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The quantification of emissions of greenhouse gases and air pollutants through the inversion of plumes in satellite images remains a complex problem that current methods can only assess with significant uncertainties. The anticipated launch of the CO2M (Copernicus Anthropogenic Carbon Dioxide Monitoring) satellite constellation in 2026 is expected to provide high-resolution images of CO2 (carbon dioxide) column-averaged mole fractions (XCO2), opening up new possibilities. However, the inversion of future CO2 plumes from CO2M will encounter various obstacles. A challenge is the low CO2 plume signal-to-noise ratio due to the variability in the background and instrumental errors in satellite measurements. Moreover, uncertainties in the transport and dispersion processes further complicate the inversion task. To address these challenges, deep learning techniques, such as neural networks, offer promising solutions for retrieving emissions from plumes in XCO2 images. Deep learning models can be trained to identify emissions from plume dynamics simulated using a transport model. It then becomes possible to extract relevant information from new plumes and predict their emissions. In this paper, we develop a strategy employing convolutional neural networks (CNNs) to estimate the emission fluxes from a plume in a pseudo- XCO2 image. Our dataset used to train and test such methods includes pseudo-images based on simulations of hourly XCO2 , NO2 (nitrogen dioxide), and wind fields near various power plants in eastern Germany, tracing plumes from anthropogenic and biogenic sources. CNN models are trained to predict emissions from three power plants that exhibit diverse characteristics. The power plants used to assess the deep learning model's performance are not used to train the model. We find that the CNN model outperforms state-of-the-art plume inversion approaches, achieving highly accurate results with an absolute error about half of that of the cross-sectional flux method and an absolute relative error of ∼ 20 % when only the XCO2 and wind fields are used as inputs. Furthermore, we show that our estimations are only slightly affected by the absence of NO2 fields or a detection mechanism as additional information. Finally, interpretability techniques applied to our models confirm that the CNN automatically learns to identify the XCO2 plume and to assess emissions from the plume concentrations. These promising results suggest a high potential of CNNs in estimating local CO2 emissions from satellite images. [ABSTRACT FROM AUTHOR]

The article examines the inversion approaches to obtain emission rates of coal-fired powerplants in Berlin, Germany using MAMAP, an airborne passive remote sensing instrument. The instrument is designed for measuring columns of methane and carbon dioxide. The approaches involve the Gaussian plume inversion and the Gaussian integral inversion method. Both methods are found capable of drawing reliable estimates of emission rates.

In this paper, a real-life renewable energy-based system is considered and the reliability function of this system is evaluated with the help of Universal Generating Function technique. The renewable energy-based system is considered from the project in Germany where the wind turbine and hydro power plant are combined. In this project the wind turbines are the world's tallest wind turbines of about 584 feet and one reservoir have the capacity of 1.6 million gallons of water. The wind turbines are set at the top of the hills and the reservoirs are allowed to be filled with river water. This paper presents a renewable energy-based system where the wind turbine and hydro power plant are combined together to produce electricity in bulk. Universal generating function technique is used to obtain the reliability function of the proposed system. Also tail signature, signature, expected cost rate, expected lifetime, and Barlow-Proschan Index are estimated. [ABSTRACT FROM AUTHOR]

Flexibility potentials are mostly provided by centrally coordinated flexibility resources such as natural-gas-fired power plants. However, the decentralization of power generation combined with the decarbonization of the sector due to the energy transition requires the exploration of new types of flexibility resources. In particular, to reduce dependence on natural-gas-fired power plants, it would be desirable to replace them with alternative flexibility resources. Therefore, the objective of this paper is to analyze, using Germany as an example, to what extent the flexibility potential of already existing battery storage systems can replace the flexibility potential of natural-gas-fired power plants. The methodology used is based on a multi-time-scale flexibility model together with an approach for temporal aggregation of flexibility potentials and two approaches for spatial aggregation of flexibility potentials. Based on the methodology and an analysis of publicly available data, a comprehensive potential analysis is carried out. This analysis shows, among others, that existing battery storage systems have a promising potential to replace a considerable number of natural-gas-fired power plants in Germany in terms of their flexibility potentials. [ABSTRACT FROM AUTHOR]

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The quantification of emissions of greenhouse gases and air pollutants through the inversion of plumes in satellite images remains a complex problem that current methods can only assess with significant uncertainties. The anticipated launch of the CO2M satellite constellation in 2026 is expected to provide high-resolution images of CO2 column-averaged mole fractions (XCO2), opening up new possibilities. However, the inversion of future CO2 plumes from CO2M will encounter various obstacles. A challenge is the CO2 plume low signal-to-noise ratio, due to the variability of the background and instrumental errors in satellite measurements. Moreover, uncertainties in the transport and dispersion processes further complicate the inversion task. To address these challenges, deep learning techniques, such as neural networks, offer promising solutions for retrieving emissions from plumes in XCO2 images. Deep learning models can be trained to identify emissions from plume dynamics simulated using a transport model. It then becomes possible to extract relevant information from new plumes and predict their emissions. In this paper, we employ convolutional neural networks (CNN) to estimate the emission fluxes from a plume in a pseudo XCO2 image. Our dataset used to train and test such methods includes pseudo images based on simulations of hourly XCO2, NO2 and wind fields near various power plants in Eastern Germany, tracing plumes from anthropogenic and biogenic sources. CNN models are trained to predict emissions from three power plants that exhibit diverse characteristics. The power plants used to assess the deep learning model's performance are not used to train the model. We find that the CNN model outperforms state of the art plume inversion approaches, achieving highly accurate results with an absolute error about half of that of the cross-sectional flux method. Furthermore, we show that our estimations are only slightly affected by the absence of NO2 fields or a detection mechanism as additional information. Finally, interpretability techniques applied to our models confirm that the CNN automatically learns to identify the XCO2 plume and to assess emissions from the plume concentrations. These promising results suggest a high potential of CNNs in estimating local CO2 emissions from satellite images. [ABSTRACT FROM AUTHOR]

