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Energy-system scenarios are widely used to relate the developments of the energy supply and the resulting carbon-emission pathways to political measures. To enable scenario analyses that adequately capture the variability of renewable-energy resources, a specialised type of power-sector model (PSM) has been developed since the beginning of this century, which uses input data with hourly resolution at the national or subnational levels. These models focus on techno-economic-system optimisation, which needs to be complemented with expert socioeconomic knowledge in order to prevent solutions that may be socially inacceptable or that oppose political goals. A way to integrate such knowledge into energy-system analysis is to use information from framework scenarios with a suitable geographical and technological focus. We propose a novel methodology to link framework scenarios to a PSM by applying complexity-management methods that enable a flexible choice of base scenarios that are tailored to suit different research questions. We explain the methodology, and we illustrate it in a case study that analyses the influence of the socioeconomic development on the European power-system transition until 2050 by linking the power-sector model, REMix (renewable-energy mix), to regional framework scenarios. The suggested approach proves suitable for this purpose, and it enables a clearer link between the impact of political measures and the power-system development., Helmholtz Association

Background Energy system models (ESM) are widely used in research and industry to analyze todays and future energy systems and potential pathways for the European energy transition. Current studies address future policy design, analysis of technology pathways and of future energy systems. To address these questions and support the transformation of today’s energy systems, ESM have to increase in complexity to provide valuable quantitative insights for policy makers and industry. Especially when dealing with uncertainty and in integrating large shares of renewable energies, ESM require a detailed implementation of the underlying electricity system. The increased complexity of the models makes the application of ESM more and more difficult, as the models are limited by the available computational power of today’s decentralized workstations. Severe simplifications of the models are common strategies to solve problems in a reasonable amount of time – naturally significantly influencing the validity of results and reliability of the models in general. Solutions for Energy-System Modelling Within BEAM-ME a consortium of researchers from different research fields (system analysis, mathematics, operations research and informatics) develop new strategies to increase the computational performance of energy system models and to transform energy system models for usage on high performance computing clusters. Within the project, an ESM will be applied on two of Germany’s fastest supercomputers. To further demonstrate the general application of named techniques on ESM, a model experiment is implemented as part of the project. Within this experiment up to six energy system models will jointly develop, implement and benchmark speed-up methods. Finally, continually collecting all experiences from the project and the experiment, identified efficient strategies will be documented and general standards for increasing computational performance and for applying ESM to high performance computing will be documented in a best-practice guide.

At present, the integration of renewables, and especially wind power plants, in the electricity market, accentuates the role of the capacity market mechanism as an important means for the further diffusion of mature renewable energy technologies. The Capacity market is one of the main solutions for improving supply adequacy. This paper studies the impact of the capacity market on supply adequacy in an advanced long-term electricity market model with a noticeable share of renewable energy, simulating the market by applying a bottom-up approach. In this regard, the entire electricity market of Europe is simulated in the HECTOR model, taking a system dynamics perspective. The model simulates the electricity market of 28 European countries, with a special focus on Germany. In addition, the auctions studied are analyzed on two different spatial levels, the state and the national level. In the state level design, all wind power plants within Germany are assumed to bid within the federal state they are located and the market is cleared at the state level. In the national level design , all wind power plants located in different states bid in a national market, which represents the German market. Comparing the results obtained for the market design reveals the superior spatial platform for the implementation of renewable energy auctions. The results obtained allow identification of the influence of capacity market on the performance of the electricity market and wind generation investment considering detailed and comprehensive categorization of wind power plants. Categorization of wind technologies is based on their regional potential. Furthermore, impacts of capacity market on market performance of neighboring regions in an interconnected market, considering different spatial platforms will be scrutinized. Methods: HECTOR is a simulation model which simulates supply side of electricity market of Europe with system dynamics perspective. It consists of five main modules which all of them are executed simultaneously with hourly resolution. Main modules includes: capacity investment, plant bidding logic, decentral production, residual demand and market clearance. The objective function of this long-term model, which minimizes total system costs subject to a set of constraints, is being solved in market clearance module. This function matches supply and residual demand considering regional constraints such as import and export costs and transmission capacities in order to find lowest total system cost. A zooming approach has been used to politically measure the optimal regional resolution in Germany which market performance can be maximized with. Results: As the database of this study is not completed yet, we just referred to the expected results from our work in progress which will be as follows: First, a group of results, provides us information about the impacts of capacity market on the installed capacity of wind technologies in different regions of Germany

The talk describes several speed-up strategies applied to a optimising linear energy system model (OESM). It highlights both simple as well as more sophisticated approaches. Additionally scaling on the spatial and temporal dimension is investigated. The research was performed within the BEAM-ME project which focussed on the application of OESM on high performance computers.

