Zukünftige Energie- und Industriesysteme
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The German Energiewende is a deliberate transformation of an established industrial economy towards a nearly CO2-free energy system accompanied by a phase out of nuclear energy. Its governance requires knowledge on how to steer the transition from the existing status quo to the target situation (transformation knowledge). The energy system is, however, a complex socio-technical system whose dynamics are influenced by behavioural and institutional aspects, which are badly represented by the dominant techno-economic scenario studies. In this paper, we therefore investigate and identify characteristics of model studies that make agent-based modelling supportive for the generation of transformation knowledge for the Energiewende. This is done by reflecting on the experiences gained from four different applications of agent-based models. In particular, we analyse whether the studies have improved our understanding of policies' impacts on the energy system, whether the knowledge derived is useful for practitioners, how valid understanding derived by the studies is, and whether the insights can be used beyond the initial case-studies. We conclude that agent-based modelling has a high potential to generate transformation knowledge, but that the design of projects in which the models are developed and used is of major importance to reap this potential. Well-informed and goal-oriented stakeholder involvement and a strong collaboration between data collection and model development are crucial.
Electricity generation requires water. With the global demand for electricity expected to increase significantly in the coming decades, the water demand in the power sector is also expected to rise. However, due to the ongoing global energy transition, the future structure of the power supply - and hence future water demand for power generation - is subject to high levels of uncertainty, because the volume of water required for electricity generation varies significantly depending on both the generation technology and the cooling system. This study shows the implications of ambitious decarbonization strategies for the direct water demand for electricity generation. To this end, water demand scenarios for the electricity sector are developed based on selected global energy scenario studies to systematically analyze the impact up to 2040. The results show that different decarbonization strategies for the electricity sector can lead to a huge variation in water needs. Reducing greenhouse gas emissions (GHG) does not necessarily lead to a reduction in water demand. These findings emphasize the need to take into account not only GHG emission reductions, but also such aspects as water requirements of future energy systems, both at the regional and global levels, in order to achieve a sustainable energy transition.
Many countries are increasingly investing in renewable energy technologies to meet growing energy demands and increase the security of their energy supply. This development is also evident in the Middle East and North Africa (MENA) region, where renewable energy targets and policies have evolved rapidly in recent years. There is a steady increase in both the number of planned and implemented solar photovoltaic (PV) but also of solar thermal projects in form of Concentrating Solar Power (CSP) plants. Many of these installations are designed as large utility-scale systems. Despite the fact that these types of large-scale projects can have significant effects on local communities and their livelihoods, the existing research into the social impacts of such large-scale renewable energy infrastructures at local level is limited. However, assessing and managing these impacts is becoming increasingly important to reduce risks to both the affected communities and to the project and businesses activities. In order to provide more robust evidence on the local effects, this research study reviews the social impacts of large-scale renewable energy infrastructure in the MENA region based on a case study of the NOORo I CSP plant in Ouarzazate, Morocco. Data collected during two empirical field studies, in combination with expert interviews and secondary data analysis, provides detailed evidence on the type and significance of livelihood impacts of the NOORo I CSP plant. The analysis results in a consolidated list of 30 impacts and their significance levels for different stakeholder groups including farmers, young people, women, community representatives and owners of small and medium enterprises. The results show that, overall, the infrastructure development was received positively. The review also indicates that factors identified as having effects on the sustainability of local livelihoods are mainly related to information management and benefit distribution, rather than physical or material aspects.
A significant reduction in greenhouse gas emissions will be necessary in the coming decades to enable the global community to avoid the most dangerous consequences of man-made global warming. This fact is reflected in Germany's 7th Federal Energy Research Program (EFP), which was adopted in 2018. Direct Air Capture (DAC) technologies used to absorb carbon dioxide (CO2) from the atmosphere comprise one way to achieve these reductions in greenhouse gases. DAC has been identified as a technology (group) for which there are still major technology gaps. The intention of this article is to explore the potential role of DAC for the EFP by using a multi-dimensional analysis showing the technology's possible contributions to the German government's energy and climate policy goals and to German industry's global reputation in the field of modern energy technologies, as well as the possibilities of integrating DAC into the existing energy system. The results show that the future role of DAC is affected by a variety of uncertainty factors. The technology is still in an early stage of development and has yet to prove its large-scale technical feasibility, as well as its economic viability. The results of the multi-dimensional evaluation, as well as the need for further technological development, integrated assessment, and systems-level analyses, justify the inclusion of DAC technology in national energy research programs like the EFP.
There is an increasing pressure that enhanced and novel energy technologies are swiftly adopted by the market to ensure meeting the energy and climate targets. An important issue with such novel developments is their risk to be stuck in the "valley of death", i.e. that their transition to the market is delayed or unsuccessful. Publicly supported demonstration projects could help to bridge the valley of death by reducing barriers to the adoption caused by missing information and perceived risks. A challenge for technology demonstrations in the industrial context is their often high investments that are required to prove their real-world benefits. Given the magnitude of such investments, it becomes crucial that public funding focuses on the most promising demonstration proposals. Structured evaluation processes can help to facilitate the identification of promising proposals and to improve the quality and transparency of decisions. This paper deals with a corresponding multi-staged multi-criteria decision support system (DSS) suggested to the German Federal Ministry for Economic Affairs and Energy. It deals with the evaluation of demonstration proposals across three stages: The first stage represents a filtering stage to identify those proposals relevant for further considerations. The second stage comprises a multi-criteria scoring method drawing on an evaluation against nineteen criteria. The final third stage serves to critically review the need for public funding of well-scored proposals. This contribution outlines the development of the DSS and its design and thus provides insights on proposal evaluating in energy research.
