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Abstract 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 Social acceptance of innovative technologies is a key element of an effective transition towards more sustainable energy economies. However, innovative technologies like genetic modification also tend to spark controversy and backlash. So far, efforts to inform the public about any risks and benefits of novel technologies not only have struggled to foster acceptance but also neglect the interdependent foundations of consumer decision-making. Through a controlled experiment with German consumers (N = 322), we examine whether consumer support and rejection of genetic modification in bioenergy crops is influenced by the statements and actions of actors throughout the supply chain. In specific, we show that the decision of energy companies to sell and support GM bioenergy positively impacts consumer decisions to support. To ensure that decision outcomes were specifically impacted by the expressions of corporate actors, we controlled for the content and valence of information by random assignment to one of three treatments in which participants received positive, negative, or balanced (risks and benefits) information. We find that negative messaging diminished support and increased rejection relative to the other treatments. Lastly, the statements and actions of corporate actors also exerted an indirect influence on consumer decisions through their interactions with social trust and labels, e.g. greater support by farmers had a positive influence only for those who are more generally trustworthy. Given these results, we anticipate more attention to the importance of actors such as farmers and energy companies for the social acceptance of novel technologies in the energy sphere.

The leafy seadragon certainly is among evolution's most "beautiful and wonderful" species aptly named for its extraordinary camouflage mimicking its coastal seaweed habitat. However, limited information is known about the genetic basis of its phenotypes and conspicuous camouflage. Here, we revealed genomic signatures of rapid evolution and positive selection in core genes related to its camouflage, which allowed us to predict population dynamics for this species. Comparative genomic analysis revealed that seadragons have the smallest olfactory repertoires among all ray-finned fishes, suggesting adaptations to the highly specialized habitat. Other positively selected and rapidly evolving genes that serve in bone development and coloration are highly expressed in the leaf-like appendages, supporting a recent adaptive shift in camouflage appendage formation. Knock-out of bmp6 results in dysplastic intermuscular bones with a significantly reduced number in zebrafish, implying its important function in bone formation. Global climate change-induced loss of seagrass beds now severely threatens the continued existence of this enigmatic species. The leafy seadragon has a historically small population size likely due to its specific habitat requirements that further exacerbate its vulnerability to climate change. Therefore, taking climate change-induced range shifts into account while developing future protection strategies.

Cogeneration of heat and electricity is an important pillar of energy and climate policy. To plan the production and distribution system of combined heat and power (CHP) systems for residential heating, suitable methods for decision support are needed. For a comprehensive feasibility analysis, the integration of the location and capacity planning of the power plants, the choice of customers, and the network planning of the heating network into one optimization model are necessary. Thus, we develop an optimization model for electricity generation and heat supply. This mixed integer linear program (MILP) is based on graph theory for network flow problems. We apply the network location model for the optimization of district heating systems in the City of Osorno in Chile, which exhibits the “checkerboard layout” typically found in many South American cities. The network location model can support the strategic planning of investments in renewable energy projects because it permits the analysis of changing energy prices, calculation of break-even prices for heat and electricity, and estimation of greenhouse gas emission savings.

Ammonia increases buffer capacity of methanogenic medium in mesophilic anaerobic reactor thus increasing the stability of anaerobic digestion process. Optimal ammonia concentration ensures sufficient buffer capacity while not inhibiting the process. It was found out in this paper that this optimum depends on the quality of anaerobic sludge under investigation. The optimal concentrations for methanogens were 2.1, 2.6 and 3.1 g/L of ammonia nitrogen in dependence on inoculum origin. High ammonia nitrogen concentration (4.0 g/L) inhibited methane production, while low ammonia nitrogen concentration (0.5 g/L) caused low methane yield, loss of biomass (as VSS) and loss of the aceticlastic methanogenic activity. It was found out that negative effect of low ammonia nitrogen concentration on biomass is caused not only by low buffer capacity but also by insufficiency of nitrogen as nutrient. It was also found out that anaerobic sludge with higher ammonia nitrogen concentration (4.2 g/L) tolerates even concentration of volatile fatty acids (160 mmol/L) which causes inhibition of the process with low ammonia nitrogen concentration (0.2 g/L).

Abstract Amorphous and microcrystalline silicon single layers and p–i–n solar cells were produced dynamically using an inline deposition system called “line source”. A highly uniform deposition of thin-film silicon layers with layer-thickness variations of less than ±5% was achieved. Amorphous and microcrystalline silicon single junction solar cells were dynamically fabricated with initial efficiencies of 8.3% and 6.3%, respectively. The dynamic deposition rate of these solar cells is 6.75 nm m/min in case of a-Si:H and 3.3 nm m/min for μc-Si:H. In this work it will be shown that an enhancement of the deposition rate up to 15.6 nm m/min during the i-layer deposition of a-Si:H solar cells has only a weak negative influence on the initial efficiencies of the cells. Further on, the effect of substrate velocity on solar cell characteristics of a-Si:H solar cells is investigated. Finally, a productivity estimation of the line source concept is presented.

Abstract Solutions containing hydrofluoric acid (HF), hydrochloric acid (HCl), and hydrogen peroxide (H2O2) were investigated as novel acidic, NOx-free etching mixtures for texturing of monocrystalline silicon wafers. High etch rates of up to 13.3 nm s−1 were observed at room temperature, which are comparable to the etch rates of KOH-IPA solutions. The silicon surface was investigated by scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM), indicating pyramidal textures for diamond wire and SiC-slurry sawn as well as saw-damage etched (polished) wafers. Non-stirred baths generate random pyramidal structures while constantly stirred solutions generate novel random inverted pyramidal surface structures. The light trapping efficiency of wafers etched by the HF-HCl-H2O2 solutions was compared by UV/vis-reflectivity measurements to KOH/i-propanol specimens indicating lower reflectivities for the HF-HCl-H2O2-treated samples. Using the ‘wafer ray tracer’ (pvlighthouse.com) the light absorption properties of monomodal and random inverted pyramid structures were simulated and compared to well-known random and monomodal textures for PERC solar cells, clearly indicating the best performance for random inverted pyramids. Besides, simulation of a PERC solar cell on a roof top at our university was performed, indicating improved performance, especially for random inverted pyramid textures.

Given the significant amount of installed generation-capacity based on wind power, and also due to current economic downturn, the subsidies and incentives that have been widely used by wind-power producers to recover their investment costs have decreased and are even expected to disappear in the near future. In these conditions, wind-power producers need to develop offering strategies to make their investments profitable counting solely on the market. This paper proposes a multi-stage risk-constrained stochastic complementarity model to derive the optimal offering strategy of a wind-power producer that participates in both the day-ahead and the balancing markets. Uncertainties concerning wind-power productions, market prices, demands' bids, and rivals' offers are efficiently modeled using a set of scenarios. The conditional-value-at-risk metric is used to model the profit risk associated with the offering decisions. The proposed model is recast as a tractable mixed-integer linear programming program solvable using available branch-and-cut algorithms. Results of a case study are reported and discussed to show the effectiveness and applicability of the proposed approach.