In Germany, in 2017 the support scheme for renewables changed to capacity auctions for wind power. While in theory auctions have a high degree of overall target fulfilment, the regional distribution of investments varies based on the implemented market designs. Results from 2017 show that changes in market design lead to a significant shift of investments in the south of Germany: While previously support schemes incentivised investments, in 2017 almost no wind projects were accepted. This paper investigates the regional distribution of investments into wind energy, when different designs of capacity auctions are implemented. The modelling approach draws on a parallel analysis of technical potential, expected revenues and social acceptance to determine economic wind power investments. The European electricity model REMix is then used to simulate investments in wind energy in order to analyze: What measures and incentives on a German/European level could be beneficial to meet regional targets? Overview: In recent years social acceptance of investment projects for renewables, power plants and power lines have gained significant attention by sociologists and policy makers. Results of previous studies show (Sonnberger 2017), that with regard to wind energy people tend to have a considerably high level of trust and acceptance of wind power projects in general. However, when wind power stations are planed close to settlements, the level of acceptance decreases sharply. Policy makers in Germany (in the state of North Rhine-Westphalia and Bavaria) therefore proposed to "avoid acceptance problems" by introducing a minimum distance of wind farms to settlements. The paper therefore aims to answer the following questions: - How can public acceptance be integrated into the analysis of wind investments? Which measures and market incentives can increase public acceptance for additional investments into wind power? - What incentives provide different remuneration schemes and auction design on the regional distribution of wind energy? - What regulatory measures and incentives on a German and European level could be beneficial to reach the regional targets (e.g. the states targets)? (here: targets of the state of Baden-Wuerttemberg) The analysis was conducted for Germany and the state of Baden-Wuerttemberg. Methods: The selected modelling approach consists of three parts: 1. Technical potential: A geodata (GIS) based analysis has been used to investigate the technical potential of wind power in different regions in Germany. The model REMix-Endat uses a high resolution spatial analysis and determines potential areas within Germany, where investments into additional wind farms could talke place. The calculation is based on distance from settlements, infrastructure, type of landscape (landcover data), slope and altitude . In a second step the model determines, based on historic windspeeds, the estimated hourly feed-in of renewables in future years for these different locations. 2. Market design and incentives: In a second step, a modell analyzing the long term investment incentives from different political frameworks and market designs will be investigated for different regions and types of locations. The model determines the expected net present value for each location. 3. Public acceptance: Aspects of public acceptance will be integrated into the model. While general acceptance for wind is high, local acceptance must be accomplished to enable investments. Two path for increasing local acceptance are investigated: Avoiding acceptance problems in the first place and creating distributional fairness and trust. The effect of both measures on the energy system and long term investments are investigated. Technical potential, market incentives and results from the acceptance analysis are integrated into the European energy system model REMix. Based on the estimated hourly dispatch and price estimates for representative years up to 2050, an overall potential can be determined for each location. The modell depicts investments - it especially adds wind (an PV) capacity to meet the renewable targets for Germany. A first analysis of market design and incentives for investments and detailed description can be found in Borggrefe (2018). This paper extends the model and focuses on the integration of aspects of "public acceptance" Results: Creating acceptance by "avoiding acceptance problems" as it is proposed/implemented by some states in Germany will not provide sufficient areas for wind power onshore. Investments into other more expensive renewable technologies will increase costs of electricity procurement. A second set of scenarios analyses the impact of a "fair distribution" of wind capacity across all regions in Germany on market results, system stability and target fulfillment. In the coming decades this will lead to increasing costs for investment and remuneration. In the long run the resulting energy system also provides benefits, because cost extensive investments into grid can be saved.

