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The escalating demand for renewable energy solutions and the imperative for efficient energy storage mechanisms have catalyzed the evolution of Power-to-X (PtX) technologies. Germany has the most PtX projects, accounting for 44% of all projects that have been reported. PtX encompasses a spectrum of processes engineered to convert surplus renewable energy into versatile energy carriers or chemical commodities, such as hydrogen, methane, or synthetic fuels. The Paramount to this domain is to synergistically harness renewable energy sources and hydrogen carriers to curtail waste and bolster sustainability. Central to achieving this synergy is the effective control of PtX processes, ensuring optimal performance, cost efficiency, and seamless integration within existing energy frameworks. This paper delves into the control processes and environmental prerequisites within the PtX landscape, elucidating key challenges, and strategies within this dynamic realm. While providing an initial overview of fundamental PtX process chains, this paper accentuates the critical role of geographical considerations. Subsequently, it conducts a thorough analysis of equipment modeling challenges, addressing performance metrics, operational requisites, and capital investments, particularly focusing on methanol and hydrogen production and storage. Through holistic examination, this paper endeavors to delineate the evolving landscape of PtX control processes and conditions, advancing our understanding of this expanding field. [Display omitted] • Comprehensive overview of PtX control process, challenges, strategies, and advancements. • Overview of PtX process chains and geographical conditions. • Analysis of equipment modeling challenges for methanol and hydrogen. • Addressing crucial storage challenges in PtX system. • Exploration of diverse influences on PtX control processes. [ABSTRACT FROM AUTHOR]

The emerging energy transition is particularly described as a move towards a cleaner, lower-carbon system. In the context of the global shift towards sustainable energy sources, this paper reviews the potential and roadmap for hydrogen energy as a crucial component of the clean energy landscape. The primary objective is to present a comprehensive literature overview, illuminating key themes, trends, and research gaps in the scientific discourse concerning hydrogen production and energy policy. This review focuses particularly on specified geographic contexts, with an emphasis on understanding the unique energy policies related to renewable energy in Brazil, Austria, and Germany. Given their distinct social systems and developmental stages, this paper aims to delineate the nuanced approaches these countries adopt in their pursuit of renewable energy and the integration of hydrogen within their energy frameworks. Brazil exhibits vast renewable energy potential, particularly in wind and solar energy sectors, positioning itself for substantial growth in the coming years. Germany showcases a regulatory framework that promotes innovation and technological expansion, reflecting its highly developed social system and commitment to transitioning away from fossil fuels. Austria demonstrates dedication to decarbonization, particularly through the exploration of biomethane for residential heating and cooling. [ABSTRACT FROM AUTHOR]

In Germany, there are over 32,000 schools, representing great potential for climate protection. On the one hand, this applies to educational work, as understanding the effects of climate change and measures to reduce GHG emissions is an important step to empower students with knowledge and skills. On the other hand, school buildings are often in bad condition, energy is wasted, and the possibilities for using renewable energies are hardly used. In our "Schools4Future" project, we enabled students and teachers to draw up their own CO2 balances, identify weaknesses in the building, detect wasted electricity, and determine the potential for using renewable energies. Emissions from the school cafeteria, school trips, and paper consumption could also be identified. The fact that the data can be collected by the students themselves provides increased awareness of the contribution made to the climate balance by the various school areas. The most climate-friendly school emits 297 kg whilst the school with the highest emissions emits over one ton CO2 per student and year. Our approach is suitable to qualify students in the sense of citizen science, carry out a scientific investigation, experience self-efficacy through one's own actions, and engage politically regarding their concerns. [ABSTRACT FROM AUTHOR]

The energy sector faces a pressing need for significant transformation to curb CO2 emissions. For instance, Czechia and Germany have taken steps to phase out fossil thermal power plants by 2038, opting instead for a greater reliance on variable renewable energy sources like wind and solar power. Nonetheless, thermal power plants will still have roles, too. While the conventional multistage axial turbine design has been predominant in large-scale power plants for the past century, it is unsuitable for small-scale decentralized projects due to complexity and cost. To address this, the study investigates less common turbine types, which were discarded as they demonstrated lower efficiency. One design is the Elektra turbine, characterized by its velocity compounded radial re-entry configuration. The Elektra turbine combines the advantages of volumetric expanders (the low rotational speed requirement) with the advantages of a turbine (no rubbing seals, no lubrication in the working fluid, wear is almost completely avoided). Thus, the research goal of the authors is the implementation of a 10 kW-class ORC turbine driving a cost-effective off-the-shelf 3000 rpm generator. The paper introduces the concept of the Elektra turbine in comparison to other turbines and proposes this approach for an ORC working fluid. In the second part, the 1D design and 3D–CFD optimization of the 7 kW Elektra turbine working with Hexamethyldisiloxane (MM) is performed. Finally, CFD efficiency characteristics of various versions of the Elektra are presented and critically discussed regarding the originally defined design approach. The unsteady CFD calculation of the final Elektra version showed 46% total-to-static isentropic efficiency. [ABSTRACT FROM AUTHOR]