This paper explores the economic implications of different contract durations in markets for on-line (primary and secondary) reserve capacity in Germany with the crucial feature of separate markets for spot energy and reserve capacity provision. The analysis is based on an equilibrium model developed by Just and Weber (Energy Econo 30:3198-3221, ) for reserve markets. It reveals the implicit trade-off for the bidders and implicit interdependencies between the reserve and the spot markets. Even if the markets are not explicitly coordinated, they are interrelated through the dispatch decisions of the power plant owners. The paper concludes that the current German reserve market design is inefficient and should be improved. The results clearly show that shorter periods (with resulting lower variations in overall electricity demand) lead to more efficient dispatch and market results. Not only prices in the reserve capacity markets are expected to be lower, but also spot market prices. As these benefits can be partially reaped by owners of large generation portfolios also under longer contract durations, it discriminates against smaller generation companies and can potentially deter market participation. Further, the paper takes a broader perspective and discusses security concerns against shorter contract durations. It is shown that the opportunity costs character of the reserve market implies sufficient incentives for supplying online reserve capacity. The concerns do not appear to be predominant and it should be possible to manage them appropriately. [ABSTRACT FROM AUTHOR]

Meeting Germany's climate targets urgently demands substantial investment in renewable energies such as hydrogen, as well as tackling industrial CO2 emissions with a strong CO2 transport infrastructure. This is particularly crucial for CO2-heavy industries such as steel, cement, lime production, power plants, and chemical plants, given Germany's ban on onshore storage. The CO2 transport network is essential for maintaining a circular economy by capturing, transporting, and either storing or utilizing CO2. This study fills gaps in CO2 pipeline transport research, examining pipeline diameters, costs, and pressure drop, and providing sensitivity analysis. Key findings show that the levelized cost of CO2 transport (LCO2T) ranges from 0.25 €/t to 55.82 €/t based on varying transport masses (1000 t/day to 25,000 t/day) and distances (25 km to 500 km), with compression costs pushing LCO2T to 33.21 €/t to 92.82 €/t. Analyzing eight pipeline diameters (150 mm to 500 mm) and the impact of CO2 flow temperature on pressure loss highlights the importance of selecting optimal pipeline sizes. Precise booster station placement is also crucial, as it significantly affects the total LCO2T. Exploring these areas can offer a more thorough understanding of the best strategies for developing cost-effective, efficient, and sustainable transport infrastructure. [ABSTRACT FROM AUTHOR]

This article investigates greenhouse gas (GHG) emissions from commercial and industrial (C&I) waste treatment considering five sector-specific waste compositions and four different treatment scenarios in Germany. Results show that the highest share of CO2-equivalent emissions can be avoided in each of the analysed industrial sectors if solid recovered fuel (SRF) is produced for co-incineration in cement kilns. Across all industries, emissions of approximately 680 kg CO2-eq. Mg−1 C&I waste can be avoided on average under this scenario. The combustion of C&I waste in waste incineration plants without any previous mechanical treatment generates the lowest potential to avoid GHG emissions with a value of approximately 50 kg CO2-eq. Mg−1 C&I waste on average in all industries. If recyclables are sorted, this can save emissions of approximately 280 kg CO2-eq. Mg−1 C&I waste while the treatment in SRF power plants amounts to savings of approximately 210 kg CO2-eq. Mg−1 C&I waste. A comparison of the treatment scenarios of the waste from these five sectors shows that waste treatment of the craft sector leads to the lowest CO2-equivalent reduction rates of all scenarios. In contrast, the treatment of waste from catering sector leads to the highest CO2-equivalent reduction rates except for direct incineration in waste incineration plants. The sensitivity analysis of the different scenarios for this paper shows that the efficiency and the substitution factor of energy have a relevant influence on the result. Changes in the substitution factor of 10% can result in changes in emissions of approximately 55 to 75 kg CO2-eq. Mg−1 in waste incineration plants and approximately 90 kg CO2-eq. Mg−1 in the case of cement kilns. [ABSTRACT FROM AUTHOR]

This article previews the IPG 2005 conference "Fulfilling Emission Directives for Large Combustion Plant," to be held in Berlin, Germany, on November 15-16, 2005. A keynoted address will be presented by Simon Critten, a senior consultant with Entec UK. There will be papers to be presented on day two which explore the best available technology on offer to bring power plant inn line with new regulations.

Considering climate change, it is essential to reduce CO 2 emissions. The provision of charging infrastructure in public spaces for electromobility – along with the substitution of conventional power generation by renewable energies – can contribute to the energy transition in the transport sector. Scenarios for the spatial distribution of this charging infrastructure can help to exemplify the need for charging points and their impact, for example on power grids. We model two kinds of demand for public charging infrastructure. First, we model the demand for public charging points to compensate for the lack of home charging points, which is derived from a previously developed and published model addressing electric-vehicle ownership (with and without home charging options) in households. Second, and in the focus of the work presented here, is the demand for public charging infrastructure at points of interest (POIs). Their locations are derived from OpenStreetMap (OSM) data and weighted based on an evaluation of movement profiles from the Mobilität in Deutschland survey (MiD, German for "Mobility in Germany"). We combine those two demands with the available parking spaces and generate distributions for possible future charging points. We use a raster-based approach in which all vector data are rasterized and computations are performed on a municipality's full grid. The presented application area is Wiesbaden, and the methodology is generally applicable to municipalities in Germany. The model is compared with three other models or model variants in a correlation comparison in order to determine the influence of certain model assumptions and input data. The identification of potential charging points in public spaces plays an important role in modeling the future energy system – especially the power grid – as the rapid adoption of electric vehicles will shift locations of electrical demand. With our investigation, we would like to present a new method to simulate future public charging point locations and show the influences of different modeling methods. [ABSTRACT FROM AUTHOR]