Up until now, wind turbines have been designed to generate electricity at the lowest possible total cost, independent of this electricity's market value. With an increasing penetration of wind power in the system, the market value of electricity generated by wind turbines is declining, since wind turbines tend to produce electricity at the same time. For this reason, it will be important in the future to design wind turbines in a system-friendly manner so that a larger proportion of electricity generation occurs in hours with lower wind speeds. This can be achieved with higher towers, longer rotor blades, and generators with comparatively low power ratings. According to model calculations, a fixed feed-in tariff provides insufficient incentives for such plant designs, which would be especially system-friendly in the context of further expansion of renewable energies. Likewise, direct marketing with a floating market premium does not provide adequate incentives if investors take the current electricity prices as a basis for their planning and project financing. By contrast, in a new instrument that is being proposed here-the so-called "production value-based benchmark approach"-the level of the feed-in tariff is based on the expected future market value of the wind turbine's electricity. In this way, incentives for investments in plants that will be especially system-friendly in the future could already be created in the present. At the same time, questions regarding the actual design and the practical implementation still need to be resolved.

Quantitative energy system modelling based on primarily linear mathematical optimization provide a basis to answer political, technical, and economic questions regarding the future development of electricity systems. In order to capture the complexity of future decentralized electricity system, models are required to become increasingly complex. This presentation outlines how high performance computing (HPC) can be applied to energy system modelling and describes challenges and benefit that arise when complex energy models based on linear and non-linear algorithms are applied to parallel computing. The presentation draws on results from the project BEAM-ME funded by the German Federal Ministry for Economic Affairs and Energy. The research project aims at improving computational performance of energy system models. Within this project the consortium of researchers from different research fields (system analysis, mathematics, operations research and informatics) develop new strategies to increase computational performance of energy system models and to apply energy system models to high performance computing. This presentation presents intermediate results from a benchmark analysis when applying the energy system model REMix to HPC. The presentation concludes with a discussion on future challenges for energy system modelling and how HPC can enable energy modelers to improve scenarios, market design and policy advice.

Das Poster "BEAM-ME Entwicklung von Beschleunigungs- ansätzen für Energiesystemmodelle" stellt das Projekt und die Inhalte der Arbeitspakete vor. Im Rahmen des Projekts erfolgt die Entwicklung von Beschleunigungsstrategien für Energiesystemmodelle (ESM) in einem interdisziplinären Team aus Modellierern, Informatikern und Mathematikern Ziel des Projekts BEAM-ME ist die Entwicklung effizienter Lösungsansätze für sehr komplexe ESM. Hierzu werden universelle Algorithmen und Verfahren zur Lösung der ESM und Demonstration der Übertragbarkeit entwickelt. Im Rahmen des Projekts liegt ein Fokus auf der Anwendung der Beschleunigungsstrategien zur Untersuchung der Fragestellungen von morgen mit komplexen ESM. Zudem sollen Energiesystemmodelle auf Hochleistungsrechnern ausgerollt und angewendet werden.

Long term capacity expansion planning requires making decisions now, which have an impact on the energy system over several decades, however uncertainty prevails with regard to exogenous parameters such as fuel prices, CO2 prices, market regulation and renewable feed-in. Stochastic optimization over a large set of scenarios can incorporate this uncertainty into the decision process. This paper compares different enhanced Benders decomposition methods implemented in an energy system model (ESM) with regard to computation time, memory used during calculation and number of iterations. When considering flexibility options like electrical energy storage, demand side management and electric mobility in energy system models, a high spatial and temporal resolution of the modelled energy system is required. Consequently, the implementation of stochastic optimization into high resolution optimizing energy system models will lead to an increased complexity, due to the additional scenario dimension. This makes traditional stochastic optimization approaches like the formulation of the deterministic equivalent impossible to solve due to memory restrictions. This problem can be tackled using decomposition approaches such as enhanced Benders decomposition in order to guarantee achieving the global optimum while taking computational constraints into account. Challenges arise especially regarding CPU load balancing for the application to high performance computing. The work is part of the BEAM-ME project, a German funded research project aiming at developing speed-up methods by improving the modelling, underlying algorithms and application of ESM on high performance computing. The presentation will discuss the modelling approaches in order to extend the existing energy system model REMix, developed at the German Aerospace Center, as well as the comparison of different algorithmic decompositions improvements implemented in order to accelerate convergence and achieve parallelization. These methodological improvements include the types of optimality cuts, application of trust-regions and achieving asynchronous solving of master and sub problem. The preliminary results indicate substantial improvements are possible compared to the traditional Benders Decomposition and computational constraints can be overcome. Furthermore these methods may be improved by applying energy system model specific information.