The widely recognised Energiewende, ("energy transition") in Germany has lost its original momentum. We therefore address the question of how the transition process to a new energy system can be reignited. To do so, we developed the "5Ds approach", which lays the groundwork for a process analysis and the identification of important catalysts and barriers. Focusing on the five major fields required for the energy transition, we analyse the effects of: (1) Decarbonisation: How can efficiency and renewable energies be expanded successfully? (2) Digitalisation: Which digital solutions facilitate this conversion and would be suitable as sustainable business models? (3) Decentralisation: How can potential decentralised energy and efficiency opportunities be developed? (4) Democratisation: How can participation be strengthened in order to foster acceptance (and prevent "yellow vest" protests, etc.)? (5) Diversification of service: Which services can make significant contributions in the context of flexible power generation, demand-side management, storage and grids? Our paper comes to the conclusion that German policy efforts in the "5D" fields have been implemented very differently. Particularly with regard to democratisation, the opportunities for genuine participation among the different social actors must be further strengthened to get the Energiewende back on track. New market models are needed to meet the challenges of the energy transition and to increase the performance of "5D" through economic incentives. [ABSTRACT FROM AUTHOR]

This paper aims to provide a holistic analysis of the role of hydrogen for achieving greenhouse gas neutrality in Germany. For that purpose, we apply an integrated energy system model which includes all demand sectors of the German energy system and optimizes the transformation pathway from today's energy system to a future cost-optimal energy system. We show that 412 TWh of hydrogen are needed in the year 2045, mostly in the industry and transport sector. Particularly, the use of about 267 TWh of hydrogen in industry is essential as there are no cost-effective alternatives for the required emission reduction in the chemical industry or in steel production. Furthermore, we illustrate that the German hydrogen supply in the year 2045 requires both an expansion of domestic electrolyzer capacity to 71 GW H2 and hydrogen imports from other European countries and Northern Africa of about 196 TWh. Moreover, flexible operation of electrolyzers is cost-optimal and crucial for balancing the intermittent nature of volatile renewable energy sources. Additionally, a conducted sensitivity analysis shows that full domestic hydrogen supply in Germany is possible but requires an electrolyzer capacity of 111 GW H2. • 412 TWh of hydrogen demand in a greenhouse gas neutral Germany in the year 2045. • Hydrogen usage is crucial for defossilization of chemical and steel industry. • 47% of hydrogen is imported from other European countries and Northern Africa. • 71 GW H2 of electrolyzer capacity in Germany with flexible operation. • 35 TWh of hydrogen storage in salt caverns for security of supply. [ABSTRACT FROM AUTHOR]

High level of greenhouse gases emission in fossil fuels has induced a significant transition from conventional energy sources to renewable energy. However, using renewable energy in electricity grids has limitations, such as intermittency and lack of efficient energy storage. This paper focuses on constructing the quanto options contract to help renewable energy producers hedge the risk against low photovoltaic (PV) production and electricity prices. To achieve our objective, we first model the interday PV power production with a combination of a deterministic and stochastic model. We analyse empirical data for daily solar production in three operators in Germany ranging from 1 January 2016 to 31 December 2020. We discovered that all estimated parameters of the deterministic process are highly significant. Meanwhile,we use an autoregressive (AR) process to describe the random behavior in the production. The results demonstrated that AR(2) is suitable enough to explain its stochastic factor. For the error terms analysis, we observed a clear sign of seasonal heteroskedasticity supported by the left skewed density. In addition, we observed a clear seasonal pattern in the squared error terms, where we suggest using seasonal variance and skewed normal distribution to describe its dynamic. As for an application, we embed the PV model in the power price modeling. We found that AR(3) process is sufficient to explain the price behavior and that normal distribution best fits the error terms. Using the suggested PV and power price model, we construct the quanto options contract for renewable energy producers using Monte Carlo simulations. We discovered that the electricity price payoffs are consistent throughout the year, whereas PV and quanto options payoffs vary greatly depending on the season. The quanto options price result shows that the prices vary during four seasons, with the highest variation in July. [ABSTRACT FROM AUTHOR]

Renewables are the greener substitute for the conventional polluting sources of generating energy. For their successful integration into the power grid, accurate forecasts are required. In this paper, we report the lessons acquired from our previous works on generating time-series ARIMA-based forecasting models for renewables. To this end, we considered a consistent dataset spanning the last four years. Assuming four different performance metrics for each of the best ARIMA-based models of our previous works, we derived a new optimal model for each month of the year, as well as for the two different methodologies suggested in those works. We then evaluated the performance of those models, by comparing the two methodologies: in doing so, we proposed a hybrid methodology that took the best models out of those two methodologies. We show that our proposed hybrid methodology has improved yearly accuracy of about 89.5% averaged over 12 months of the year. Also, we illustrate in detail for the four years under study and each month of the year the observed percentage of renewables and its corresponding accuracy compared to the generated forecasts. Finally, we give the implementation details of our open-source REN4KAST software platform, which provides several services related to renewables in Germany. [ABSTRACT FROM AUTHOR]

