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This paper aims to quantify the relation between real GDP, CO2 emissions, renewable and nonrenewable energy consumption, tourism development and labor force for France and Germany as these two countries are pioneer countries pushing Paris agreement within and outside the European Union. The time spans have been used for the period of 1995–2015 according to data availability. In the presence of cross-sectional dependency, several first and second-generation unit root tests confirm the unit root problem while Pedroni and Westernlund confirm the cointegration. Results reveal an inverted U-shape relation between CO2 emissions and real GDP in long run confirming the validity of environmental Kuznets curve for the group of France and Germany. Results declare that renewable energy significantly reduces carbon emissions while nonrenewable energy consumption adds to carbon emissions. Tourism sector was found helpful in carbon reduction that appeals to attract more tourists for the development of sustainable tourism industry by taking energy conservation and emissions reduction in relevant industries in the full consideration. • This paper explores the determinants of carbon emissions for France and Germany. • An inverted U-shape relation was found between carbon emissions and real GDP in long run. • Results reveal renewable energy helps in carbon emissions reduction. • Nonrenewable energy consumption was adding in CO2 emissions. • Tourism sector was found supportive in carbon reduction. [ABSTRACT FROM AUTHOR]

Short-term forecasting of electricity generation from variable renewable energy sources is not an end in itself but should provide some net benefit to its user. In the case of electricity trading, which is in the focus of this paper, the benefit can be quantified in terms of an improved economic outcome. Although some effort has been made to evaluate and to improve the profitability of electricity forecasts, the understanding of the underlying effects has remained incomplete so far. In this paper, we develop a more comprehensive theoretical framework of the connection between the statistical and the economic properties of day-ahead electricity forecasts. We find that, apart from the accuracy and the bias, which have already been extensively researched, the correlation between the forecast errors and the market price spread determines the economic implications - a phenomenon which we refer to as 'correlation effect'. Our analysis is completed by a case study on solar electricity forecasting in Germany which illustrates the relevance and the limits of both our theoretical framework and the correlation effect. • The economics of short-term electricity forecasts are studied analytically and empirically. • The value and the risk of forecast-based electricity trading are evaluated. • We find that the economics depend on the correlation of forecast errors with prices. • Hence, the most accurate forecast is not necessarily the most accurate. [ABSTRACT FROM AUTHOR]

A power system with 80% renewable energy sources (RES) requires significant provision of flexibility to balance the deviations of fluctuating solar and wind power. This paper focuses on how a smart mix of renewable generation technologies can reduce the demand for flexibility and therefore the overall system costs. To measure the demand for flexibility in systems with high RES generation, the term flexibility is defined and described using predictable indicators such as the difference between the highest and the lowest residual demand or the number of hours with negative residual load during a year. This definition is required to determine the optimal mix of RES installations. Optimization is performed for Germany based on the grid development plan of the transmission system operators. In contrast to most studies of the future energy system that foresee a further expansion of onshore wind, this paper shows that higher shares of offshore wind and, to some extent, photovoltaic are better suited to reducing the demand for flexibility and thus the cost of integrating fluctuating RES into the system. • Extended definition of flexibility demand for power systems based on renewables. • Offshore wind and photovoltaic requires less flexibility than onshore wind. • Uncertainty about the future renewable mix increases system integration costs. • Challenge: trade-off between levelized cost of generation and system integration. [ABSTRACT FROM AUTHOR]