The transition of the energy system towards a sustainable supply with low carbon emissions requires the long term planning of power generation capacity expansion. Energy scenarios can give insight into the development of complex electricity systems in the coming decades. Each scenario includes a large number of external factors which influence the pathway of energy system development. However, due to the long term nature of the energy transition, these external parameters (e.g. fuel prices, technology development, weather influences etc.) contain large uncertainties. To a certain degree, cross-impact-balance analysis can evaluate the consistency and improve the holistic image of future energy scenarios, but a large degree of uncertainty remains. So far, this problem was usually tackled by deterministic optimization with subsequent sensitivity analysis. Recent development towards parallel computing allow for stochastic optimization over a large set of scenarios. When considering flexibility options like electrical energy storage, demand side management and electric mobility, high temporal resolutions of the modelled energy system are required. Consequently, the implementation of stochastic optimization into high resolution optimizing energy system models will lead to an increased complexity, due to the additional scenario dimension. This problem can be tackled using decomposition approaches like enhanced Benders decomposition in order to guarantee achieving the global optimum while taking computational restrictions into account. Challenges arise especially regarding CPU load balancing for the aspired migration to high performance computing. The presentation will discuss preliminary results from an extension of the energy system model REMix, developed at the German Aerospace Center (8760 h per year, developed in GAMS and solved as a LP or MIP using CPLEX). By implementing different decomposition techniques and improving convergence, computational constraints can be overcome and the number of evaluated scenarios can be increased. Aim of this analysis is to increase the complexity of the stochastic models and improve the quality and robustness of the modelling results.

Ein breites Spektrum an neuen Technologien und Lösungen wird notwendig sein, um den Übergang vom fossilen zum erneuerbaren Energiezeitalter verlässlich und wirtschaftlich zu gestalten. Gemeinsam mit dem Beratungsunternehmen Ludwig-Bölkow-Systemtechnik hat das Deutsche Zentrum für Luft- und Raumfahrt (DLR) im Auftrag des Clusters Brennstoffzelle BW untersucht, welchen Beitrag der Energieträger Wasserstoff zum Energie- und Verkehrssystem bis zum Jahr 2030 in Baden Württemberg leisten und wie er aus erneuerbarem Strom hergestellt werden kann. Analysiert wurden die potenziellen Einsatzbereiche, die jeweils benötigte Infrastruktur, die Kopplung von Strom- und Wasserstofferzeugung sowie die finanziellen und klimarelevanten Auswirkungen.

Ziel der Studie war es, potenzielle Einsatzbereiche und Infrastrukturen für eine künftige Nutzung von Wasserstoff in Baden-Württemberg zu identifizieren und die monetären sowie klimarelevanten Wirkungen darzustellen. Eine Kommerzialisierung ist voraussichtlich zuerst im Verkehrssektor möglich, weitere Marktpotenziale in der Erdgas- und Chemieindustrie sowie zur Rückverstromung werden erst nach 2030 gesehen. Derzeit existieren erste Kleinserien für Brennstoffzellenfahrzeuge, auf Basis derer die Markthochlaufphase in der kommenden Dekade stattfinden könnte. Die erfolgreiche Einführung der Wasserstoffnutzung ist sehr stark abhängig von der Entwicklung der Technologie- und Betriebskosten, des vorhandenen Tankstellennetzes und der Effizienz der Energieumwandlung. Diese Studie arbeitet daher mit zwei Szenarien, einem „konservativen“, in dem ein signifikanter Markthochlauf erst nach 2030 erfolgt, und einem „ambitionierten“, in dem im Jahr 2030 bereits 140.000 Brennstoffzellen-Pkw auf den Straßen Baden-Württembergs fahren, mit zusätzlich bis zu 900 brennstoffzellenbetriebenen Stadtbussen und 50 Triebfahrzeugen für den Schienenpersonennahverkehr. Das ambitionierte Szenario würde die Treibhausgasemissionen im Land um rund 200 kt CO2 pro Jahr mindern. Dies ergibt sich aus der Betrachtung sowohl der Strombereitstellung für die Elektrolyseure als auch der Substitution konventioneller Antriebe in den Fahrzeugflotten. Die Emissionsminderung im Verkehr beläuft sich dabei auf rund 380 kt CO2, während die Annahme einer flexiblen, d.h. sich in einem definierten Rahmen an den Grenzkosten der Stromerzeugung orientierenden Nutzung des Strommixes für die Wasserstoffelektrolyse zu zusätzlichen Emissionen im Stromsektor von rund 180 kt CO2 führt.