The energy crisis in Europe in 2022 and its consequences have brought changes to approaches towards the issue of energy security, energy policy, and the ability to react to crisis phenomena in the energy market in a short period of time. European countries that are dependent on Russian fossil fuels have faced numerous dilemmas and challenges in 2022. This paper aims to analyse the instruments and energy policies introduced as the reactions of European countries, specifically with the examples of Poland and Germany, to the ongoing fossil fuel crisis in the context of a short period. Due to the specificity of the energy market, the countries' energy policies mainly concern long- and medium-term goals. In 2022, there was an unprecedented situation in which many European countries had to make significant changes to their fossil fuel imports quickly. We analyse and evaluate how two European countries that are heavily reliant on imported energy resources responded in a short time to the necessity of modifying their patterns of fossil fuel supply and demand. The results of our research are models that illustrate both countries' reactions to the disturbances in the energy market during the initial months of the energy crisis. As part of the research, we conducted an analysis of the energy mix of Poland and Germany, their import energy dependency, and self-sufficiency. We then compared them with the short-term energy policies of both countries. As a result, we elaborate on a comparative analysis of the models of Poland's and Germany's responses to the crisis. The research also assesses the similarities and differences in the response models in Poland's and Germany's short-term energy security policies. The results of our research may help, in the future, to choose the available short-term instruments in the energy policy of countries in the face of a sudden need resulting from disruptions in supply chains. The article contributes to the future discussion on renewed national and regional energy security, as well as efficiency concepts. Our research findings could be valuable in selecting appropriate short-term energy policy tools for countries during supply chain disruptions. This article provides significant input for future deliberations on enhancing national and regional energy security, and also efficiency strategies. [ABSTRACT FROM AUTHOR]

Temporally and spatially resolved data on wind power generation are very useful for studying the technical and economic aspects of this variable renewable energy at local and regional levels. Due to the lack of disaggregated electricity data from onshore and offshore turbines in Germany, it is necessary to use numerical simulations to calculate the power generation for a given geographic area and time period. This study shows how such a simulation model, which uses freely available plant and weather data as input variables, can be developed with the help of basic atmospheric laws and specific power curves of wind turbines. The wind power model is then applied to ensembles of nearly 28,000 onshore and 1500 offshore turbines to simulate the wind power generation in Germany for the years 2019 and 2020. For both periods, the obtained and spatially aggregated time series are in good agreement with the measured feed-in patterns for the whole of Germany. Such disaggregated simulation results can be used to analyze the power generation at any spatial scale, as each turbine is simulated separately with its location and technical parameters. This paper also presents the daily resolved wind power generation and associated indicators at the federal state level. [ABSTRACT FROM AUTHOR]

Integrating renewable energies into the electricity grid is a challenge that requires an in-depth investigation. This paper presents a model of the day-ahead electricity market, including wind and photovoltaic (PV) generators, and contingency analysis. The comprehensive day-ahead marketing model is designed as a modular structure so that the individual modules can be easily modified in the future. First, the day-ahead electricity marketing of an electricity grid with and without renewable energies is studied. A market model solves the problem of unit commitment and economic dispatch. A grid model was used to calculate the power flow of the branches and the grid losses. Congestions in the branches were handled by redispatching. For this purpose, the generators were redispatched using mixed-integer linear programming and the power transfer distribution factor. A contingency analysis, investigating the outage of one branch, was applied by using the line outage distribution factor. The redispatch process was operated with these calculated increased power flows, which need to be handled by the grid to achieve N-1 security. The simulations were carried out using 30-bus 118-bus systems. Historic wind speed and solar radiation data of Germany were used as input data for renewable energy production. The load data of the 118-bus system were generated based on a standard load profile from Germany. The results show that both systems were able to meet the demand without violation of the grid capacity during normal conditions, with and without renewable energies. However, when applying the contingency analysis, an outrageous amount of load curtailment is needed. [ABSTRACT FROM AUTHOR]

Recently, challenge-oriented innovation policy has become increasingly popular in political and scientific discussions. However, the extent to which such a challenge-based thinking has entered regional policy making is relatively unclear. This paper examines the scope of the regional level in promoting challenge-based innovation, focusing on the recent renewable energy innovation policy in Schleswig-Holstein, Germany. The results show that while regional innovation policy in Schleswig-Holstein aims to address several structural and transformational systemic failures, many other problems and challenges remain, as they are beyond the capacity of a single region to address. Based on this analysis, we draw four conclusions. First, similar to many other structurally weak regions, policymakers in Schleswig-Holstein are struggling with some of the same key challenges that the policy was originally designed to address. Second, multi-scalar governance and inter-scalar coordination are essential for managing regional sustainability transitions. Third, challenge-driven innovation policy is an extension of, rather than a replacement for, conventional regional innovation policy. Finally, environmental and economic goals should be well balanced in challenge-driven regional innovation policy design. [ABSTRACT FROM AUTHOR]

The large-scale integration of renewable energy sources requires flexibility from power markets in the sense that the latter should quickly counterbalance the renewable supply variation driven by weather conditions. Most power markets cannot (yet) provide this flexibility effectively as they suffer from inelastic demand and insufficient flexible storage capacity or flexible conventional suppliers. Research accordingly shows that the volume of renewable energy in the supply system affects the mean and volatility of power prices. We extend this view and show that the level of wind and solar energy supply affects the tails of the electricity price distributions as well and that it does so asymmetrically. The higher the supply from wind and solar energy sources, the fatter the left tail of the price distribution and the thinner the right tail. This implies that one cannot rely on symmetric price distributions for risk management and for valuation of (flexible) power assets. The evidence in this paper suggests that we have to rethink the methods of subsidizing variable renewable supply such that they take into consideration also the flexibility needs of power markets. [ABSTRACT FROM AUTHOR]

