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This study innovatively combines a set of methods to provide a new way to assess the economic potential of pumped hydro energy storage. It first provides a method based on geographic information systems to study the potential of pumped-hydro for different topologies. Second, using cost estimates for each identified site, cost-potential curves are derived. Finally, these curves are used for planning a fully renewable system to assess their impact on investment recommendations. Applications to Chile, Peru, and Bolivia show the usability of the methods. Over 450 pumped-hydro locations are identified, totaling around 20 TWh (1600 GW of installed capacity with 12 h of storage). These numbers exceed by 20-fold the projected daily energy demand of the corresponding countries. When taking into account investment costs, most locations are cheaper than current Li-ion batteries, but only some are expected to remain competitive. When using the resulting cost-potential curves to design a future energy system, the planning tool recommends about 1.6 and 5.0 times more pumped-hydro storage compared to using average values and literature values, respectively. These differences underline the significance of the found cost curves. These findings are relevant to the energy planning community, policymakers, and energy companies. Post-print / Final draft

Future energy-supply systems must become more flexible than they are today to accommodate the significant contributions expected from intermittent renewable power sources. Although numerous studies on planning flexibility options have emerged over the last few years, the uncertainties related to model-based studies have left the literature lacking a proper understanding of the investment strategy needed to ensure robust power grid expansion. To address this issue, we focus herein on two important aspects of these uncertainties: The first is the relevance of various social preferences for the use of certain technologies, and the second is how the available approaches affect the flexibility options for power transmission in energy-system models. To address these uncertainties, we analyze a host of scenarios. We use an energy-system optimization model to plan the transition of Europe’s energy system. In addition to interacting with the heating and transport sectors, the model integrates power flows in three different ways: as a transport model, as a direct-current power-flow model, and as a linearized alternating-current power-flow model based on profiles of power transfer distribution factors. The results show that deploying transmission systems contributes significantly to system adequacy. If investments in new power-transmission infrastructure are restricted—for example, because of social opposition—additional power generation and storage technologies are an alternative option to reach the necessary level of adequacy at 2% greater system costs. The share of power transmission in total system costs remains widely stable around 1.5%, even if cost assumptions or the approaches for modeling power flows are varied. Thus, the results indicate the importance of promoting investments in infrastructure projects that support pan-European power transmission. However, a wide range of possibilities exists to put this strategy into practice.

To assess the resilience of energy systems, i.e., the ability to recover after an unexpected shock, the system’s minimum state of service is a key input. Quantitative descriptions of such states are inherently elusive. The measures adopted by governments to contain COVID-19 have provided empirical data, which may serve as a proxy for such states of minimum service. Here, we systematize the impact of the adopted COVID-19 measures on the electricity demand. We classify the measures into three phases of increasing stringency, ranging from working from home to soft and full lockdowns, for four major electricity consuming countries of Europe. We use readily accessible data from the European Network of Transmission System Operators for Electricity as a basis. For each country and phase, we derive representative daily load profiles with hourly resolution obtained by k-medoids clustering. The analysis could unravel the influence of the different measures to the energy consumption and the differences among the four countries. It is observed that the daily peak load is considerably flattened and the total electricity consumption decreases by up to 30% under the circumstances brought about by the COVID-19 restrictions. These demand profiles are useful for the energy planning community, especially when designing future electricity systems with a focus on system resilience and a more digitalised society in terms of working from home., German Federal Ministry of Economic Affairs and Energy, German Federal Ministry of Education and Research

The comprehensive evaluation of strategies for decarbonizing large- scale energy systems requires insights from many different perspectives. In energy systems analysis, optimization models are widely used for this purpose. However, they are limited in incorporating all crucial aspects of such a complex system to be sustainably transformed. Hence, they differ in terms of their spatial, temporal, technological, and economic perspective and either have a narrow focus with high resolution or a broad scope with little detail. Against this background, we introduce the so- called granularity gaps and discuss two possibilities to address them: increasing the resolutions of the established optimization models, and the different kinds of model coupling. After laying out open challenges, we propose a novel framework to design power systems in particular. Our exemplary concept exploits the capabilities of power system optimization, transmission network simulation, distribution grid planning, and agent- based simulation. This integrated framework can serve to study the energy transition with greater comprehensibility and may be a blueprint for similar multi-model analyses.