For many years, carbon capture and storage (CCS) has been discussed as a technology that may make a significant contribution to achieving major reductions in greenhouse gas emissions. At present, however, only two large-scale power plants capture a total of 2.4 Mt CO2/a. Several reasons are identified for this mismatch between expectations and realised deployment. Applying bibliographic coupling, the research front of CCS, understood to be published peer-reviewed papers, is explored to scrutinise whether the current research is sufficient to meet these problems. The analysis reveals that research is dominated by technical research (69%). Only 31% of papers address non-technical issues, particularly exploring public perception, policy, and regulation, providing a broader view on CCS implementation on the regional or national level, or using assessment frameworks. This shows that the research is advancing and attempting to meet the outlined problems, which are mainly non-technology related. In addition to strengthening this research, the proportion of papers that adopt a holistic approach may be increased in a bid to meet the challenges involved in transforming a complex energy system. It may also be useful to include a broad variety of stakeholders in research so as to provide a more resilient development of CCS deployment strategies.
New energy technologies may fail to make the transition to the market once research funding has ended due to a lack of private engagement to conclude their development. Extending public funding to cover such experimental developments could be one way to improve this transition. However, identifying promising research and development (R&D) proposals for this purpose is a difficult task for the following reasons: Close-to-market implementations regularly require substantial resources while public budgets are limited; the allocation of public funds needs to be fair, open, and documented; the evaluation is complex and subject to public sector regulations for public engagement in R&D funding. This calls for a rigorous evaluation process. This paper proposes an operational three-staged decision support system (DSS) to assist decision-makers in public funding institutions in the ex-ante evaluation of R&D proposals for large-scale close-to-market projects in energy research. The system was developed based on a review of literature and related approaches from practice combined with a series of workshops with practitioners from German public funding institutions. The results confirm that the decision-making process is a complex one that is not limited to simply scoring R&D proposals. Decision-makers also have to deal with various additional issues such as determining the state of technological development, verifying market failures or considering existing funding portfolios. The DSS that is suggested in this paper is unique in the sense that it goes beyond mere multi-criteria aggregation procedures and addresses these issues as well to help guide decision-makers in public institutions through the evaluation process.
One of the main objectives of impact assessments is to identify potentially significant impacts. However, determining this significance has received very limited attention as a procedural step in social impact assessments. Consequently, only limited research and documentation exists on approaches, survey tools and evaluation methods, especially with regard to participatory approaches and combined participatory-technical approaches. This study aims to address this research gap by developing and applying a joined participatory and technical impact significance evaluation. The approach is applied in a case study which analysed the livelihood impacts of the large-scale concentrated solar power plant NOORO I in Ouarzazate, Morocco.
The analysis shows that although different approaches and significance criteria must be applied when involving both local stakeholders and experts, the linked analysis offers more robust results and an improved basis for decision-making. Furthermore, it was observed in the case study that impacts affecting the social, cultural and political spheres were more often considered significant than impacts affecting the physical and material livelihood dimensions. Regarding sustainability assessments of large-scale renewable energy plants, these findings underline the importance (as for other large-scale infrastructure developments) of placing greater emphasis on the inclusion of social aspects in impact assessments.
The transformation processes towards a sustainable development are complex. How can science contribute towards new solutions and ideas leading to change in practice? The authors of this book discuss these questions along the energy transition in the building sector.
A transformative research that leaves the neutral observer position needs appropriate concepts and methods: how can knowledge from different disciplines and from practice be integrated in order to be able to explain and understand complex circumstances and interrelations? What role do complex (agent-based) models and experiments play in this respect? Which mix of methods is required in transformative science in order to actively support the actors in transformation processes?
Theses questions are illustrated by the example of the BMBF funded project "EnerTransRuhr".
Facing the uncertainty of CO2 storage capacity in China by developing different storage scenarios
(2016)
China is very active in the research and development of CO2 capture and storage technologies (CCS). However, existing estimates for CO2 storage capacity are very uncertain. This uncertainty is due to limited geological knowledge, a lack of large-scale research on CO2 injection, and different assessment approaches and parameter settings. Hence storage scenarios represent a method that can be used by policy makers to demonstrate the range of possible storage capacity developments, to help interpret uncertain results and to identify the limitations of existing assessments. In this paper, three storage scenarios are developed for China by evaluating China-wide studies supplemented with more detailed site- and basin-specific assessments. It is estimated that the greatest storage potential can be found in deep saline aquifers. Oil and gas fields may also be used. Coal seams are only included in the highest storage scenario. In total, the scenarios presented demonstrate that China has an effective storage capacity of between 65 and 1551 Gt of CO2. Furthermore, the authors emphasise a need for action to harmonise storage capacity assessment approaches due to the uncertainties involved in the capacity assessments analysed in this study.