• Energy Research

Abstract The transparency and open availability of energy system models and their input data are of particular importance due to their increasing complexity and policy relevance. In recent years, a large number of model-based scenario analyses have been carried out. These analyses are based on diverse model approaches and lead to a rather broad range of results, which due to different data structures and mathematical approaches are hardly directly comparable. In this paper, detailed and harmonized scenario input parameters are the basis of a systematic model experiment including four electricity system models. In the following, the different model approaches are classified and their respective results are discussed transparently. Consequently, differences in results can be interlinked directly with model properties. The results are compared focusing on a selection of output parameters, such as investment and dispatch decisions in flexible power plants, storage dispatch, wholesale electricity prices, CO2 emissions and generation adequacy in hours with critical supply situations in Germany until 2030. Differences in the results are traced back to conceptual differences as the models can be distinguished not only with regard to their mathematical approaches, but also to their level of detail. Results indicate that next to the differences of the mathematical approaches (i.e., linear optimization vs. agent-based simulation), the myopic foresight perspective (e.g., rolling planning algorithm with 24- and 36-hours loops vs. perfect foresight in a closed loop for one year) are decisive for the range of obtained results.

In diesem Beitrag werden die Wechselwirkungen zwischen dem schweizerischen Strommarkt und denen der Nachbarländer mit Hilfe von Korrelations- und Regressionsanalysen untersucht. Der Fokus wird dabei auf den Einfluss von fundamentalen Faktoren, die aus den Nachbarländern resultieren, auf den schweizerischen Strompreis gelegt. Die Analysen zeigen, dass der schweizerische Strompreis im Sommer stärker mit dem deutschen Strompreis korreliert und die Auswirkungen der deutschen erneuerbaren Energien im Sommer eher signifikant sind. Die Studie zeigt jedoch auch, dass der Einfluss der Gaspreise und der Stromlast einen deutlich stärkeren Einfluss auf die Preise haben. Insbesondere eine hohe Last in der Schweiz und in den Nachbarländer Frankreich und Italien treiben die schweizerischen Preise im Winter in die Höhe, während in den letzten vier Jahren die Strompreise im Durchschnitt aufgrund der gefallenen Brennstoff- und CO2-Preise stark gefallen sind.

In this article, cross-border effects of different market design options are analyzed using Switzerland, which is strongly interconnected to larger neighboring markets, as a case study. An investigation is conducted with an agent-based model where in one scenario, all market designs are represented according to the current legislation, and in another, energy-only markets (EOM) are assumed in all considered countries. The results show that wholesale electricity prices are highly dependent on the chosen market design and in the annual average are up to 27% higher in the EOM scenario. Due to expected larger interconnector capacities, this increase is evident in all simulated markets. Furthermore, the results indicate that the planned market design changes in the neighboring countries decrease investments in Switzerland. However, generation adequacy is still guaranteed due to the high Swiss hydropower storage capacity. Our results suggest that, under the current circumstances, a domestic mechanism in Switzerland is not required.

In liberalized energy markets, the issue of generation adequacy gains more and more in importance. Especially demand response is regarded as a crucial measure to handle supply and demand imbalances caused by inflexible renewable energy resources (RES) power production. However, the influence of demand response on wholesale electricity prices has not been sufficiently analyzed up to now.

To estimate the (future) impact of hydrogen generation on the electricity market, it is necessary to adequately consider electrolyzers’ flexibility in models to evaluate the integration. Therefore, a cost-minimizing linear optimization problem for determining the dispatch of electrolyzers is integrated into an existing agent-based electricity market simulation model. In a case study with two scenarios considering most western European countries, effects on the wholesale electricity spot markets are investigated. Scenario one considers locally demanded and produced hydrogen. Scenario two assumes one single internal hydrogen market to cover all modeled markets.The results indicate that average wholesale electricity prices and renewable curtailments differ only slightly between scenarios. However, the cost of dispatching electrolyzers is substantially lower in one single internal hydrogen market. Additionally, the utilization of electrolyzers between markets is more evenly distributed. Hydrogen is produced mainly in markets with substantial wind potentials, such as Denmark and Great Britain.

The energy transition fosters a dynamic landscape marked by renewable energy, electrification, and complex interactions among actors and technologies. Employing model experiments and comparisons shows promise for exploring these connections and enhancing model clarity and precision. This study adopts a multi-model approach, integrating a model comparison to probe how the electrification of demand-side sectors and strategic load shifts of battery electric vehicles and heat pumps might impact Germany's generation adequacy by 2030. Specific demand models from the transport and heating sectors and a future load structure projection model are interlinked with three electricity system models. The comparative analysis of the three electricity system models unveils discrepancies in dispatch decisions for power plants, flexibility options' load shifts, and their effects on generation adequacy, directly tied to model attributes. The comparison underscores methodological variations (linear optimization versus agent-based simulation, myopic foresight versus perfect foresight) as pivotal, emphasizing the significance of considering load change and start-up costs for power plants. The results show that with optimized load shifting by electric vehicles and heat pumps, the adequacy of power generation is less strained despite increased electricity demand. Moreover, load shifts mitigate curtailment of renewables and consumers, reducing carbon emissions by lowering conventional power generation.

Growing numbers of plug-in electric vehicles in Europe will have an increasing impact on the electricity system. Using the agent-based simulation model PowerACE for ten electricity markets in Central Europe, we analyze how different charging strategies impact price levels and production- as well as consumption-based carbon emissions in France and Germany. The applied smart charging strategies consider spot market prices and/or real-time production from renewable energy sources. While total European carbon emissions do not change significantly in response to the charging strategy due to the comparatively small energy consumption of the electric vehicle fleet, our results show that all smart charging strategies reduce price levels on the spot market and lower total curtailment of renewables. Here, charging processes optimized according to hourly prices have the strongest effect. Furthermore, smart charging strategies reduce electricity purchasing costs for aggregators by about 10% compared to uncontrolled charging. In addition, the strategies allow aggregators to communicate near-zero allocated emissions for charging vehicles. An aggregator's charging strategy expanding classic electricity cost minimization by limiting total national PEV demand to 10% of available electricity production from renewable energy sources leads to the most favorable results in both metrics, purchasing costs and allocated emissions. Finally, aggregators and plug-in electric vehicle owners would benefit from the availability of national, real-time Guarantees of Origin and the respective scarcity signals for renewable production.

In 2020, the European Commission published a hydrogen strategy announcing different policy measures to support the construction of a European hydrogen infrastructure. Hereby, a target of 40 GW installed electrolyser capacity within the EU by 2030 was set, which will cause a significant electricity demand and will link together hydrogen and electricity markets. Therefore, state-of-the-art power modelling must include both electricity and hydrogen. This work proposes a novel approach to integrate hydrogen in existing long-term optimization electricity market dispatch models. A comprehensive modification of the optimization framework is not necessary as the hydrogen market can be modelled in analogy to the electricity market. This is done by implementing hydrogen markets as additional zones within the model with their own hydrogen demands and production. Thus, a hydrogen layer next to the existing electricity layer is created. Next to the dispatch model, hydrogen generation technologies are integrated into a system dynamics investment module, which is interlinked with the optimization model and determines market-driven investments in power plants based on the NPV. As a support scheme for electrolysers, carbon contracts for difference are implemented. Further, a detailed analysis of the German hydrogen and electricity markets is carried out. The analysis shows that renewable energy sources and electrolysers are complementary technologies, which mutually increase their profitability. The model indicates that higher electricity demands caused by electrolysers will not lead to higher electricity prices but reduce the price volatility.