Greenhouse gas emissions need to stop shortly after mid-century to meet the Paris Agreement of keeping global warming well below 2°C. Fully renewable energy systems arise as a clear solution. To cope with their highly fluctuating power output (wind and solar photovoltaic), power systems need to become more flexible than they are today. Energy storage is one source of flexibility and is widely esteemed as a key-enabler for the energy transition. Hydropower often has storage, and can also help in this task. To assess how much energy storage is needed, expansion planning tools are commonly used. In general terms, they aim to minimize system-wide investment and operational costs, while meeting a set of techno-economic constraints. In the task of quantifying the need for energy storage, the present thesis makes four contributions, related to the overarching research question: how to plan the optimal energy storage mix for fully renewable power systems with important shares of hydropower? These contributions aim to assist the energy transition and to be relevant for energy system modelers, energy policy makers, and decision makers from ecohydrology, storage companies, and the renewable industry. - First contribution: The last couple of years have seen a particularly strong enrichment of such expansion tools. In response, the first contribution of this thesis is to provide a comprehensive review of the existing models, including a clear classification of the approaches and derivation of the current modeling trends. This review culminates by identifying the following open challenges for storage planning. First, the many available storage devices are quite diverse in their technical and economic parameters (including efficiency and lifetime), and this must be considered in the models. The tools also need to count with a high resolution of space and time to adequately capture the challenges of integrating renewable generation. Second, the many services that storage technologies can provide (beyond energy balancing, such as power reserves) need to be acknowledged. And third, the different energy sectors (electricity, heat, transport) all have sources of flexibility; thus, planning has to become multi-sectoral. - Second contribution: Many storage expansion studies have been produced within the last 5 years, but these resulted in a very broad range of storage requirements. To shed light on their recommendations, the second contribution systemizes over 400 scenarios of these studies for the U.S., Europe, and Germany. This exercise revealed that, as the share of renewable generation grows, the power capacity (e.g. GW, in pumped hydro, related to the number of turbines) and energy capacity (e.g. GWh, in pumped hydro, related to the water held by its reservoir) of storage systems increase linearly and exponentially, respectively. As grids become highly renewable, especially when based on solar photovoltaic, the need for storage peaks. The power capacity is around 40-75% of the peak demand, and the energy capacity 10% of the annual demand. A final finding of this analysis is that assumptions on electrical grid modeling, grid expansion, and energy curtailment have strong impacts on the found storage sizes. - Third contribution: Developing a new optimization tool for storage expansion planning in the power sector is the third contribution: LEELO (Long-term Energy Expansion Linear Optimization). LEELO extends the available models by including further services in the planning approach: power reserves and energy autonomy. A further novelty of LEELO is a detailed representation of hydropower cascades, which is a convenient source of flexibility in many regions of the world. A case study about Chile for the year 2050 assesses the impact of including these multiple services in the planning stage on the final storage recommendations. Indeed, the found deviations in total power capacities and energy capacities of storage are large; up to 60% and 220%, respectively. Moreover, the resulting storage mix (i.e. the sizes of the individual storage technologies) is also strongly affected. Lastly, planning with such services revealed a 20% cost increase that would otherwise remain hidden to the planners. Overall, modeling multiple services in expansion planning is relevant when designing fully renewable systems, as controllable (dispatchable) generators disappear. - Fourth contribution: In the final contribution, two optimization-objectives are added to LEELO. The first one relates to reducing hydropeaking, a highly fluctuating operational scheme of hydropower reservoirs that threatens the downstream river ecology. The second objective minimizes new transmission lines, as they have numerous externalities that result in delays and social opposition. Multi-objective LEELO is able to find the Pareto Front of these three dimensions (costs, hydropeaking, new transmission). In a case study, again about Chile, the found trade-offs are assessed from the perspective of the involved stakeholders. It found that the minimum cost solution requires doubling the existing transmission infrastructure while operating at severe hydropeaking. Avoiding all transmission projects will cost between 3 and 11% (depending on the allowed level of hydropeaking). In other words, the upside of new transmission is rather limited. As transmission is avoided, the generation turns significantly more solar while investments in wind decrease. At the same time, and to support a solar grid, the requirements for storage technologies grow. Demand for storage also grows when hydropeaking is constrained, as a direct response to the missing flexibility from hydropower. Severe hydropeaking can be mitigated for as little as 1% of additional costs (if new transmission is installed), which is good news to environmental organizations. Completely avoiding both hydropeaking and new transmission lines is the most extreme scenario, costing an additional 11% and requiring about 20% more storage power capacity. In short, cheap storage and solar technologies emerge as key-enablers for reaching such attractive solutions that can avoid both externalities (transmission and hydropeaking). A clear investment strategy for these technologies is needed and, if done right, can make the generation more sustainable and socially acceptable. When comparing the storage requirements for Chile to those for Europe and the U.S., it becomes clear that the storage power capacities needed for Chile are on the higher end (>70% of peak demand). This is related to the fact that Chile’s power system is about 20 times smaller and has highly correlated energy resources. The needed energy capacities are also on the higher end (9-13% of annual demand). Here, however, the existing hydropower park already provides a buffer of 6%, making the remaining demand much lower (3-7%). If new transmission projects are to be avoided, the need for storage increases very strongly in terms of power capacity (adding 5 to 30 percentage points) and only slightly in terms of energy capacity (adding 1 percentage point). Mitigating hydropeaking also increases the need for power capacity but without exceeding the range above. The strongest storage requirements arise from the multi-service simulations; in particular for meeting high levels of energy autonomy, the (storage) energy capacity needs to be doubled. Relating back to the main question on how to plan the mix of energy storage systems, it became evident that multi-service, multi-sector, and multi-objective approaches are needed. This thesis took a first step in that direction. Two detailed extensions (multi-service, multi-objective) for storage planning determined a higher need for these technologies in a case study on Chile, where the future for storage looks promising. In general, the performed case study provides the first 100% renewable scenarios for Chile. Altogether, the gained insights showed to be relevant for stakeholders from the energy and environmental sectors on the path to a zero-carbon energy supply.