This talk investigates to what extend demand side management (DSM) can play a significant role in future energy markets and can help to integrate large shares of renewable energy into the energy system. Based on results of recent studies at the DLR System Analysis Group the presentation addresses three topics. In the first part it analyzes the technical potential for demand side Management. The second part investigates how demand side management will be used in future energy systems. The role of load managment in balancing and intraday markets is investigated as well as the potential for integration of renewables in the spot market are analyzed. In the final part potential game changers to the application of DSM and long term impact of DSM on the energy system are outlined.

Die Energiewende ist bislang stark stromfokussiert, obwohl sie nur als Strom-, Wärme- und Mobilitätswende erfolgreich sein kann. Trotz großer Potenziale im Bereich Effizienz und erneuerbare Energien weist die Wärmewende in den letzten Jahren kaum Fortschritte auf. Im Jahr 2014 hatten die erneuerbaren Energien in Deutschland einen Anteil von 10,9 % an der gesamten Wärmeversorgung im Gegensatz zu 26,2 % an der Brutto-Stromversorgung. Allerdings ist die Energiewende im Wärmesektor auch wesentlich schwieriger umsetzbar als im Stromsektor. Denn in Bezug auf Technologien, Marktstrukturen, Akteursvielfalt und Kostenstrukturen weist der Wärmesektor eine deutlich größere Heterogenität als der Stromsektor auf, was die Umsetzung einer effizienten Politik erschwert. Mittlerweile liegen umfangreiche Praxiserfahrungen mit Politikinstrumenten im Wärmesektor vor, so dass die Umsetzung einer erfolgreichen Wärmewende mit einer adäquaten, berechenbaren, konsistenten und konsequenten Politik möglich ist. Im Interesse einer erfolgreichen Umsetzung der Energiewende plädiert der FVEE für eine deutliche Stärkung des Wärmesektors in der Energiepolitik und die Umsetzung einer entschiedenen und langfristig angelegten Politik der Wärmewende, die den besonderen Anforderungen des Wärmesektors gerecht wird. Diese muss auf einer fundierten Analyse aufbauen und den spezifischen Bedingungen im Wärmesektor gerecht werden. Als Beitrag zu einer fundierten Diskussion über adäquate Politikinstrumente in der Wärmewende hat der FVEE mit seinen Mitgliedsinstituten das vorliegende Positionspapier erstellt. Dieses gibt einen umfassenden Überblick über die Herausforderungen und Handlungsoptionen im Wärmesektor und bietet damit eine wichtige Orientierung. Das Papier dient zur Standortbestimmung, kann aber fundierte Studien nicht ersetzen, die für ein vertieftes Verständnis dringend erforderlich sind. Das FVEE-Positionspapier stellt die möglichen Lösungsansätze im Wärmemarkt vor und beschreibt die Rolle der wichtigsten Technologien, die für eine nachhaltige Wärmeversorgung erforderlich sind: Solarthermie, Biomasse, Wärmepumpen und Tiefengeothermie. Auch die Kälteversorgung mit erneuerbaren Energien wird diskutiert. Weiter geht das Papier auf die Herausforderungen in der Systemintegration und die Systemtechnologien ein: Kraft-Wärme-Kopplung (KWK), Wärmespeicher, Heizen mit EE-Strom sowie Wärmenetze und kommunale Wärmepläne. Unter Berücksichtigung der Entwicklungspotenziale dieser Technologien liefert das Papier Empfehlungen für die Wärmewende. Eine erfolgreiche Wärmewende muss insbesondere den spezifischen Bedingungen des Wärmemarktes gerecht werden. Dieser ist geprägt von einer großen Heterogenität und hohen Komplexität, was Eigentümer und Betreiber, Heiztechnologien und Anlagengrößen,- felder angeht. Dabei ist seine künftige Entwicklung stark von externen Faktoren abhängig, beispielsweise der Entwicklung fossiler Energiepreise, den Entwicklungen im Stromsektor (Power to heat) und den Fortschritten bei der Gebäudeeffizienz. Eine große Herausforderung stellt auch die Infrastrukturfrage dar, denn im Gegensatz zum Stromsektor sind verschiedene Infrastrukturlösungen möglich, beispielsweise eine dezentrale Beheizung mit Biogas (Gasnetz), Wärmepumpen (Stromnetz) oder Holz kombiniert mit Solarwärme sowie eine zentrale Wärmeversorgung mit Kraft-Wärme-Kopplung (Nahwärmenetze). Aufgrund der fehlenden Sicherheit künftiger Entwicklungen sind Infrastrukturentscheidungen im Wärmesektor mit einem hohen Investitionsrisiko behaftet. Weiter erschweren die starken saisonalen Wärmebedarfsschwankungen eine verstärkte Nutzung von Strom im Wärmesektor.

