Modeling flexibility in energy systems : comparison of power sector models based on simplified test cases

Model-based scenario analyses of future energy systems often come to deviating results and conclusions when different models are used. This may be caused by heterogeneous input data and by inherent differences in model formulations. The representation of technologies for the conversion, storage, use, and transport of energy is usually stylized in comprehensive system models in order to limit the size of the mathematical problem, and may substantially differ between models. This paper presents a systematic comparison of nine power sector models with sector coupling. We analyze the impact of differences in the representation of technologies, optimization approaches, and further model features on model outcomes. The comparison uses fully harmonized input data and highly simplified system configurations to isolate and quantify model-specific effects. We identify structural differences in terms of the optimization approach between the models. Furthermore, we find substantial differences in technology modeling primarily for battery electric vehicles, reservoir hydro power, power transmission, and demand response. These depend largely on the specific focus of the models. In model analyses where these technologies are a relevant factor, it is therefore important to be aware of potential effects of the chosen modeling approach. For the detailed analysis of the effect of individual differences in technology modeling and model features, the chosen approach of highly simplified test cases is suitable, as it allows to isolate the effects of model-specific differences on results. However, it strongly limits the model's degrees of freedom, which reduces its suitability for the evaluation of fundamentally different modeling approaches

Impacts of power sector model features on optimal capacity expansion: a comparative study

The transition towards decarbonized energy systems requires the expansion of renewable and flexibility technologies in power sectors. Many powerful tools exist to find optimal capacity expansion. In a stylized comparison of six models, we evaluate the capacity expansion results of basic power sector technologies. The technologies under investigation include base- and peak-load power plants, electricity storage, and transmission. We define four highly simplified and harmonized test cases that focus on the expansion of only one or two specific technologies to isolate their effects on model results. We find that deviating assumptions on limited availability factors of technologies cause technology-specific deviations between optimal capacity expansion in models in almost all test cases. Fixed energy-to-power-ratios of storage can entirely change model optimal expansion outcomes, especially shifting the ratio between short- and long-duration storage. Fixed initial and end storage levels can impact the seasonal use of long-duration storage. Models with a pre-ordered dispatch structure substantially deviate from linear optimization models, as missing foresight and limited flexibility can lead to higher capacity investments. A simplified net transfer capacity approach underestimates the need for grid infrastructure compared to a more detailed direct current load flow approach. We further find deviations in model results of optimal storage and transmission capacity expansion between regions and link them to variable renewable energy generation and demand characteristics. We expect that the general effects identified in our stylized setting also hold in more detailed model applications, although they may be less visible there

Verbundvorhaben FlexMex: Modellexperiment zur zeitlich und räumlich hoch aufgelösten Untersuchung des zukünftigen Lastausgleichs im Stromsystem

Das Projekt FlexMex konzentrierte sich auf einen Modellvergleich zur Untersuchung der Nutzung von Flexibilitätsoptionen zum Ausgleich der Stromerzeugung aus variablen erneuerbaren Energien. Die zentrale Frage war, wie unterschiedliche Optimierungs- und Technologiemodellie-rungsansätze den Anlageneinsatz in stündlich aufgelösten Stromsektormodellen beeinflussen. Darüber hinaus wurde der Einfluss unterschied-licher Modellumfänge auf den Einsatz von Flexibilitätsoptionen untersucht. Um datenbedingte von modellbedingten Unterschieden in den Ergebnissen konsequent zu trennen, wurden die Eingangsdaten der neun beteiligten Modelle vollständig harmonisiert. Die Anwendung der Modelle wurde dann in zwei Hauptexperimente unterteilt. Im ersten Experiment wurden auf der Grundlage einer umfassenden qualitativen Analyse der Modelle und ihrer Unterschiede einzelne Flexibilitätsoptionen untersucht. Anhand stark reduzierter Testfälle konnten modellspe-zifische Effekte isoliert und quantifiziert werden. Ergänzende Analysen befassten sich mit dem modellendogenen Ausbau von Stromspeichern, Stromnetzen und regelbaren Kraftwerken. Aufbauend auf den technologiespezifischen Analysen wurden im zweiten Modellexperiment komplexere Szenarien betrachtet. Dort wurden sechzehn stilisierte Szenarien betrachtet, die sich in Versorgungsanteil erneuerbarer Ener-gien, Technologieumfang und Optimierungsumfang unterscheiden. Trotz der hohen Anzahl der Modelle und der interagierenden Modellun-terschiede können die Ergebnisabweichungen auf die Modelleigenschaften zurückgeführt werden. Das Experiment zeigt, dass Unterschiede im Modellierungsansatz und der Technologieabbildung zu vergleichsweise geringen Abweichungen führen, während ein heterogener Modell-umfang einen deutlich größeren Einfluss haben kann. Zusammenfassend können die Ergebnisse des FlexMex-Projekts ein besseres Verständ-nis für die Wirkung unterschiedlicher Modellierungsansätze liefern und damit zur Interpretation von Modellergebnissen beitragen

Investigation of optimal transformation pathways towards 2050 for the successful implementation of a sustainable reduction of carbon emissions from power generation

Today's energy system is largely based on the use of fossil energy sources, while clean, decentralised power generation have been gaining in importance as they became competitive in the last decade. Through increased integration of renewable energies and flexibility options for spatial and temporal balancing global reductions of carbon emissions are realisable to address raising global temperatures due to greenhouse gasses. The objectives of this thesis are to develop a computer optimisation toolbox for a flexible model parametrisation, which allows studying the long-term behaviour and development pathways of the power system, and to calculate different scenarios representing potential political frameworks or conditions. The tool that is developed, called GENESYS-2, will implement new algorithmic approaches in order to address the high complexity of the calculations required for the investigation of several decades with high temporal resolution of one hour. The model is parametrised for a European scenario with technical system component properties, cost and settings for political boundaries. Different sensitivities of the model are investigated to demonstrate how the concepts of the different available techno-economic parameters work and how they affect the properties of the model composition and resulting pathways. The investigation, furthermore, leads to the conclusion, that further integration of renewable sources is more economical than conventional generation, especially, if political decarbonisation targets need to be reached. The development of additional components like storage and grids to provide the necessary system flexibility, in the long run, need to become an essential part of investment efforts

Representative, empirical, real-world charging station usage characteristics and data in Germany

Electric vehicle (EV) charging infrastructure is a new type of consumer in the power grid. Oftentimes,theoretical models have to be used to understand the impact of these new assets since little empiricaldata of charging station usage is available. This paper aims to increase understanding of charging stationusage by providing empirical data collected from 26,951 charging station connectors in Germany. Wedemonstrate that currently the usage intensity of stations is overall between 15% and 20% and thereforerelatively low, but depends strongly on weekday and hour of the day. Fast-chargers are generallyoccupied less time compared to slower chargers while each charging event also takes significantly lesstime. A key challenge in optimizing real-world asset usage are EVs which are parked significantly longerat charging stations than the actual charging process takes. We show that an unexpectedly high share ofcharging events requires between 8 and 10 h indicating that people park their EVs before going to workand then picking them up after they finished working