In contemporary times, where most academic research mainly focuses on the factors of economic and environmental sustainability and emissions reduction. Yet, very little attention has been paid to the identification of the factors of renewable energy, which requires appropriate policy-level attention. Consequently, this research investigated two developed economies, i.e., Germany and the USA, from 1991 to 2021 where, the objective of the study includes using novel and robust empirical methods to test the causal relationship between renewable energy and CO2 emissions, economic growth, technological innovations and oil prices. Using the normality and unit root estimators, this study observed that non-normal data distribution, yet all the variables are stationary. Using time-series and panel cointegration tests, the results validate the cointegration between economic growth, oil prices, carbon emission, technological innovation, and renewable energy adoption in the United States whereas Germany does not show cointegration between the variables. This study employ 's the Morlet-Wavelet approaches and key findings show that all these variables have a significant role in improving renewable energy adoption in both the region. Furthermore, results show a unidirectional and bidirectional causal association between the variables via the panel-stacked Granger causality test. This study recommends effective policy ramifications concerning improved investment in technological innovation, improved low-carbon production, and diverting economic growth to renewable energy transition. Use of improved new time-series method of wavelet coherence show the key contribution in this paper with new evidence of time frequency analysis on how external variables affect renewable energy consumption in developed countries of US and Germany. The objective includes understanding the effects of CO2 emissions, economic growth, technological innovations and oil prices on renewable energy which would give evidence to policy makers and environmentalists on how developed countries should improve clean energy adoption. [ABSTRACT FROM AUTHOR]

While current climate targets demand substantial reductions in greenhouse gas emissions, the potentials to further reduce carbon dioxide emissions in traditional primary steel-making are limited. One possible solution that is receiving increasing attention is the direct reduction (DR) technology, operated either with renewable hydrogen (H 2) from electrolysis or with conventional natural gas (NG). DR technology makes it possible to decouple steel and H 2 production by temporarily using overcapacities to produce and store intermediary products during periods of low renewable electricity prices, or by switching between H 2 and NG. This paper aims to explore the impact of this decoupling on overall costs and the corresponding dimensioning of production and storage capacities. An optimization model is developed to determine the least-cost operation based on perfect-foresight. This model can determine the minimum costs for optimal production and storage capacities under various assumptions considering fluctuating H 2 and NG prices and increasing H 2 shares. The model is applied to a case study for Germany and covers the current situation, the medium term until 2030, and the long term until 2050. Under the assumptions made, direct reduced iron (DRI) storage mainly serves as long-term storage for several weeks, similar to usual balancing storage capacities. Storing H 2 , on the contrary, is used for short-term fluctuations and could balance H 2 demand in the hourly range until 2050. From an economic perspective, DRI production using NG tends to be cheaper than using H 2 in the short term, and potential savings from the flexible operation with storages are initially small. However, in the long term until 2050, NG and H 2 could achieve similar total costs if buffers are used. Otherwise, temporarily occurring electricity price spikes imply substantial increases in total costs if high shares of H 2 need to be achieved. [Display omitted] • Investigation of the use of renewable hydrogen in primary steel-making. • Analyses of flexible operation with natural gas and hydrogen in direct reduction. • Modeling optimal dimensions and minimum costs under increasing renewable shares. • Case study on optimal hydrogen and direct-reduced iron storages. [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]

Renewable energy sources (RES) can play a significant role in economic growth. This article examines the development of the wind energy market in the EU. The applicable regulations, directives, and legal acts are reviewed, and the State's role in the development of the renewable energy market is discussed. The analyses were carried out based on the available literature and Eurostat data. The authors of the paper used basic statistics to summarize the changes in wind energy and make a prognosis. The data analysis uses the Autoregressive Integrated Moving Average Method (ARIMA). The survey found that the highest average wind cumulative installed capacities were in Germany (31026 MW), Spain (18602 MW), United Kingdom (7894 MW) and France (6108 MW). Our analysis indicates that the biggest average annual installed wind capacity was in Germany (2952.6 MW), Spain (1224.5 MW) and the United Kingdom (1363.8 MW). These same countries achieved the highest average wind gross electricity production in the years 2004–17: Germany (50.9 TWh), Spain (39.3 TWh) and United Kingdom (18.9 TWh). The study finds that wind cumulative installed capacity will increase in most countries of the EU. • The European Union onshore wind energy market seems to be stable. • Wind power plays an important role as a source of energy supply. • The most important wind gross electricity producers in the EU are: Germany and Spain. • The highest increase of wind cumulative installed capacity in 2022 will be in Croatia. [ABSTRACT FROM AUTHOR]