Legislative efforts for renewables-based energy decarbonisation hinge upon the support and commitment from different stakeholders holding often conflicting positions regarding disruptive processes of socio-technical transformation. However, the evolving acceptance of market actors on the policy-driven promotion of renewables over time remains under-scrutinised. Simultaneously, despite growing attention to power and politics in sustainability transitions, limited efforts remain invested for elucidating the political-economic nature of the market-based selection environments they are operationalised through, highlighting the need for a more systematic comprehension of the "politics of selection". To address these shortcomings, this paper provides a more refined understanding of the role of policy-driven markets and its participating agents in facilitating/hindering innovation diffusion and broader (system-wide) sustainability transitions. To do so, it showcases a longitudinal case study of the politics underlying Germany's evolving feed-in policy support framework for orchestrating a market-mediated diffusion of renewables (1980s–2020). Based on policy analysis and semi-structured interviews, the study traces the changing acceptance and ensuing strategic (re)actions of market actors to the emergence and evolution of Germany's market for electricity from renewable energy sources. Results show how different market participants effectively shape the selection environments they operate in by proactively contesting/deluding the design features of the support policies organising their economised relations (e.g., market entry conditions, exchange rules, remuneration levels, pricing schemes, etc.). Such efforts are undertaken through legal means and market framing strategies targeting the affordability of policy support costs, coupled with the strategic use of policy instrumentation as a vehicle to further expand/retain their market shares to the detriment of competing actors. [ABSTRACT FROM AUTHOR]

In this paper, a multi-step framework to design flexible power-to-methane processes is presented. The approach considers all crucial parts of the power-to-methane process, including the renewable energy source. The aim is to provide a design that allows for feasible operation under the fluctuating conditions induced by the renewable energy source at all times. For each part of the process, the operating windows are analyzed and optimized under different site-specific constraints, and recommendations for actions regarding the technical implementations are provided. The impact of the carbon dioxide source is scrutinized, and subsequent scheduling optimization is performed to determine necessary storage capacities. The framework is demonstrated on two carbon dioxide availability scenarios where the renewable energy source is a wind turbine coupled to a polymer exchange membrane electrolyzer that produces hydrogen, which is then converted to methane in a fixed-bed reactor. The results show that the feasible operation of the system strongly depends on the site-specific conditions. In particular, the availability of carbon dioxide impacts the flexibility of the methanation reactor. When the stochiometric ratio between hydrogen and carbon dioxide cannot be sustained, the operating window of the reactor deteriorates significantly. However, it is shown that appropriate integration and scheduling of storage capacities debottlenecks the reactor and enables the utilization of all electricity generated by the wind turbine. • A framework for the design of flexible power-to-methane systems is introduced. • Optimization approaches for each step of the framework are provided. • A dynamic optimization approach for storage integration is given. • The impact of the carbon dioxide provision flexibility is investigated. • The framework is tested in a case study with an onshore wind turbine in Germany. [ABSTRACT FROM AUTHOR]

The flexible coupling of sectors in the energy system, for example via battery electric vehicles, electric heating or electric fuel production, can contribute significantly to the integration of variable renewable electricity generation. For the implementation of the energy system transformation, however, there are numerous options for the design of sector coupling, each of which is accompanied by different infrastructure requirements. This paper presents the extension of the REMix energy system modelling framework to include the gas sector and its application for investigating the cost-optimal design of sector coupling in Germany's energy system. Considering an integrated optimisation of all relevant technologies in their capacities and hourly use, a path to a climate-neutral system in 2050 is analysed. We show that the different options for flexible sector coupling are all needed and perform different functions. Even though flexible electrolytic production of hydrogen takes on a very dominant role in 2050, it does not displace other technologies. Hydrogen also plays a central role in the seasonal balancing of generation and demand. Thus, large-scale underground storage is part of the optimal system in addition to a hydrogen transport network. These results provide valuable guidance for the implementation of the energy system transformation in Germany. • Combination of all options for flexible sector coupling has high synergy potential. • Flexible hydrogen production is a key enabler of renewable energy system integration. • Hydrogen storage and transport networks are important future energy infrastructures. • Climate targets require a timely acceleration of sector coupling implementation. [ABSTRACT FROM AUTHOR]

Prediction of weather is a main goal of atmospheric science. Its importance to society is growing continuously due to factors such as vulnerability to natural disasters, the move to renewable energy sources, and the risks of climate change. But prediction is also a major scientific challenge due to the inherently limited predictability of a chaotic atmosphere, and has led to a revolution in forecasting methods as we have moved to probabilistic prediction. These changes provide the motivation for Waves to Weather (W2W), a major national research program in Germany with three main university partners in Munich, Mainz, and Karlsruhe. We are currently in the second 4-yr phase of our planned duration of 12 years and employ 36 doctoral and postdoctoral scientists. In the context of this large program, we address what we have identified to be the most important and challenging scientific questions in predictability of weather, namely, upscale error growth, errors associated with cloud processes, and probabilistic prediction of high-impact weather. This paper presents some key results of the first phase of W2W and discusses how they have influenced our understanding of predictability. The key role of interdisciplinary research linking atmospheric scientists with experts in visualization, statistics, numerical analysis, and inverse methods will be highlighted. To ensure a lasting impact on research in our field in Germany and internationally, we have instituted innovative programs for training and support of early-career scientists, and to support education, equal opportunities, and outreach, which are also described here. [ABSTRACT FROM AUTHOR]