In this paper the German congestion management regime is analyzed and future congestion management costs are assessed given a higher share of intermittent renewable generation. In this context, cost-based re-dispatching of power plants and technical flexibility through topology optimization are considered as market-based and technical congestion management methods. To replicate the current market regime in Germany a two-step procedure is chosen consisting of a transactional spot market model and a congestion management model. This uniform pricing model is compared to a nodal pricing regime. The results show that currently congestion can mainly be managed by re-dispatching power plants and optimizing the network topology. However, congestion management costs tend to increase significantly in future years if the developments of transmission as well as generation infrastructure diverge. It is concluded that there is a need for improving the current congestion management regime to achieve an efficient long-term development of the German electricity system. [ABSTRACT FROM AUTHOR]

The availability of electric power is an important prerequisite for the development or maintenance of high living standards. Global change, including socio-economic change and climate change, is a challenge for those who have to deal with the long-term management of thermoelectric power plants. Power plants have lifetimes of several decades. Their water demand changes with climate parameters in the short and medium term. In the long term, the water demand will change as old units are retired and new generating units are built. The present paper analyses the effects of global change and options for adapting to water shortages for power plants in the German capital Berlin in the short and long term. The interconnection between power plants, i.e. water demand, and water resources management, i.e. water availability, is described. Using different models, scenarios of socio-economic and climate change are analysed. One finding is that by changing the cooling system of power plants from a once-through system to a closed-circuit cooling system the vulnerability of power plants can be reduced considerably. Such modified cooling systems also are much more robust with respect to the effects of climate change and declining streamflows due to human activities in the basin under study. Notwithstanding the possible adaptations analysed for power plants in Berlin, increased economic costs are expected due to declining streamflows and higher water temperatures. [ABSTRACT FROM AUTHOR]

The innovation is to turn bridges into energy storage units in addition to their usual function. Today the methods for mass energy storage are the pumped hydro-electric and Compressed Air Energy Storage (CAES). Whilst the former requires two reservoirs at different levels, the CAES requires only space for storing compressed air. Underground caverns have been used for CAES in power plants in Huntorf of Germany, 1978 and McIntosh of Alabama, USA, 1991 (Crotogino et al. [2]). The CAES of a power plant is to regulate the mismatching supply and demand of the grid power, so that the electricity would not be wasted when it is not needed. It is equally important to save energy as to regenerate it. To store the equivalent energy of a power plant, a sizable container is needed. Suitable underground caverns are difficult to find. Bridge structures are plentiful in many cities and their body space is voluminous. Steel pipes are the most effective structural element in storing compressed air. It can perform as a beam to carry loads. The new bridge form is to replace the girders with steel pipes that can carry loads and compressed air. The pipes provide the space for storing mass of unwanted electricity and the intermittent power output from regenerated energy sources such as wind and solar. The stored compressed air can be released to regenerate power according to the demands. The bridge is designed to operate in three levels of safety measures. With proper implementation, it will substantially reduce the energy wastage in the grid and the carbon footprint of the city, and create new industry and new jobs. This paper gives a description of the new bridge form and its applications. [ABSTRACT FROM AUTHOR]

Abstract As for other renewable energy sources in Germany like wind or photovoltaics, biogas has rapidly expanded in the past fifteen years. The installed electricity capacity for German biogas plants increased from 0.2 GW el in 2001 up to about 4.2 GW el by the end of the year 2016. This expansion has been supported in particular by the Renewable Energy Sources Act (EEG) through electricity Feed-In-Tariffs (FITs). However, major uncertainties are linked to the future capacity expansion in particular due to volatile electricity and energy crops prices. Taking into account this situation this paper analyzes possible future developments of the German biogas plant capacity up to 2030. For this purpose, a regional optimization model is employed, with the objective of determining the optimal economic development of the future biogas plants under different legal framework conditions. The base scenario with a constant energy crops cost evolution shows that the EEG 2012 framework -if maintained- would have fostered the development of agricultural plants, especially co-digestion plants valorizing energy crops and manure. The new EEG 2014 stops the expansion of energy crops mono-digestion plants, which will no longer be built due to an unprofitable situation. The German biogas market will thus face a paradigm shift and move towards the increase of biowaste and small-scale manure plants. Further scenarios quantify the impact of a strong variation of three main fundamental drivers, namely the energy crop costs, the EPEX-Peak electricity price and the biowaste valorization revenues, on future capacity developments. Based on the model results recommendations in direction of plant operators and policy-makers are formulated aiming at a more sustainable electricity production from biogas. Further work should consist in integrating the present analysis in national bioenergy models under the EEG 2017 legal framework. [ABSTRACT FROM AUTHOR]

The energy industry must change dramatically in order to reduce CO2-emissions and to slow down climate change. Germany, for example, decided to shut down all large nuclear (2022) and fossil thermal power plants by 2038. Power generation will then rely on fluctuating renewables such as wind power and solar. However, thermal power plants will still play a role with respect to waste incineration, biomass, exploitation of geothermal wells, concentrated solar power (CSP), power-to-heat-to-power plants (P2H2P), and of course waste heat recovery (WHR). While the multistage axial turbine has prevailed for the last hundred years in power plants of the several hundred MW class, this architecture is certainly not the appropriate solution for small-scale waste heat recovery below 1 MW or even below 100 kW. Simpler, cost-effective turbo generators are required. Therefore, the authors examine uncommon turbine architectures that are known per se but were abandoned when power plants grew due to their poor efficiency compared to the multistage axial machines. One of these concepts is the so-called Elektra turbine, a velocity compounded radial re-entry turbine. The paper describes the concept of the Elektra turbine in comparison to other turbine concepts, especially other velocity compounded turbines, such as the Curtis type. In the second part, the 1D design and 3D computational fluid dynamics (CFD) optimization of the 5 kW air turbine demonstrator is explained. Finally, experimentally determined efficiency characteristics of various early versions of the Elektra are presented, compared, and critically discussed regarding the originally defined design approach. The unsteady CFD calculation of the final Elektra version promised 49.4% total-to-static isentropic efficiency, whereas the experiments confirmed 44.5%. [ABSTRACT FROM AUTHOR]