The estimation of the electrical power output and energy yield of high concentration photovoltaic (HCPV) modules is a hard task because of the many parameters involved. In this work, we propose the usage of an Artificial Neural Networks (ANN) method to estimate the maximum power output of a FLATCON® CPV-module manufactured by Fraunhofer ISE. The advantage of the ANN is that it is a part of the Artificial Intelligence Deep Learning domain, which makes it easy to model complex systems. A detailed knowledge about the underlying module technology is not necessary. In this work, various meteorological parameters are tested as inputs of the ANN including spectral matching ratios for considering the spectral variation of the solar irradiance to evaluate the maximum power output of the HCPV module under study. Eleven scenarios considering different combinations of input parameters have been investigated. It is demonstrated that the ANN gives excellent results and allows for an accurate prediction of the HCPV module's instantaneous power output with only a few amount of data used on training the ANN. The model has been tested using the measured data set of a FLATCON® CPV-module located on the rooftop of the Fraunhofer ISE in Freiburg, Germany. The module has been electrically characterized outdoors in the period from April 2013 to April 2014. The accuracy of the proposed ANN approach was analyzed using this measurement data in combination with error metrics. It was found that the best agreement between the measured and the predicted maximum power output was achieved when using direct normal irradiance, wind speed, ambient temperature and spectral matching ratios as input. The normalized root mean square error for the maximum power output over one year is found to be between 2.2 and 4.6%. The deviation of the modelled energy yield to the measured one is in the range of 0.2–2.2%. • We use ANN method to predict the maximum power output of a FLATCON® CPV-module. • The accuracy of model used was validated through measurements and metrics errors. • The spectral effect of DNI through the use of SMRs has improved the model performance. • The knowledge of module technology is not necessary for performance prediction. • Only small amount of data are needed for performance prediction using this approach. Short Abstract: This paper uses the artificial Neural Networks model to estimate the electrical power and the energy yield of high concentration photovoltaic modules. The model has been verified using a whole year measurement data of power output of FLATCON CPV Module manufactured by Fraunhofer ISE, Germany. A best agreement between the measured and computed energy output was found trough the analysis of eleven scenarios where different input parameters were combined. [ABSTRACT FROM AUTHOR]

Geothermal Organic Rankine Cycle (ORC) power plants have tremendous worldwide potential for the utilization of low- and medium-temperature geothermal resources. However, monitoring of such a system is associated with special challenges for plant operators since the generated electrical power fluctuates strongly, which is caused by mainly two reasons: Firstly, due to the changing condensation conditions caused by air-cooled condensers, and secondly, due to the formation of scaling and fouling. Therefore, the process parameters of a geothermal ORC plant are highly variable, both in terms of diurnal and seasonal fluctuations. Considering the currently applied control software in commercial ORC plants, these fluctuations result in challenges regarding a reliable identification of potential degradation processes within the ORC process. This paper presents a novel analytical and data-based methodology for advanced monitoring of the main components of a two-staged subcritical geothermal ORC system in Southern Germany. These components are the heat exchanger, turbine and air-cooled condenser. For this purpose, operational data from more than three years were preprocessed and evaluated. For the shell-and-tube evaporator, this work applies an equation-based simulation model for the calculation of the thermal resistance due to scaling and fouling. For the turbine and condenser, polynomial functions of various degrees and different objective functions for the numerical computation of regression coefficients are examined. Regression models for three years of operation of the investigated geothermal plant were computed and compared with each other. The results indicate that there are no significant negative changes in the operational performance of most ORC main components during the investigated time period. However, negative operational changes are detected over a three-year period for one turbine of the ORC system. The detailed evaluation of the turbine data reveal a decrease of the normalized isentropic efficiency by 10%, which is significantly higher than the calculated RMSE of the developed correlations, thus indicating a clear performance reduction of the turbine. The developed advanced monitoring methodology allows the operator detailed and accurate assessment of the ORC components conditions, which can not be provided by the software solutions of the commercial ORC manufacturer. Furthermore, the presented methodology can also be applied to other thermal cycle systems with similar components, such as the Kalina Cycle. Finally, a user-friendly software application, developed with the MATLAB® App Designer, is presented. The developed software tool facilitates operators to easily and precisely monitor the operation of the main components of a geothermal ORC plant. • Novel analytical and data-based methodology for advanced monitoring of ORC systems • Equation-based simulation model for shell-and-tube evaporators of ORC systems • Data-based simulation model for turbines and condensers of ORC systems • Development of a software application for advanced monitoring of ORC systems [ABSTRACT FROM AUTHOR]

