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The expected increase in battery electric vehicles poses both, opportunities and risks for the decarbonisation of future power systems. While electric mobility may technically serve as a source of flexibility, it increases the overall power demand and may as well increase the demand for power in peak load hours. While electric mobility in national and continental scale energy system optimization is often treated in an aggregated fleet, user behaviour and charging decisions play a crucial role in the availability of vehicles' batteries for balancing electric load and renewable energy feed-in. Michaelis, Gnann & Klingler (2018) find that reduction of peak load and RE surplus electricity stemming from plug-in vehicles in Germany may be as high as 2.2 GW and 1.8 TWh respectively for 2030. However, they assume constant charging stations' power of 3.7 kW that seem conservative. Also, the authors don't explicitly describe to what effect user behaviour limits vehicle charging. By linking the modular energy system optimization model REMix with the vehicle stock model VECTOR21 and the charging decision simulation tool CURRENT, we aim to determine a more realistic demand response potential for future electric vehicles compared to previous studies. All three models are developed at the German Aerospace Center (DLR) and have been applied and validated in different project contexts. We for the first time integrate hourly profiles determined by individual charging decisions as input for an energy system optimization model. We determine the reduction potential of peak load, renewable energy (RE) curtailment as well as RE capacity expansion for the different cases of controlled charging versus uncontrolled charging for Germany for 2030. Thus, we provide both methodological and quantitative insights into the effects of coupling power and transport sector that are of value to the scientific discussion.

Newly industrialized countries face major challenges to comply with the Paris treaty targets as economic growth and prosperity lead to increasing energy demand. Our paper analyses technological and structural options in terms of energy efficiency and renewable energies for a massive reduction of energy-related CO2 emissions in Latin America. Brazil and Mexico share similar growth prospects but differ significantly with respect to renewable energy potentials. We identify, how this leads to different transformation pathways. By applying and energy system balancing model we develop normative energy system transformation scenarios across the heating, power, and mobility sectors, including their potential interactions. The normative scenarios rely on three basic strategies for both countries: (1) strong exploitation of efficiency potentials, (2) tapping the renewable energy potentials, and (3) sector coupling and electrification of heat supply and transport. Despite economic growth, significant CO2 emission reductions could be achieved in Brazil from 440 Gt/a (2.2 t/cap) in 2012 to 0.4 Gt (2 kg/cap) in 2050 and in Mexico from 400 Gt/a (3.3 t/cap) to 80 Gt (0.5 t/cap). Our study shows the gap between existing policy and scenarios and our strategies, which provide an economically feasible way to comply with the Paris treaty targets.

This paper presents a methodology for the development of normative energy scenarios. The focus is on cross-sectoral transformation pathways towards a completely renewable energy supply. By using the REMix energy model, which is temporal and spatially highly resolved, the least-cost power supply structure is assessed. The model also calculates additional storage and grid capacity necessary for the target year 2050. By analyzing the interactions of different technologies and sectors we provide a basis for the backcasting of a transformation pathway. This is carried out by a simulation model within the MESAP-PlaNet environment, covering the heat, transport & power sectors. We present and compare feasible transformation pathways towards a 100% renewable energy supply for two case studies, the Canary Islands and Brazil.

State-of-the-art energy system models include a comprehensive representation of energy sectors and their associated technologies while including high resolution spatial and temporal data. This complexity is increased further by technologies linking the system along temporal, spatial and sectoral dimensions such as electrical energy storages, transmission grids or combine heat and power plants. One of the downsides of the increasing detail in optimising energy system models is the necessary time to solve the model. The BEAM-ME project addresses the need for efficient solution strategies for the increasing complexity of energy system models and. The project is funded by the German Federal Ministry of Economic Affairs and Energy and brings together researchers from the fields of energy system analysis, mathematics, operations research and informatics. The goal of the project is to develop technical and conceptual strategies for every step of the solution process. This the formulation of the energy system model, improving the solvers and utilising the resources of high performance computing. This talk provides an overview of the challenges in adapting the formulation of energy systems in order to utilise specialised solvers which efficiently exploit the underlying block structures. This requires energy system modellers to annotate their models in order to communicate which parts of the model should be solved in parallel while still maintaining the ability to achieve a global optimum solution. Finally, first insights of current results are discussed and an outlook on subsequent steps is given.

Energy systems based on renewable resources are characterized by a high number of decentralized components as well as by an increasing importance of storage, grid, and demand response. State-of-the-art energy system models reflect this growing complexity by combining a comprehensive representation of energy sectors and technologies with a high spatial and temporal resolution. However, such high level of detail is typically associated with long solving times of the models. The reduction of the latter is urgently required and the need for guidelines for a reasonable balance between degree of detail and solution time is pressing. The BEAM-ME project addresses these questions by improved computing power and efficiency in energy systems modelling. The German Aerospace Center is the principal investigator on the modelling side, while the project gathers various partners with complementary expertise in the fields of optimization algorithms, high performance computing, and application development. This talk provides an overview and evaluation of conceptual and technical strategies identified so far to reduce the model solution time of the REMix energy system model. Moreover, an insight in the implementation and assessment of selected speed-up strategies is provided. Finally, conclusions from the first project results are drawn and an outlook on the subsequent works is given.