The nuclear phase‐out in Germany and the decarbonization of the energy supply are accompanied by a profound upheaval of the generation fleet. The decommissioning of large power plants and their replacement by decentralized, renewable generation plants (DG) as well as storage facilities leads to a shift in generation output from power plants connected to the transmission grid to a large number of renewable and decentralized plants connected to the distribution grids. This significantly impacts the approach to restore the interconnected system after a large‐scale blackout. In order to be able to plan and instruct the dispatch of generating power from the network operator's control centres when restoring the grid after a large‐scale blackout, two aggregation and forecasting methods differentiated by voltage level are presented. For larger farms connected to the high‐voltage grid, a structure‐based node approach is chosen; for the multitude of small and microunits connected to the medium‐ and low‐voltage grids, an area‐based approach is used. These methods do provide the network operator with active power/frequency management in the medium and long‐term range. The provision of fast frequency response (FFR) by inverter‐coupled units or storage systems stabilizes the frequency in the short‐term range. In this way, the frequency nadir following a load connection can be mitigated during network restoration, which accelerates the process. This is particularly relevant against the background of the nuclear and coal phase‐out, as it can compensate for the reduction in inertia and controllable feed‐in power caused by power plant shutdowns. In a case study, it is shown that in a grid island typical for the early phase of network restoration, the inertia of a 500 MW coal‐fired power plant can almost be replaced by a battery storage system of 50 MW which provides FFR. [ABSTRACT FROM AUTHOR]

In addition to their ecological importance, rivers and streams have always been used in diverse ways by humans, resulting in the development of settlements and their connected built environments along many of the world's watercourses. During heavy rainfall, buildings, traffic infrastructure and water‐related infrastructure are exposed to potential hazards in the form of (flash) floods. In contrast to near‐natural watercourses, anthropogenically modified channels in urban areas are particularly susceptible to damage by flooding. Previous damage assessments have highlighted the need to forecast such damage to watercourses in order to identify critical areas and justify the selection and expansion of adaptation measures. Within the scope of the current study, we have developed a method based on the hydro‐morphological properties of watercourses to make transferable estimates of the economic damage potential based on ecologically‐relevant parameters. Using a scale‐specific cause‐effect analysis, we have identified characteristics of the watercourse type and adjacent structures as well as construction‐related properties of reinforcements that can increase the damage potential during flooding. In this way, we are able to show that several influencing factors determine the vulnerability of watercourses: in addition to the specific longitudinal gradient and size (macroscale) of various watercourse types, damage‐relevant boundary conditions in watercourse sections (mesoscale) and the resistance of typical bed and bank constructions are also important, reflecting the specific structural conditions. Taking rivers in Germany and the Czech Republic as case studies, in the following, we review the local identification of critical areas and describe the necessary data management. The presented "Hydro‐morphological based Vulnerability Assessment‐Concept (HyVAC)" can contribute to the flood damage prevention at watercourses by utilizing existing basic data to the greatest possible extent and thus is suitable for preliminary investigations according to the EC Flood Risk Management Directive. [ABSTRACT FROM AUTHOR]

Dynamic state and parameter estimation (DSE) plays a key role for reliably monitoring and operating future, power-electronics-dominated power systems. While DSE is a very active research field, experimental applications of proposed algorithms to real-world systems remain scarce. This motivates the present paper, in which we demonstrate the effectiveness of a DSE algorithm previously presented by parts of the authors with real-world data collected by a Phasor Measurement Unit (PMU) at a substation close to a power plant within the extra-high voltage grid of Germany. To this end, at first we derive a suitable mapping of the real-world PMU-measurements recorded at a substation close to the power plant to the terminal bus of the power plants' synchronous generator. This mapping considers the high-voltage transmission line, the tap-changing transformer and the auxiliary system of the power plant. Next, we introduce several practically motivated extensions to the estimation algorithm, which significantly improve its practical performance with real-world measurements. Finally, we successfully validate the algorithm experimentally in an auto- as well as a cross-validation. • Experimental demonstration of a dynamic state and parameter estimation method. • Utilizing phasor measurements obtained from the extra-high voltage grid of Germany. • A previously presented algorithm was improved and adjusted to real-world scenarios. • The performance was successfully demonstrated in an auto- and a cross-validation. [ABSTRACT FROM AUTHOR]

In the planning phase of district energy systems, optimization models based on mathematical programming are a widely used approach. Most optimization models determine the optimal energy system design based on a single representative year. However, this approach is unable to consider changing economic and technological boundary conditions over the system's lifetime. As a result, these one-period models fall short for districts with 5th generation district heating and cooling (5GDHC) networks, which are typically developed over long time periods and are built in multiple construction phases. In this paper, we present two multi-period optimization approaches for designing 5GDHC districts: The first approach is a forward-looking model which determines the optimal investment pathway by using a perfect foresight of future parameter developments. In the second approach, a one-period model is solved repeatedly for every investment period without knowledge of future parameter developments. Both approaches are compared to a one-period model for a real-world 5GDHC district in Germany. In comparison with a one-period design approach, the forward-looking method leads to total cost savings of up to 17 % and the sequential method of up to 11 %. By using a forward-looking model, gas-fired technologies are sized smaller while the capacity of electricity-driven technologies in the energy hub as well as photovoltaic modules and thermal energy storages in buildings increases compared to a one-period model. The case study shows that a multi-period modeling approach is an important addition to design optimization models for 5GDHC networks and can have a significant impact on the optimal design. [ABSTRACT FROM AUTHOR]