Many countries plan to decarbonise their energy systems by increasing energy efficiency and expanding the use of renewable energy sources (RES). Such actions require significant investments in new energy infrastructures. While people are generally accepting of these infrastructures, opposition sometimes arises when these developments are sited at close proximity to people's residences. Therefore, it is important to understand what actually drives people's preferences for spatial proximity to different energy infrastructure technologies. This study examines the factors influencing people's proximity preferences to a range of different energy technologies using a cross-country econometric analysis of the stated preference data from an unprecedented survey conducted on nationally representative samples of the population in Ireland, the U.S. and Germany. The survey involved more than 4,500 participants in total. This paper presents the data and selected results from a generalised ordered logit model for each energy technology surveyed. These are; wind turbines, solar power technology, biomass power plant, coalfired power plant and natural gas power plant. The results show that, in general, German and Irish citizens are willing to accept energy infrastructures at smaller distances to their homes than their U.S. counterparts. Moreover, attitudinal factors are found to shape people's preferences more consistently than any of the socio-demographic characteristics. [ABSTRACT FROM AUTHOR]

Electricity grids are crucial for the energy transition. Despite its importance for renewable energy, the literature on grid ownership at the local level in Germany lacks up-to-date knowledge. Existing research does not state the extent to which municipalities own distribution system operators (DSOs). Based on a novel dataset on grid operators in 10,800 German municipalities, this paper can provide for the first time an overview of the current ownership of electricity distribution companies. Although the electricity infrastructure is decentralised, ownership remains centralised in the hands of Germany's leading energy companies and concentrated in affluent population centres. • Novel dataset on 10,800 German municipalities' grid operators. • In-depth overview of municipal and non-municipal DSOs in Germany. • Incumbent energy firms continue to lead German DSO market amid grid transition. • Disparities in utility ownership persist between East and West Germany. • Municipal DSOs more common in larger cities and industrial southern Germany. [ABSTRACT FROM AUTHOR]

• Economic efficiency of various imported e-fuels for heavy-duty transport in different scenarios for the year 2035 has been evaluated. • E-fuels considered are Fischer-Tropsch diesel, methanol, and hydrogen transported as cryogenic liquid or in form of liquid organic hydrogen carriers. • We develop a mathematical model that covers the entire process chain. • The choice of production site has a major impact on the mobility cost using the respective fuels. The transformation of economies worldwide towards climate neutrality will require not only renewable electricity but also climate-neutral energy carriers such as hydrogen and its derivatives. The production cost of electric fuels (e-fuels) are to a large extent driven by the energy-intensive electrolytic water splitting. The option of producing e-fuels in highly industrialized countries, as Germany, competes with production at international locations, with excellent conditions for renewable energies and thus very low levelized cost of green hydrogen and its derivatives. In this paper, we examine the economic efficiency of various imported e-fuels that are under consideration in different scenarios for the year 2035: Fischer-Tropsch diesel, methanol, and hydrogen transported as cryogenic liquid or in form of liquid organic hydrogen carriers. We develop a mathematical model that covers the entire process chain, from the production of the e-fuels at various excellent locations worldwide to the energetic utilization of the fuels in a heavy duty vehicle. We find that the choice of production site has a major impact on the mobility cost using the respective fuels. Under the selected boundary conditions and assumptions, methanol, cryogenic hydrogen, and liquid organic hydrogen carriers are the most favourable options for all seven locations examined. Which e-fuel is cheapest varies with the production site. Especially in case of diesel, the levelized cost of electricity determined by the full load hours of the applied renewable energy source have a huge impact. An LOHC-based system is shown to be less dependent on electricity source compared to other technologies due to its comparatively low electricity consumption. The length of the transportation route and the price of the filling station infrastructure, however, increase mobility cost for LOHC and LH 2. [ABSTRACT FROM AUTHOR]

With its strong ties to the European Union, Germany is well-positioned to assist many countries achieve sustainability goals. Therefore, the main objective of this paper is to examine how renewable energy intensity and renewable energy share improve environmental sustainability, the load capacity factor (LCF) in Germany from 1970 to 2018. To this end, the study uses the autoregressive distributed lag model, with the effects of the Kyoto Protocol included as a dummy variable. The study contributes to the literature by considering and testing for the first time the impact of renewables on the LCF in terms of intensity and share for Germany. The empirical results show that (i) economic growth lowers the LCF faster in the early stages of economic development than in later periods; therefore, the environmental Kuznets curve hypothesis is valid in Germany. (ii) A 1% upsurge in renewable energy intensity has no statistically significant effect on the LCF, while a 1% rise in the share of renewables in the total energy mix increases LCF by 0.48%. (iii) A 1% rise in urbanization reduces the LCF by 6.52%. (iv) A 1% augment in human capital enhances the LCF by 3.49%. These outcomes suggest that the German government should use human capital development and increasing the share of renewable energy as policy instruments to achieve the sustainable development goals. [Display omitted] • The EKC hypothesis is valid for Germany. • Renewable energy intensity has no influence on the load capacity factor. • A higher renewable share in the energy mix is associated with an improvement in LCF. • Human capital plays a key role in solving environmental challenges. • The urbanization process has a devastating effect on the environment. [ABSTRACT FROM AUTHOR]

