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One of the major challenges of renewable energy systems is the inherently limited dispatchability of power generators that rely on variable renewable energy (VRE) sources. To overcome this insufficient system flexibility, electrical energy storage (EES) is a promising option. The first contribution of our work is to address the role of EES in highly renewable energy system in Europe. For this purpose, we apply the energy system model REMix which endogenously determines both capacity expansion and dispatch of all electricity generation as well as storage technologies. We derive an EES capacity of 206 GW and 30 TWh for a system with a renewable share of 95%. An extensive sensitivity analysis shows that ESS requirements range from 126 GW and 16 TWh (endogenous grid expansion) to 272 GW and 54 TWh (low EES investment costs). As our second contribution, we show how the spatial distribution of EES capacity depends on the residual load, which-in turn-is influenced by regionally predominant VRE technologies and their temporal characteristics in terms of power generation. In this sense, frequent periods of high VRE excess require short-term EES, which naturally feature low power-related investment costs. In contrast, long-term EES with low energy-related costs are characteristic for regions where high amounts of surplus energy occur. This relationship furthermore underlines how EES capacity distribution is implicitly influenced technical potentials for VRE expansion.

Expansion planning models are often used to support investment decisions in the power sector. Towards the massive insertion of renewable energy sources, expansion planning of energy storage systems (SEP-Storage Expansion Planning) is becoming more popular. However, to date, there is no clear overview of the available SEP models in the literature. To shed light on the existing approaches, this review paper presents a broad classification of SEP, which is used to analyze a database of about 90 publications to identify trends and challenges. The trends we found are that while SEP was born more than four decades ago, only in the last five years increasing research efforts were put into the topic. The planning has evolved from adequacy criteria to broader targets, such as direct costs, mitigation of CO2 emissions, and renewable integration. The modeling of the network, power system, energy storage systems (ESS), and time resolution are becoming more detailed. Uncertainty is often considered and the solution methods are still very diverse. As outstanding challenges, we found that (1) the large diversity of ESS, in contrast to conventional generation technologies, and (2) the complex lifetime and efficiency functions need to be addressed in the models. (3) Only a high temporal and spatial resolution will allow for dimensioning the challenge of integrating renewables and the role of ESS. (4) Although the value of ESS lies beyond shifting energy in time, current SEP is mostly blind to other system services. (5) Today, many flexibility options are available, but they are often assessed separately. In the same line, although cross-sectorial (power, heat, transport, water) SEP is becoming more frequent, there are many open tasks towards an integrated coordination. The planning of future energy systems will be multi-sectorial and multi-objective, consider the multi-services of ESS, and will inherently require interdisciplinary efforts.

Background: The focus of the paper is on scenario studies that examine energy systems. This type of studies is usually based on formal energy models, from which energy policy recommendations are derived. In order to be valuable for strategic decision-making, the comprehensibility of these complex scenario studies is necessary. We aim at highlighting and mitigating the problematic issue of lacking transparency in such model-based scenario studies.

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The Future Fuels project combines research in several institutes of the German Aerospace Center (DLR) on the production and use of synthetic fuels for space, energy, transportation, and aviation. This article gives an overview of the research questions considered and results achieved so far and also provides insight into the multidimensional and interdisciplinary project approach. Various methods and models were used which are embedded in the research context and based on established approaches. The prospects for large-scale fuel production using renewable electricity and solar radiation played a key role in the project. Empirical and model-based investigations of the technological and cost-related aspects were supplemented by modelling of the integration into a future electricity system. The composition, properties, and the related performance and emissions of synthetic fuels play an important role both for potential oxygenated drop-in fuels in road transport and for the design and certification of alternative aviation fuels. In addition, possible green synthetic fuels as an alternative to highly toxic hydrazine were investigated with different tools and experiments using combustion chambers. The results provide new answers to many research questions. The experiences with the interdisciplinary approach of Future Fuels are relevant for the further development of research topics and co-operations in this field.Synthetic fuels based on renewable energies (RE) are widely seen as a key element to achieving climate-neutral transport (e.g., [1,2]). As liquid hydrocarbons have a high energy and power density, they are primarily discussed as fuels for (heavy) road vehicles, ships, and aircraft. Due to their low storage and transport losses, they are also conceivable as a complementary long-term electricity storage option [3]. The challenges of producing and implementing these fuels are manifold. Chemical processes and renewable electrical or thermal energy can be used to produce liquid hydrocarbons from various carbon sources and hydrogen (and sometimes oxygen). Synthetic fuels have several advantages: they can be easily integrated into our existing energy and mobility infrastructures, can be used in all areas of the transport sector, and they can be optimized with regard to their chemical properties. The main disadvantages are the high energy losses and production costs.In this research context, eleven research groups at the German Aerospace Center (DLR) are working together on the Future Fuels project on synthetic fuels. The aim of the interdisciplinary approach is to realize synergies and joint research activities, as well as new research impulses through different perspectives. The scientists and engineers are investigating how synthetic fuels can be produced using solar energy and electrolysis processes (Solar Fuels), and are developing concepts for the re-conversion of these fuels into electricity. They are working on emission-optimized fuels for transport and aviation (Designer Fuels), as well as advanced space ap...

Energy system optimization models used for capacity expansion and dispatch planning are established tools for decision-making support in both energy industry and energy politics. The ever-increasing complexity of the systems under consideration leads to an increase in mathematical problem size of the models. This implies limitations of today’s common solution approaches especially with regard to required computing times. To tackle this challenge many model-based speed-up approaches exist which, however, are typically only demonstrated on small generic test cases. In addition, in applied energy systems analysis the effects of such approaches are often not well understood. The novelty of this study is the systematic evaluation of several model reduction and heuristic decomposition techniques for a large applied energy system model using real data and particularly focusing on reachable speed-up. The applied model is typically used for examining German energy scenarios and allows expansion of storage and electricity transmission capacities. We find that initial computing times of more than two days can be reduced up to a factor of ten while having acceptable loss of accuracy. Moreover, we explain what we mean by “effectiveness of model reduction” which limits the possible speed-up with shared memory computers used in this study.

Flexibility requirements in prospective energy systems will increase to balance intermittent electricity generation from renewable energies. One option to tackle this problem is electricity storage. Its demand quantification often relies on optimization models for thermal and renewable dispatch and capacity expansion. Within these tools, power plant modeling is typically based on simplified linear programming merit order dispatch (LP) or mixed integer unit-commitment with economic dispatch (MILP). While the latter is able to capture techno-economic characteristics to a large extent (e.g. ramping or start-up costs) and allows on/off decision of generator units, LP is a simplified method, but superior in computational effort.We present an assessment of how storage expansion is affected by the method of power plant modeling and apply a cost minimizing optimization model, comparing LP with MILP. Moreover, we evaluate the influence of wind and photovoltaic generation shares and vary the granularity of the power plant mix within MILP.The results show that LP underestimates storage demand, as it neglects technical restrictions which affect operating costs, leading to an unrealistically flexible thermal power plant dispatch. Contrarily, storage expansion is higher in MILP. The deviation between both approaches however becomes less pronounced if the share of renewable generation increases.