The effectiveness of the energy-only market (EOM) in providing sufficient incentives for investments is intensively discussed in Europe. While supporters claim that an improved EOM can guarantee generation adequacy, energy suppliers in particular favor the introduction of a capacity market to finance power plant investments. However, there is a lack of quantitative assessment of market design options taking into account individual decisions of market players. Existing studies mainly include a system view based on a central planner optimization. This paper on the other hand is based on an agent-based simulation model for the German electricity market. This method can explicitly incorporate individual investment decisions and aggregate them to present a holistic view of the system. Our results show that an EOM extended with a strategic reserve can incentivize investments, and guarantee supply security in a market with high share of renewable energies. However, the generation adequacy can be more easily achieved with a capacity market. Furthermore, the cost advantage of an EOM diminishes in the long-term, as scarcity prices in the EOM lead to similar system costs as with a capacity market. [ABSTRACT FROM AUTHOR]

This paper analyses the effects of regional renewable electricity self-sufficiency targets on the power system in Germany. For this purpose, an interdisciplinary approach from social sciences and energy system modelling was chosen, which allows considering qualitative factors such as public acceptance or political stability. Following the concept of context scenarios, consistent raw scenarios are generated by a cross-impact balance analysis (CIB), and the scenarios are quantified by the unit commitment and expansion cost minimisation model ENTIGRIS considering power plants, storages, and the electricity grid. This approach enables an understanding of the system framework conditions and their relationships and allows the combination of qualitative and quantitative scenario descriptors. The most important factors for setting regional self-sufficiency targets were identified through interviews. The main system effects identified are: The regional distribution of generation capacities is strongly influenced by a more demand-oriented installation of generation capacities. This leads to less grid reinforcement, but higher rates of curtailment. In all scenarios, higher utilization of the PV roof potential instead of ground mounted could be observed. The total system costs are increasing only slightly with regional self-supply targets. In general, it was found that the influence of regional self-sufficiency targets is less pronounced in scenarios that already achieve high national RES shares than in scenarios that achieve lower shares, since technology, storage and grid expansion measures are necessary anyway to achieve high RES shares. Overall, the effects here are rather small and the regional objective is not associated with major disadvantages for the system. In a future characterised by stagnation, the system can benefit from regional targeting, as higher renewable shares and lower costs can result. The main conclusion therefore is that regional target setting seem to be beneficial for the overall power system, in terms of system cost, national RE share, acceptance and CO2-emissions. [ABSTRACT FROM AUTHOR]

The political discussion to reduce the carbon footprint of Germany's electricity sector, focusing on coal, is intensifying. In this paper, we develop scenarios for phasing out lignite and hard coal power plants in Germany prior to the end of their technical lifespan ("coal-exit"). Our analysis bases upon two coal-exit instruments, the retirement of coal generation capacities and the limiting of how much aged coal power plants with high carbon intensity can be used within a year. Results show that phasing out coal in Germany would have a considerable impact on Central European electricity markets, in terms of decarbonization efforts and electricity trade. An ambitious coal-exit could avert foreseeable shortcomings in Germany's climate performance in the short-run and release additional carbon savings, thus compensating for potential shortfalls in other energy-intensive sectors by 2030. Limited emissions in the range of 27% would be shifted to neighboring countries. However, tremendous positive climate effects on European scale would result, because Germany's annual emission savings in 2030 would be substantial. Totaling 85 million tons of CO2, the overall net reduction is equivalent to 17.5% of total European emissions in 2030 without retirements of coal-firing power plants prior to the end of their technical lifespan. [ABSTRACT FROM AUTHOR]

In future energy systems with high shares of non-dispatchable renewable generation, the storage of electricity will play a key role. Today, a number of different storage options are discussed to cover the fast growing demand for storage. One of these options involves federal waterways for pumped hydro storage plants. The paper analyses the concept and the results of achievable storage potentials for Germany. The total storage potential for Germany sums up to approx. 400 MWh of which the majority can be attributed to four flight of locks which have been identified as the most suitable sites. [ABSTRACT FROM AUTHOR]

Local Energy Markets (LEMs) were recently proposed as a measure to coordinate an increasing amount of distributed energy resources on a distribution grid level. A variety of market models for LEMs are currently being discussed; however, a consistent analysis of various proposed grid tariff designs is missing. We address this gap by formulating a linear optimization-based market matching algorithm capable of modeling a variation of grid tariff designs. A comprehensive simulative study is performed for yearly simulations of a rural, semiurban, and urban grids in Germany, focusing on electric vehicles, heat pumps, battery storage, and photovoltaics in residential and commercial buildings. We compare energy-based grid tariffs with constant, topology-dependent and time-variable cost components and power-based tariffs to a benchmark case. The results show that grid tariffs with power fees show a significantly higher potential for the reduction of peak demand and feed-in (30–64%) than energy fee-based tariffs (8–49%). Additionally, we show that energy-based grid tariffs do not value the flexibility of assets such as electric vehicles compared to inflexible loads. A postprocessing of market results valuing the reduction of power peaks is proposed, enabling a compensation for the usage of asset flexibility. [ABSTRACT FROM AUTHOR]