Over the last five decades, there have been several phases of interest in the so-called hydrogen economy, stemming from the need for either energy security enhancement or climate change mitigation. None of these phases has been successful in terms of a major market development, mainly due to the lack of cost competitiveness and partially due to technology readiness challenges. Nevertheless, a new phase has begun very recently, which despite holding original objectives has the new motivation to be fully green, i.e. based on renewable energy. This new movement has already initiated bipartisan cooperation of some energy importing countries and those with abundant renewable energy resources and supporting infrastructure. One key challenge in this context is the diversity of pathways for the (national and international) export of non-electricity renewable energy. This poses another challenge, that is the need for an agnostic tool for comparing various supply chain pathways fairly while considering various techno-economic factors such as renewable energy sources, hydrogen production and conversion technologies, transport, and destination markets, along with all associated uncertainties. This paper addresses the above challenge by introducing a probabilistic decision analysis cycle methodology for evaluating various renewable energy supply chain pathways based on the hydrogen vector. The decision support tool is generic and can accommodate any kind of renewable chemical and fuel supply chain option. As a case study, we have investigated eight supply chain options composed of two electrolysers (alkaline and membrane) and four carrier options (compressed hydrogen, liquefied hydrogen, methanol, and ammonia) for export from Australian ports to three destinations in Singapore, Japan, and Germany. The results clearly show the complexity of decision making induced by multiple factors, and that the preferred supply chain combination (electrolyser technology, green energy carrier) in terms of least cost strongly depends on whether the expected levelized cost of hydrogen (ELCOH) or the expected levelized cost of energy (ELCOE) is used as a decision criterion. For instance, with ELCOH for the case study, under the given input parameters, the Ammonia combination with alkaline electrolysers (AE-NH 3) becomes the least-cost supply chain option for Singapore, Japan, and Germany with values of 8.60, 8.78 and 9.63 $/kgH 2 , respectively. This leaves liquid hydrogen (with alkaline electrolysers) as the second-best supply chain route, with ELCOH values of 9.05, 9.39 and 10.70 $/kgH 2 , respectively. However, with ELCOE, methanol (with alkaline electrolysers) becomes the preferred supply chain path for all destinations, and liquid hydrogen (with alkaline electrolysers) keeps its place as the second-best alternative. [ABSTRACT FROM AUTHOR]

Schools play an important role in achieving climate protection goals, because they lay the foundation of knowledge for a responsible next generation. Therefore, schools as institutions have a special role model function. Enabling schools to become aware of their own carbon footprint (CF) is an important prerequisite for being able to tap the substantial CO2 reduction potential. Aiming at the direct involvement of students in the assessment process, a new assessment tool was developed within the Schools4Future project that gives students the opportunity to determine their own school's CF. With this instrument the CO2 emissions caused by mobility, heating and electricity consumption as well as for food in the school canteen and for consumables (paper) can be recorded. It also takes into account existing renewable energy sources. Through the development of the tool, not only a monitoring instrument was established but also a concrete starting point from which students could take actions to reduce Greenhouse Gas (GHG) emissions. This paper presents the tool and its methods used to calculate the CF and compares it with existing approaches. A comparative case study of four pilot schools in Germany demonstrates the practicability of the tool and reveals fundamental differences between the GHG emissions. [ABSTRACT FROM AUTHOR]

This paper identifies socioeconomic factors that are supposed to impact the investment decision of private households in Germany regarding small-scale solar PV (photovoltaic) systems. In 2022, the last nuclear power plant will phase out and the end of coal-fired power plants is fixed for 2038. Thus, the legislator is mandated to foster the addition of renewable energy capacities to close the gap fossil fuels and nuclear power leaves. Some share of the renewable energies could be from private households that mainly invest in small-scale solar PV systems. To stimulate investments, it is necessary to identify factors that are important for the investment decisions of private households. Within this paper, secondary socioeconomic data for the period from 2009–2018 was compiled. In order to identify the latent variables, a factor analysis was conducted. The results state five factors that are supposed to impact the investment decisions of the prosumer in Germany. [ABSTRACT FROM AUTHOR]

The intensive electrification of the automotive sector means that the energy system must be able to adapt to the current market situation. The increase in energy demand is a major factor associated with electric vehicles. The study analyzed the operation of a grid-connected facility operating a vehicle fleet providing transport services in the region Halle/Saale, Germany. Measurement data were used in the analysis, including global positioning system data of the vehicles and technical data, including average fuel consumption on a given route section, daily load demand of the industrial facility, and energy generation from photovoltaics. This paper shows the impact of using a battery electric vehicles (BEVs) fleet in the load distribution for the industrial facility considered. The NEDC energy consumption profile for the Nissan e-NV200 were used in this study. Furthermore, the paper presented simulation results allowing one to determine the usage potential, energy demand, and consumption of EVs using real data, reliably representing the processes related to EV daily use. The measurement data were captured using available specialized equipment: Dako-Key (GPS data), PV power generation (Siemens 7KM PAC4200), and load (Janitza UMG 604-Pro) in September, 2018. On this basis, it is possible to identify the effects and variations in load on the power grid during the replacement of combustion vehicle fleets used currently by EVs for the provision of transport services. Three models were presented, making it possible to calculate changes in energy demand for each scenario. In the first model, EVs were charged exclusively from the distribution network. In the second, the energy generation from a renewable source was considered and the possibility of compensating the energy demand of the vehicles from this source was demonstrated. In the third model, the daily load profile and the period of maximum load in the electricity grid were considered. The results are presented in graphical and tabular form. Finally, the potential of using an EV fleet to increase the functionality of a modern industry object was determined and discussed. Based on data for the adopted scenarios, electrification of transport can increase demand for energy by 40.9% for individual enterprises. The electrification of the automotive sector will increase the instantaneous energy demand of businesses, forcing the integration of renewable energy sources during designing new invests. [ABSTRACT FROM AUTHOR]