The price effect of the rising share of renewable electricity, which is called ‘merit-order-effect’, leads to noticeable changes in the German power industry and debates about the electricity market design. This paper estimates the merit-order-effect induced by variable renewable energy in the German-Austrian electricity sector with a multivariate regression model. The research focus lies on the impact of the estimated effects on the marketability of variable renewable electricity generation. The results show a systematic decline of the average market revenues for wind and photovoltaic plants in the period from January 2011 to December 2013. Current market data shows a continuation of this trend into 2016. According to the German long term goals for the use of renewables, wind and solar power will play a crucial role in the future electricity generation mix. If investments in these technologies will be profitable without any regulatory remuneration mechanisms in addition to the market revenues, depends on the further cost degression and the development of the merit-order-effect. [ABSTRACT FROM AUTHOR]

Biodiesel is an important bridging biofuel for reducing greenhouse gases (GHG). In 2015, Germany introduced a new GHG based quota scheme for biofuels. However, the use of default GHG values for rapeseed cultivation could provide inaccurate for specific regions and locations. Therefore, the aim of this paper was to use RELCA (a REgional Life Cycle inventory Approach) to assess the regional and spatial variation of GHG emissions associated with biodiesel production in Central Germany and to compare these results with the default values of the Renewable Energy Directive (RED), as well as to identify potential mitigation options for biodiesel production. The RELCA simulations indicated GHG emissions of 31.9–39.83 CO 2 eq./MJ, with emission magnitude changing between biodiesel configurations due to their locations within the CG region. In comparison with typical RED values for biodiesel, the CG simulations showed 13–31% greater mitigation potential. The results also indicated that the configuration of biomass and conversion plant needs to be assessed to develop the most appropriate mitigation strategies. Current GHG mitigation strategies are limited to the energy sector, allowing leakages within the agricultural sector. Therefore, for more spatially targeting GHG accounting to be implemented, sustainability certification should be expanded to other biomass markets. [ABSTRACT FROM AUTHOR]

Power production from biogas is quite common in Germany and other parts of the world. German biogas production, in particular, primarily uses silage corn as feedstock which is unpopular with the society because of the negative side effects. Sugar beets could be an alternative. This paper maps the aggregated results concerning the greenhouse gas (GHG) emissions and energy balances of power production from different energy crops at national level based on field experiments and all biogas plants registered in Germany. The regional feedstock production costs integrated into the objective function of a plant specific linear optimization model were calculated based on regional production circumstances and district specific yields. Different scenarios with e.g. a fixed share of sugar beets in biogas plant feedstock mix as well as yield increases due to biological and technical progress of silage corn and sugar beets were compared to a business as usual scenario in terms of their effects on GHG emissions and energy balances of power production. The results demonstrated that the GHG emissions and energy balances depend on regional production circumstances. Furthermore, forcing sugar beets into feedstock mix resulted in generally higher GHG emissions and deteriorated energy balances. [ABSTRACT FROM AUTHOR]

In this paper we investigate the location-specific attractiveness of small wind turbines (SWT) for private households. In order to assess the economic viability of an investment in SWT, we analyze a set of scenarios that incorporate different types of SWT, various storage system options, support schemes, and specific urban surroundings for the case of Germany. As urban structures substantially influence local wind speeds, and hence the potential energy yield of a turbine, the location of SWT in the urban area is crucial for their economic feasibility. We find that SWT today are only profitable under very favorable conditions, the most important parameters being prevailing wind speeds and the location's degree of urbanization. In most cases, the coupling of the SWT to a storage system is crucial for cost-effectiveness. A feed-in tariff system specifically adapted to SWT technology is found to be an important driver of diffusion. Further research needs are identified in the field of long-term performance and yield projections for SWT. Based on the findings from our study, significant SWT diffusion can only be expected, if at all, in coastal suburban and rural areas. [ABSTRACT FROM AUTHOR]