The implementation of oxyfuel carbon capture and storage technologies in combination with use of alternative fuels comprising high biogenic shares is promoted as an attractive climate change mitigation option for the cement sector to achieve low or even negative carbon emissions. Here, we perform a prospective life cycle assessment of two state-of-the art cement plants, one in Sweden and one in Germany, under conventional and retrofitted oxyfuel conditions considering alternative fuel mixes with increasing bio-based fractions of forest residues or dedicated bioenergy crops. The analysis also considers effects of the projected changes in the electricity systems up to 2050. Retrofitting the cement plants to oxyfuel reduces climate change impacts between 74 and 91%, while with additional use of biomass as alternative fuel the cement plants reach negative emission between − 24 and − 169 gCO2eq. kgclinker−1, depending on operational condition, location, and biomass type. Additional emission reduction of − 10 (Sweden) and − 128 gCO2eq. kgclinker−1 (Germany) are expected from the decarbonization of the future electricity systems. Retrofitting the cement plants to oxyfuel conditions shows trade-offs with other environmental impacts (e.g., human toxicity, water and energy depletion), which are partially offset with projected changes in electricity systems. Our results illustrate the large climate change mitigation potential in the cement sector that can be achieved by the implementation of oxyfuel carbon capture and storage and biomass use as alternative fuel. [ABSTRACT FROM AUTHOR]

Summary: Fluctuating residual loads force lignite‐ and hard‐coal‐fired power plants to operate at technical and economical limitations. Energy storage systems (ESS) could resolve the plant‐design restrictions and enlarge the overall bandwidth of operation. Therefore, the electricity during minimum load can be stored and later fed into the grid. For this, the occurrence of minimum loads which could enable the periodic charging of ESS is analyzed at the example of lignite‐ and hard‐coal‐fired power plants in Germany. The durations of the minimum loads show marginal deviations within the considered years, as the median varies between 3 and 4 hours. The median of hard coal is 4 hours and for lignite, between 2 and 3 hours, respectively. In contrast to hard coal, the number of minimum loads of lignite increases slightly from 2016 to 2018. In total, the number and duration of minimum loads of both generation types are aligning within all transmission system areas. This is an indication that lignite power plants are increasingly affected by the merit‐order and are gradually being forced to operate more flexibly. Based on the analysis, a rough estimate of a suitable storage size for the integration of an ESS technology was derived for an exemplary power plant. [ABSTRACT FROM AUTHOR]

Abstract: Biomass cofiring in coal power plants (with thermal contributions of typically 5–20%) is an interesting option to mitigate CO2 emissions, since the additional costs are relatively minor and a secondary benefit is provided by the increased fuel flexibility. Worldwide, about 150 cofiring plants are in operation. In Germany, the electrical power potential for biomass cofiring in coal plants is about 28 TWh per annum, assuming a 10% replacement of coal combustion by biomass. In this paper, we study the economic potential of biomass cofiring in hard coal power plants in Germany. To this end, we identify suitable biomass input fuels, investment and operating costs, and the profitability of cofiring investments. In a sensitivity analysis, we check for the robustness of the results gained, and in a Monte Carlo simulation (MCS) uncertainties are explicitly taken into account. We find that both regional and international biomass supplies are relevant, and that the cost effectiveness of cofiring is strongly affected by the prices for biomass, coal and CO2 permits, while investment and operating costs only have a modest influence. According to our calculations, electrical power generation costs attributable to biomass combustion for a plant put into operation in 2020 are between 70 and 75 € MWh−1, while the average costs of biomass fuel from various sources and markets are calculated to be around 4.1 € GJ−1. [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: RWE Power, BASF and Linde entered into a cooperation in 2007 to adapt the CO2-scrubbing technology for application in power plants and to optimize significantly the technical and economic performance of CO2 post-combustion capture. All aspects of the capture process on the basis of new energy-efficient solvents developed by BASF and the improved plant technology by Linde are investigated in a pilot plant at RWE Power''s lignite-fired power station in Niederaussem, Germany. Some 250 measurements and an online-gas analysis system allow a detailed validation of the operational performance of the plant and a precise determination of the energy demand for the CO2 capture process. In extensive accompanying analysis programs, solvent stability and the formation of degradation products and emissions are investigated. Including commissioning, start up and extensive parameter studies, the pilot plant was in operation for more than 5000h with 30%-weight MEA as benchmark solvent from mid-2009 until January 2010. During this time, all aspects of the optimized process configuration were tested and compared with modeling results and literature data. This paper describes the performance validation approach on the basis of the results of the measurement program (specific energy demand: 3.5GJ/tCO2) and the investigation of the time-dependence of MEA degradation and organic acid formation under real power plant operating conditions (MEA loss: 0.3kg/tCO2; after 5000h of operation weight-related content of acetate: 1.8%, formate: 0.2% and oxalate: <0.1%). [Copyright &y& Elsevier]

Abstract: The Pebble Bed Modular Reactor (PBMR) is a First of a Kind Engineering with respect to the over 200 new innovations used in the design. The PBMR technical design is an inherited modified design from an earlier design such as the German 15MWe AVR (Arbeitsgemeinschaft Versuchs Reaktor) and the THTR-300MWe Thorium High Temperature Reactor (THTR), which ran in Germany as a test and research facility for 20 years. This paper discusses the Operator Training Simulator System for the PBMR Demonstration Power Plant. The Operator Training Simulator System will be used for operator training and licensing of plant operators. Included in the discussion is an overview of the major elements of the Operator Training Simulator System, including some of the main functional areas. [Copyright &y& Elsevier]