• Low reservoir amplitudes in run-of-river hydropower enable extensive grid balancing. • 1 MW of hydropower can facilitate grid integration of up to 11.6 MW of wind or PV. • Potentials for negative balancing services significantly higher than for positive. • Providing balancing services reduces overall energy production. • Nevertheless balancing services can increase the total incomes. The increasing shares of wind energy and photovoltaics in many countries challenge the energy systems in a twofold way. On one hand, there is an increased need for balancing energy in order to compensate abrupt changes in load or power generation. On the other hand, fossil plants being important providers of balancing services are gradually driven out of the system creating a need for renewable substitutes. Due to strict requirements on the upstream water level regime German run-of-river (ROR)-hydropower has until now remained largely unused for providing positive balancing services. However, in this paper we present a novel optimized operation scheme allowing ROR-plants to exactly keep their production schedule and, in addition to that, provide positive and negative balancing services even under these constraints. Our simulations on an exemplary power plant with a very low head show that huge unused balancing power potentials can be expected for ROR-hydropower in Germany enabling a multiplication of fluctuating renewable energy sources. Next to these potentials under current market conditions, this paper elaborates the economic and ecologic aspects of balancing operation. [ABSTRACT FROM AUTHOR]

In recent years, wind power has emerged as an important source of renewable energy. When onshore and offshore wind farm regions are connected to the grid for power generation, consistent multi-location short-term wind power predictions are extremely valuable in terms of assuring the power system's safety, sustainability, and economic operation. An abrupt variation in wind power generation influences the efficiency of the regional power grid. This makes accurate short-term forecasting essential for high-level planning and scheduling of power grids. To address the issue, this paper presents two variants of recurrent neural networks (RNN): gated recurrent unit (GRU) and long short-term memory (LSTM) models considering substantially better prediction accuracy to forecast a country-wide (Germany) wind power data for daily (t + 1), and multi-step (t + 3, t + 5 , and t + 12) hours ahead. In addition, wind velocities [m/s] measured at heights of 2, 10, and 50-m (above ground level) are exploited as an essential characteristic among the available input variables and evaluated each feature subset based on four training divisions (80-20%, 70-30%, 60-40%, and 50-50%) and compared the results with ARIMA and SVR approaches in the literature. The findings reveal that the RNN-GRU model not only can achieve higher predicting accuracy but also has a faster learning speed over long sequences. • Multivariate analysis of hourly wind power predictions is carried out. • The prediction model integrated RNN-GRU and RNN-LSTM. • A countrywide dataset for Germany in 2016 is employed for the forecast. • Accuracy and computational efficiency were used to evaluate the performance of proposed time series models. • Comparison with reported models and ablation strategies supports the design of individual modules in RNN-GRU. • RNN-GRU with multi-step/multi-location demonstrated potential for large-scale wind farm applications. [ABSTRACT FROM AUTHOR]

• State of the art of the Power-to-X options is discussed. • Power-to-X definitions and options are discussed. • Particular attention is given to Power-to-X options in Germany. • Multicriteria evaluation of the Power-to-X options is conducted. Hydrogen is a versatile energy carrier studied and considered to substitute fossil fuels since the seventies after the first energy crisis. Later, a second hydrogen wave due to another crisis occurred. Currently, the world is discussing the third hydrogen wave, for which, unlike the other two waves, its driving force is not the lack of fossil fuels but the imminent climate change. The hydrogen economy is expected to answer the energy storage challenges created by fluctuating electricity generation from renewable energy sources and provide a solution for the decarbonization of high energy demand sectors and the synthesis of many chemicals. Today, governments around the globe are committed to scale-up the hydrogen economy; more than 30 nations have launched a National Hydrogen Plan or Strategy. The hydrogen economy functions with a Power-to-X (PtX) versatile system. Power-to-X ("X" as an energy carrier) refers to hydrogen produced via a carbon-free process and the further storage of this element either as pure hydrogen or converted to an energy carrier that can easily be stored, transported, and used, such as ammonia, methanol and other liquid organic hydrogen carriers. This paper conducts a literature review of the political commitment regarding the hydrogen economy, the status of PtX technologies, and development worldwide. It also compares four different scenarios for green hydrogen storage using various criteria. Power-to-Ammonia, Power-to-Methanol, Power-to-Hydrogen blended with natural gas, and Power-to-Liquid hydrogen are evaluated. Conclusively, the four concepts have their advantages and disadvantages, depending on the specific application and related scenario. Germany sponsors most of the research associated with PtX and is the country with the most advanced PtX projects. Therefore, Germany was chosen as a study case for multicriteria evaluation of PtX technologies. Power-to-Ammonia appears to be the best solution. [ABSTRACT FROM AUTHOR]