Abstract: An analysis of scientific publications on solar energy was conducted to determine whether public interest in the subject is mirrored by more intense research in the area. To this end, the research published by Spain and Germany, the two EU countries with the highest installed photovoltaic capacity, was analyzed based on Web of Science data. The results show that: solar output has risen substantially; solar research has a greater impact (measured in terms of citations) than publications on other renewables such as wind power; scientific production on solar energy is high in Germany and Spain, which together account for 51% of the total in the EU-27; the pattern of topics researched in the two countries is very similar; and their international collaboration is more intense than the world average and higher than in countries such as the USA, China or Japan. Collaboration between them is likewise intense. The main conclusion is the divergence in Germany and Spain between solar energy demand/output growth, being exponential, and the growth of research papers on the subject, which is linear. [Copyright &y& Elsevier]

Abstract: Wind energy development is booming worldwide with Germany and the United States being forerunners in installed capacity. Based on a review of relevant laws and regulations, policy, siting, and permitting documents, academic literature, and expert interviews, the paper compares the permit and environmental impact assessment (IA) policies and regulations pertaining to wind energy projects in both countries. The focus is on the potential of IAs in supporting an environmentally conscious development of wind power generation. This includes the analysis of IA regulations on the project level, strategic level impact assessment and planning processes, opportunities for public involvement and transparency of processes, and the clarity and predictability of the IA provisions. The findings suggest certain variations between both countries'' permit and IA processes for wind energy projects and further research needs, inter alia on the actual effects of strategic assessment of wind development on subsequent permitting. [Copyright &y& Elsevier]

Abstract: The development of geothermal energy application as a part of Germany’s renewable energy portfolio is a multidimensional process with fast growing improvements. In this paper basic information on geothermal application in low-enthalpy regions, such as Germany and Abu Dhabi are given. [Copyright &y& Elsevier]

Abstract: This paper develops previous research on space heating in passive houses (PH). The results reported are based on a complex theoretical model used to simulate the heating system operation in Pirmasens PH (Rhineland Palatinate, Germany). The economic feasibility of different active space heating systems based on ground thermal energy utilization was studied. Both the heating and cooling potentials of the system under real climatic conditions were investigated. On medium- and long-time operation (i.e. longer than 3–10 years), a ground-source heat pump (GSHP) configuration proves to be the best economical solution. The configuration based on a ground heat exchanger is also a better solution than conventional heating in case the operation time is longer than 20–30 years. As compared to the GSHP configuration, it has the advantage of a much lower investment cost. [Copyright &y& Elsevier]

Abstract: This paper develops previous research on passive house (PH) space heating. A simple and accurate ground heat exchanger model is developed. It is based on a numerical transient bi-dimensional approach that allows to computing the ground temperature at the surface and at various depths. The new model was integrated into the existing theoretical approach and implemented within the computer code used to simulate the heating system operation in Pirmasens PH (Rhineland Palatinate, Germany). The heating and cooling potential of the system under real climatic conditions was investigated. The energy delivered by the ground heat exchanger depends significantly on different design parameters like pipe''s depth, diameter and material. [Copyright &y& Elsevier]

This paper presents quantitative results on the economics of different levels of thermal insulation for a building envelope. Results are calculated on the basis of an example building in Germany, which is a recently built single family house with materials commonly used in light-weight constructions. Defining the cost efficiency of an energy efficient building allows one to identify solutions which are already economically viable as well as to determine specific costs of the investment in an advanced sustainable building. [Copyright &y& Elsevier]

While the success of the German Renewable Energy Sources Act in supporting the use of renewable energy sources for electricity generation is widely acknowledged, it is partly criticised for imposing unjustified extra costs on society. Based on the well established ExternE methodology for the quantification of environmental externalities the paper makes an attempt to estimate the external costs avoided in the German energy system due to the use of renewable energies for electricity generation, and to compare them against the compensation to be paid by grid operators for electricity from renewable energies according to the Renewable Energy Sources Act. In spite of existing uncertainties associated with the assessment of external costs, results clearly indicate that the reduced environmental impacts and related economic benefits do outweigh the additional costs for the compensation of electricity from renewable energies. [Copyright &y& Elsevier]