Today wastewater treatment plants are evaluated not only in terms of their treatment efficiency but also concerning their energy efficiency. Increasing energy efficiency can be realized either through operational optimisation or by realising an already existing potential for energy generation on-site. The main source of energy at a municipal wastewater treatment plant is the biogas produced in the anaerobic sludge digester. Studies indicate excess digester capacities of about 20% in Germany available for co-fermentation of organic substrates other than sewage sludge. This paper presents an example of a municipal wastewater treatment plant going towards an energy self-sufficient operation and even a surplus energy production as the result of an increasing co-fermentation of sludge from grease skimming tanks. In 2005 on average 113% of the electricity consumed for plant operation was generated on-site in gas engines. Co-fermentation of about 30% (related to the total dry residue input) of grease interceptor sludge in the presented case does not only effect a 4-times increased gas yield, but also an intensified 20% higher anaerobic degradation of the organic matter of the sewage sludge and thus having a positive influence not only on the energy and financial balance but also on the anaerobic sludge stabilisation with respect to the degradation degree of the organic fraction. [ABSTRACT FROM AUTHOR]

• Gas-fired power plants are often no more profitable under current market situation. • Retrofit measures that enable a more flexible operation can enhance profitability. • A real options model is proposed for the flexibility investment decision-making. • The optimal operation strategy is shown for two hourly profitability indicators. • The retrofit decision depends significantly on some of the economic parameters. The promotion of electricity from renewable energies in Germany causes difficulties in the profitable operation of many modern conventional power plants. Also, fluctuating availability of power from renewable energy sources requires flexible conventional plants, i.e. power plants which are able to react fast to these fluctuations. In this paper, we propose a model which provides some decision support tool for the operators of conventional power plants regarding investments in technical upgrades aimed at enhancing the flexible operation of these power plants. Because of the irreversible character of the investments considered we apply a real options approach to the gas-fired power plant investigated. We compare the electricity price and the spark spread as profitability indicators and sources of uncertainty, and use a simplified 3-stage definition of the power plant's operation strategy. In a case study for a combined cycle gas-fired turbine plant recently built in Germany, we find that the retrofit decisions depend strongly on economic parameters, such as the level of the operation and maintenance costs, as well as the enabled longer operation time on the maximum level. The proposed procedure can help to assess the expected future profitability role of conventional power plants, and supports the decision-making process regarding both reinvestments and optimal operation of power plants in markets with high shares of variable renewables. [ABSTRACT FROM AUTHOR]

Synthetic Natural Gas (SNG) is the most researched option for a Power-to-Fuel pathway in Germany after hydrogen, having the advantage of being compatible with the existing infrastructure. However, it is not clear under which conditions SNG is economically and environmentally advantageous compared to natural gas usage, since this is determined by a complex interplay of many factors. This study analyzes the technical, economic and environmental aspects of a pilot SNG plant to determine the key parameters for profitable and sustainable operation. The SNG plant was simulated in Aspen Plus® with CO2 from biogas production as a feedstock and with hydrogen provided by a 1 MWel electrolyzer unit. A life cycle analysis (LCA) was undertaken considering several impact categories with a special focus on global warming potential (GWP). An SNG cost of 0.33–4.22 €/kWhth was calculated, depending on factors such as operational hours, electricity price and type of electrolyzer. It was found that the CO2 price has a negligible effect on the SNG cost, while the electricity is the main cost driver. This shows that significant cost reductions will be needed for SNG to be competitive with natural gas. For the investigated scenarios, a CO2 tax of at least 1442 €/t was determined, calling for more drastic measures. Considering the global warming potential, only an operation with an emission factor of electricity below 121 g CO2-eq/kWhel leads to a reduction in emissions. This demonstrates that unless renewable energies are implemented at a much higher rate than predicted, no sustainable SNG production before 2050 will be possible in Germany. [ABSTRACT FROM AUTHOR]

The study presents the results of an integrated assessment of carbon capture and storage (CCS) in the power plant sector in Germany, with special emphasis on the competition with renewable energy technologies. Assessment dimensions comprise technical, economic and environmental aspects, long-term scenario analysis, the role of stakeholders and public acceptance and regulatory issues. The results lead to the overall conclusion that there might not necessarily be a need to focus additionally on CCS in the power plant sector. Even in case of ambitious climate protection targets, current energy policy priorities (expansion of renewable energies and combined heat and power plants as well as enhanced energy productivity) result in a limited demand for CCS. In case that the large energy saving potential aimed for can only partly be implemented, the rising gap in CO reduction could only be closed by setting up a CCS-maximum strategy. In this case, up to 22% (41 GW) of the totally installed load in 2050 could be based on CCS. Assuming a more realistic scenario variant applying CCS to only 20 GW or lower would not be sufficient to reach the envisaged climate targets in the electricity sector. Furthermore, the growing public opposition against CO storage projects appears as a key barrier, supplemented by major uncertainties concerning the estimation of storage potentials, the long-term cost development as well as the environmental burdens which abound when applying a life-cycle approach. However, recently, alternative applications are being increasingly considered-that is the capture of CO at industrial point sources and biomass based energy production (electricity, heat and fuels) where assessment studies for exploring the potentials, limits and requirements for commercial use are missing so far. Globally, CCS at power plants might be an important climate protection technology: coal-consuming countries such as China and India are increasingly moving centre stage into the debate. Here, similar investigations on the development and the integration of both, CCS and renewable energies, into the individual energy system structures of such countries would be reasonable. [ABSTRACT FROM AUTHOR]

In the not too distant future several power plants throughout Europe will have to be replaced and the decision has to be made whether to build coal-fired power plants with carbon capture and storage (CCS). In a study for the city of Kiel in northern Germany only an 800 MW coal power plant reaches a required minimum for rentability. This study looks at an additional economic and environmental evaluation of a coal plant with CCS. We find that in two out of three carbon and energy price scenarios integrated gasification combined cycle (IGCC) plants with CCS have the greatest rentability. Pulverised coal (PC) plants with CCS can only compete with other options under very favourable assumptions. Life-cycle emissions from CCS are less than 70% of a coal plant - compared with at least more than 80% when only considering direct emissions from plants. However, life-cycle emissions are lower than in any other assessed option. [ABSTRACT FROM AUTHOR]

