact of Covid-19 on the power prices through reduced loads. We find that Covid-19 reduced power prices by 3 to 6 EUR per MWh. The effect of Covid-19 on carbon emissions in the power sector is likely to be small. In Germany, the country with the highest absolute level, emissions in the power sector were reduced by approximately 2% (4 Mio. t CO2).

Germany has experienced rapid growth in its renewable electricity generation capacity in the past fifteen years. This development has been accompanied by a drop in wholesale electricity prices and significant net export surpluses. This situation has given rise to discussions in policy circles concerning the drivers behind these dynamics. The paper at hand empirically analyzes historical cross-border commercial flows (CBCF) of electricity from Germany by applying a Ridge Regression model to parse the effects of the growing shares of renewable energy capacity on the commercial electricity exchange between 2012 and 2016. In case of PV, the fraction of PV generation (marginal effect of PV on export) that is exported correlates positively with the level of PV generation. However, the marginal effect of wind on export is negatively correlated with the level of wind generation. A possible explanation for this finding as it relates to wind feed-in could involve the high degree to which the grid is constrained at times of high wind penetration.

Abstract European electricity markets are zonal markets, a set-up that naturally entails an imperfect representation of intra-zonal congestion patterns that may limit cross-border trade. The method of flow-based market coupling aims to reflect limitations to cross-border trade by incorporating intra- and interzonal grid elements within the setting of zonal pricing through monitoring the flows on these critical network elements caused by inter-zonal trade. A major challenge for grid operators is the selection of critical network elements, essentially deciding which grid elements send congestion signals and trade limitations to the markets. Our main research question is: Can insights on hypothetically re-configured market zones help to improve the selection of critical network elements and lead to cost reductions without effectively changing the market zone setting? Using a flow-based market coupling optimization model based on a 3-zone test network, we propose a hypothetical nodal price-based market zone re-configuration to identify congestion signals and derive an improved set of critical network elements. We find that around 90% of the cost reductions from this market zone re-configuration can be maintained when the critical network elements, obtained from the re-configured market zones, are used in the original 3-zone setting. This is a strong indication that, both in reality as well as model-based research of flow-based market coupling, the selection of critical network elements should be based on expected congestion patterns. The proposed approach can constitute a helpful addition to static and assumption-based selection criteria for critical network elements that are currently used by European grid operators.