This work addresses the role of an enhanced integration of the power, heat and transport sectors in future energy supply systems with high shares of intermittent renewable power generation. Such integration is realized by technological linkages between the sectors, e.g. through combined heat and power (CHP) generation, electric heat pumps and electric vehicles. The analysis is focused on their application in Germany, and relies on a comprehensive and multi-step modelling approach.

Eine stärkere Verknüpfung von Strom-, Wärme-, Verkehrs- und Gassektor kann einen wesentlichen Beitrag zum Gelingen der Energiewende leisten. So können beispielsweise durch ein gesteuertes Laden von Elektrofahrzeugen, sowie einen optimierten Betrieb von Wärmepumpen und Kraft-Wärme-Kopplungs-Anlagen der Bedarf nach regelbaren Kraftwerken gesenkt, und Erzeugungsspitzen aus Windkraft- und Photovoltaikanlagen in höherem Maße genutzt werden. Im Zentrum des Vortrags steht die Analyse des wirtschaftlichen Potenzials verschiedener Sektorenkopplungstechnologien in einem überwiegend auf fluktuierenden Quellen basierenden Energieversorgungssystem in Deutschland. Die Untersuchungen stützen sich auf die Anwendung des DLR-Energiesystemmodells REMix, und behandeln auch die Frage, wie die Sektorenkopplung mit anderen Technologieoptionen, z.B. einem erweiterten Stromnetzausbau und dem Import regelbaren erneuerbaren Stroms, wechselwirkt.

Greenhouse gas reduction is one of the main challenges toward obtaining a more sustainable energy system. The diffusion of electricity generation technologies that rely on renewable resources is one promising option to tackle this problem. However, the temporal mismatch of intermittent electricity generation (e.g. from wind power or photovoltaics) and load requires an increase in flexibility of the future energy system, for example provided by storage, dispatchable generation, or demand response. We quantify the potential contribution of an enhanced coupling between the electricity and heating sectors to balance intermittent renewable power generation in highly renewable energy scenarios for the U.S., focusing on the New England region (ISONE). For this purpose, a multi–sectoral approach is applied, combining the scenario construction methodology of the Stanford University with the cost optimizing capacity expansion and dispatch model REMix (Renewable Energy Mix). A particular focus lies on the flexible operation of Combined Heat and Power (CHP) plants and electric heat pumps (HP) enabled by thermal energy storage. Moreover, we evaluate the interaction and competition with alternative flexibility options, including power transmission, electric energy storage and controlled charging of battery electric vehicles (BEV).

Dieser Beitrag bietet Einblick in die Entwicklung und Anwendung einer Methodik zur Ermittlung von normativen Energieversorgungsszenarien. Im Fokus steht dabei eine sektorenübergreifende Betrachtung von Transformationspfaden hin zu einer überwiegend oder vollständig auf erneuerbaren Quellen basierenden Energieversorgung. Durch Anwendung des zeitlich und räumlich hoch aufgelösten Energiesystemmodells REMix wird der kostenminimale Kraftwerkspark, sowie der Bedarf an Speichern und Netzen im Zieljahr 2050 ermittelt, und die Wechselwirkung verschiedener Technologien und Sektoren analysiert. Die REMix-Ergebnisse bilden die Grundlage für die Ableitung eines Transformationspfades mit dem Simulationsmodell MESAP-PlaNet. Die so erweiterte Methodik wird hier in zwei Fallstudien für die Kanarischen Inseln und Brasilien angewendet.

The project focuses on a new update of the Brazilina Energy [R]evolution scenario, which was developed and published so far three times since 2007. The Energy [R]evolution scenario is a national energy scenario based on the assessment of energy demand and supply patterns and the renewable energy potentials available in ten Brazilian regions. The normative scenario is developed in a back-casting process, driven by ambitious CO2 reduction targets and 100 % renewable energy system. The project includes a new combinded modeling approach, coupling the MESAP7Planet simulation tool for the whole energy system, with an power system optimization tool REMix. The project elaborates supply scenarios for electricity, heat and transport based on renewable energy technologies and their respective potentials, generation costs, cost reduction potentials, and technology maturity as well as regional opportunities and barriers. The time horizon of the scenario is from 2014 to 2050.

Die Entwicklung robuster Strategien zur Reduktion industrieller Treibhausgasemissionen setzt detaillierte Analysen des Prozesswärmebedarfs voraus. Für die Einbindung erneuerbarer Energien in die industrielle Wärmeerzeugung ist dabei die Unterscheidung verschiedener Temperaturniveaus insbesondere im Prozesswärmebereich entscheidend, da die meisten erneuerbaren Technologien Wärme nur bis zu einer gewissen Temperatur bereitstellen können.