The advancing energy transition is leading to a constantly increasing number of prosumers and active participants in the energy system. Local energy markets are considered a promising approach to coordinate those active participants efficiently, increase acceptance among the population, and decrease grid expansion costs. However, energy models and markets do not consider heterogeneous user preferences which are considered crucial for the progressing energy transition. Therefore, this paper proposes new auction-based local energy market models that consider user preferences and users' willingness to pay a premium for heterogeneous energy qualities. In order to account for the unknown and stochastic user behavior in such a new market setting, we simulate and compare existing and newly developed auction-based clearing algorithms with an unbiased Monte Carlo method and evaluate whether they fulfill pre-defined key characteristics. Based on the results, we conclude and identify a clearing algorithm that verifiably satisfies user preferences, considers willingness to pay a premium, increases local coverage of electricity, maintains individual rationality, and computational tractability. The presented clearing algorithms enable new market designs that can help to increase acceptance and accelerate the expansion of renewable energies. All market models and simulations are publicly available in the open-source repository lemlab. Future research will validate the presented results in a field trial in Germany with 20 households. • New auction-based clearing algorithms for community-based local energy markets. • New bidding format for local energy markets. • Verifiable satisfaction of user preferences. • Incorporation of willingness-to-pay a premium for heterogeneous energy qualities. • Increasing local coverage of electricity supply and demand. [ABSTRACT FROM AUTHOR]

[Display omitted] • We simulate renewables pathways under different support phase-out scenarios. • We extend an investment algorithm by preferences and calibrated returns. • Our improved algorithm incorporates more heterogeneity resulting in stronger effects. • Further auction support is necessary for most capacity targets in the case countries. • Countries should coordinate policy changes due to cross-border effects. Support schemes have been central to the expansion of renewable electricity globally and in the European Union. As technologies mature, individual member states may decide to phase out these policies. While previous research has shown that such policy changes affect investors' decisions, we investigate how they affect pathways and electricity prices by simulating investment decisions in an agent-based model in two case countries. This paper contributes and applies an adapted investment decision algorithm that incorporates empirically observed technology and return preferences and is calibrated by return observations. The new algorithm yields more refined and stronger effects compared to its predecessor. Results show that the phase-out of auctions in Germany and the Netherlands slows down their deployment of renewable capacity by up to ∼60% and ∼35%, respectively. With the exception of photovoltaics and onshore wind projects in the Netherlands, the targeted capacities can only be reached by continuing support in both countries. Furthermore, ending support in a large country like Germany leads to higher electricity prices and fosters a market-driven but insufficient capacity expansion in smaller neighbours like the Netherlands. As the electricity grids in many countries are strongly interconnected, such cross-border effects are of international relevance. Our findings suggest that continued auctions may be necessary and that countries should coordinate policy changes to stay on track for meeting their renewables targets. [ABSTRACT FROM AUTHOR]

In August 2020, Germany and Ukraine launched an energy partnership that includes the development of a hydrogen economy. Ukraine has vast renewable energy resources for "green" hydrogen production and a gas transmission system for transportation instead of Russian natural gas. Based on estimates by Hydrogen Europe, Ukraine can install 8000 MW of total electrolyser capacity by 2030. For these reasons, Ukraine is among the EU's priority partners concerning clean hydrogen, according to the EU Hydrogen strategy. Germany plans to reach climate neutrality by 2045, and "green" hydrogen plays an important role in achieving this target. However, according to the National Hydrogen Strategy of Germany, local production of "green" hydrogen will not cover all internal demand in Germany. For this reason, Germany considers importing hydrogen from Ukraine. To govern the production and import of "green" hydrogen, Germany and Ukraine shall introduce legal regulations, the initial analysis of which is covered in this study. Based on observation and comparison, this paper presents and compares approaches while exploring the current stage and further perspectives for legal regulation of hydrogen in Germany and Ukraine. This research identifies opportunities in hydrogen production to improve the flexibility of the Ukrainian power system. This is an important issue for Ukrainian energy security. In the meantime, hydrogen can be a driver for decarbonisation according to the initial plans of Germany, and it may also have positive impact on the operation of Germany's energy system with a high share of renewables. [ABSTRACT FROM AUTHOR]

Due to higher penetration of renewable energy sources, grid reinforcements, and the utilization of local voltage control strategies, a significant change in the reactive power behavior as well as an increased demand for additional reactive power flexibility in the German power system can be predicted. In this paper, an application-oriented reactive power management concept is proposed, which allows distribution system operators (DSO) to enable a certain amount of reactive power flexibility at the grid interfaces while supporting voltage imitations in the grid. To evaluate its feasibility, the proposed concept is applied for real medium voltage grids in the south of Germany and is investigated comprehensively in different case studies. The results prove the feasibility and reliability of the proposed concept, which allows the DSO to control the reactive power exchange at grid interfaces without causing undesired local voltage problems. In addition, it can be simply adjusted and widely applied in real distribution grids without requiring high investment costs for complex information and communication infrastructures. As a significant contribution, this study provides an ideal bridging solution for DSOs who are facing reactive power issues but have no detailed and advanced monitoring system for their grid. Moreover, the comprehensive investigations in this study are performed in close cooperation with a German DSO, based on a detailed grid model and real measurement data. [ABSTRACT FROM AUTHOR]