Fifty seven (57) cloud water samples collected in 1 hr intervals during 9 cloud events in 1997 at the summit of the Brocken (altitude 1142 m) in Central Germany were analyzed for their Pb concentrations and isotopic compositions. For comparison, filter dusts of such possible emitters as power plants, cement factories, waste incinerators, cars and others were also studied. Profiles over many hours reveal changes in composition correlated with changes in the origin of the air masses. Five main groups of possible sources of the Pb can be distinguished: most important are (1) the European standard pollution ESP dominating the continent from Germany over France to Scandinavia and (2) industrial Pb (and soot from car exhausts) followed by (3) urban waste incinerators as well as (4) perhaps ores from Norilsk/Siberia, and, somewhat uncertain, (5) ores from Paleozoic European deposits. Local and daily varying anthropogenic emissions of the sources (2–5) cause scatter of the points around the ESP correlation line. In soils all these variations and individual signatures are levelled out so that specific sources of pollution cannot be identified anymore. Geogenic Pb from rocks and soils is the same as that from power plants and cement factories. It is one of the two nominal end components making up the mixture of the ESP. The less radiogenic end component of this mix which must contain Pb from very old deposits is somewhat elusive: none of the large Archaic or Proterozoic deposits could be identified. Most probably numerous sources contribute to this Pb. Pb from leaded gasoline seems to be absent or is hidden under the five components dominating the composition of the Pb in the European environment. This probably reflects phasing out of such gasoline in most European countries. The Pb in the clouds may contain a small component of old Proterozoic or even Archaic Pb, but it can also be modelled with Paleozoic Pb. [ABSTRACT FROM AUTHOR]

Energy storage, both short- and long-term, will play a vital role in the energy system of the future. One storage technology that provides high power and capacity and that can be operated without carbon emissions is compressed air energy storage (CAES). However, it is widely assumed that CAES plants are not economically feasible. In this context, a mixed-integer linear programming (MILP) model of the Huntorf CAES plant was developed for revenue maximization when participating in the day-ahead market and the minute-reserve market in Germany. The plant model included various plant variations (increased power and storage capacity, recuperation) and a water electrolyzer to produce hydrogen to be used in the combustion chamber of the CAES plant. The MILP model was applied to four use cases that represent a market-orientated operation of the plant. The objective was the maximization of revenue with regard to price spreads and operating costs. To simulate forecast uncertainties of the market prices, a rolling horizon approach was implemented. The resulting revenues ranged between EUR 0.5 Mio and EUR 7 Mio per year and suggested that an economically sound operation of the storage plant is possible. [ABSTRACT FROM AUTHOR]

This study researches the concept of underground pumped-storage hydro power plants in closed-down underground hard coal mines in Germany. After a review on how this could be realized technically, an economic feasibility analysis is presented, with a particular focus on the costs for the underground storage reservoir. The analysis is performed for different lower (i.e., underground) reservoir sizes and temporal arbitrage potentials (peak/off-peak electricity price spreads), and cost uncertainty is dealt with by means of a Monte Carlo simulation for two distinct head heights. The findings regarding costs and acceptability are compared with those of a classic (on-surface) pumped-storage hydro power plant in a mountainous area. Based on a techno-economic evaluation we conclude that under favorable conditions the realization of underground pumped-storage hydro power (UPSHP) plants seems both technically feasible and economically reasonable. More specifically, an extension of a tubular system seems the most promising option. A UPSHP plant in a mineshaft is probably slightly more expensive than a conventional one, an outcome that depends strongly on the feasible head height. However, the significant reduction of the adverse impacts on the landscape and on local residents, as well as a potentially large number of feasible sites in flat terrain, could make UPSHPs an interesting option for the future energy transition, not just in Germany but worldwide at sites where underground mining is being abandoned. [ABSTRACT FROM AUTHOR]

In Germany, the political decision to phase out nuclear and coal-fired power as well as delays in the planned grid extension are expected to intensify the current issue of high grid congestion volumes. In this article, we investigate two instruments which may help to cope with these challenges: market splitting and the introduction of a capacity mechanism. For this purpose, we carry out a comprehensive system analysis by jointly applying the demand side models FORECAST and eLOAD, the electricity market model PowerACE and the optimal power flow model ELMOD. While a German market splitting has a positive short-term impact on the congestion volumes, we find the optimal zonal delimination determined for 2020 to become outdated by 2035 resulting in new grid bottlenecks. Yet, readjusting the zonal configuration would lower the ability of the market split to provide regional investment incentives. Introducing a capacity mechanism with a congestion indicator allows allocating new power plants in regions with higher electricity demand. Consequently, we find the required congestion management to be substantially reduced in this setting. However, given the large amount of design parameters, any capacity mechanism needs to be carefully planned before its introduction to avoid new inefficiences on the market side. [ABSTRACT FROM AUTHOR]

Discusses issues related to the implementation of two European Commission Directives in the power generation industry effective January 2008. Significance of the directives in the efforts to reduce emissions of air pollutants such as greenhouse gases; Challenges faced by owners and operators of large generating power plants in compliance with the directives; Evaluation of the requirements at the Fulfilling Emission Directives for Large Combustion Plant conference in Berlin, Germany on September 6-7, 2005.

Reports on the opening of a grid connected PV power plant in Germany in November 2004. Number of modules comprising the grid; Developers of the solar power plant; Location of the PV power plant.

Reports on the opening of a new merchant coating grade precipitated calcium carbonate facility on the site of a massive power plant by Specialty Minerals Inc. in Germany. Use of waste carbon dioxide from the power plant as a raw material; Application of power and wastewater treatment; Production of 125,000 metric tons annually at regional mills.