Das Ziel des Vorhabens war die Ermittlung des Einsatzpotenzials unterschiedlicher Lastausgleichsoptionen in einem zukünftigen Stromversorgungssystem bei steigendem Anteil der Stromerzeugung aus fluktuierenden erneuerbaren Energien. Dabei waren neben dem Einsatz von Stromspeichern auch die Möglichkeiten und Grenzen verschiebbarer Lasten, des Stromtransports im transeuropäischen Verbund und des stromgeführten Betriebs dezentraler KWK-Anlagen mit Wärmespeicher zu untersuchen. Das am DLR entwickelte Energiesystemmodell REMix wurde um die entsprechenden Technologiemodelle erweitert. Für Europa konnte gezeigt werden, dass in den untersuchten Szenarien bei angepasstem Netzausbau ein Ausbau neuer Speicherkapazitäten unterbleibt und die Überschüsse aus fluktuierender Stromerzeugung deutlich reduziert werden. Langzeitspeicher werden nur bei konservativ begrenztem Netzausbau, wie er z.B. aus Akzeptanzgründen auftreten könnte, eingesetzt. In Detailsimulationen zum Lastausgleich in Deutschland wurden ausgehend von den Europaszenarien zusätzlich zu Langfristspeichern folgende Optionen des Lastausgleichs untersucht: a) Flexibilisierung des KWK-Betriebs mit thermischen Speichern, konventionellen und elektrischen Spitzenlastkesseln, b) Lastmanagementoptionen einschließlich flexibilisierter Wärmepumpen und Ladesteuerung für Elektrofahrzeuge und c) modellendogener Zubau von Mittelfristspeichern. Damit konnte die Funktionen des erweiterten Modells REMix demonstriert und erste Erkenntnisse zur zukünftigen Rolle von Lastausgleichsoptionen und zu Wechselwirkungen zwischen den Sektoren Strom, Wärme und Verkehr gewonnen werden.

EU member states aim for significantly increasing the share of electricity production from renewable energy sources to meet long-term decarbonization targets. The German government defined a goal of 80% electricity generation from renewable energies by 2050. Fluctuating renewable energy technologies based on wind, photovoltaic and water are seen as key technologies to meet these goals. This contribution presented results of a three-year study estimating fluctuating renewable feed-in and analyzing medium to long-term potentials of most relevant load balancing options in a power supply system with high shares of renewable energies.

EU Member States increase deployment of intermittent renewable energy sources to deliver the 20% renewable target formulated in the European Renewables Directive of 2008. To incorporate these intermittent sources, a power market needs to be flexible enough to accommodate short-term forecasts and quick turn transactions. This flexibility is particularly valuable with respect to wind energy, where wind forecast uncertainty decreases significantly in the final 24 hours before actual generation. Therefore, current designs of intraday and balancing markets need to be altered to make full use of the flexibility of the transmission system and the different generation technologies to effectively respond to increased uncertainty. This paper explores the current power market designs in European countries and North America and assesses these designs against criteria that evaluate whether they are able to adequately handle wind intermittency.