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Abstract The objective of this work is to evaluate the surge characteristics of an axial compressor operating under surge conditions, by using a hybrid BDF/harmonic balance method. During a surge event, a large amount of backflow occurs in the compressor. Consequently, the airflow oscillates along the axial direction at a low frequency, which can considerably damage the compressor. In this paper, a numerical investigation is performed to examine the effects of the system volume and average mass flow on the surge characteristics of a transonic high speed single stage axial compressor (stage 35) designed and evaluated at the NASA Glenn Center. The results show that the oscillation frequency of the airflow in the compressor generally ranges from 14.32–26.04 Hz during surge conditions, and both the system volume and average mass flow considerably influence the surge characteristics. For a constant average mass flow, as the system volume decreases, the oscillation frequency of the airflow in the compressor increases slightly, while the oscillation amplitude of the exit static pressure decreases significantly, and the maximum static pressure at the outlet remains nearly constant. In the case of a constant system volume, with the decrease in the average mass flow, the oscillation frequency of the airflow in the compressor gradually decreases, and the oscillation amplitude of the exit pressure increases significantly. With a further decrease in the average mass flow, the oscillation frequency stabilizes at a certain point and does not change thenceforth. Furthermore, the surge frequency obtained using the numerical method shows a same tendency with the Helmholtz frequency, but there is a considerable difference between them.

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.

AbstractChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.

Abstract Emissions and efficiency of a pellet boiler (40 kW) at nominal load were compared with emissions and efficiency at reduced load, while fired with six biomass pellets. The pellets include reed canary grass ( Phalaris arundinacea ), pectin waste from citrus shells ( Citrus reticulata ), sunflower husk ( Helianthus annuus ), peat, wheat straw ( Triticum aestivum ) and wood pellets. The measurements of emissions comprised of carbon monoxide (CO), nitrogen oxides (NO x ), sulphur oxides (SO x ) and flue dust mass concentrations (using DIN plus and isokinetic sampling techniques). Emissions varied as a function of operational loads, for each type of pellets. The CO emissions were insignificant with reed canary grass (RCG), citrus pectin waste (CPW) and straw pellets at nominal load, however, at reduced load same pellets emitted 1.9, 4.0 and 7.4 times higher CO than wood pellets, respectively. Peat pellets emitted maximum CO at nominal load (4221.1 mgNm −3 , 12.6 times higher than wood pellets) however; at reduced load CO emission was insignificant. The highest NO x emissions were reported with CPW, which were 3.4 and 4.6 times higher than wood pellets at nominal load and reduced load, respectively. Dust emissions were highest with sunflower husk and lowest with RCG pellets, at both operational modes. The best performance was reported with wood pellets, followed by RCG and pectin pellets, however, wood pellets combustion emitted 1.7 and 2.0 times higher dust DIN plus than RCG at nominal and reduced loads, respectively. Not only fuel specific combustion optimization but also operational load specific optimization is essential for efficient use of agro-pellets in this type of boilers.

A reduced-order, “grey-box” model of an active distribution network, intended for dynamic simulations of the transmission system, is derived. The network hosts inverter-based generators as well as static and motor loads, whose dynamic parameters are affected by uncertainty. This issue is addressed using Monte-Carlo simulations. The parameters of the equivalent are adjusted to match as closely as possible the average of the randomized responses, while their dispersion is accounted for through the weights of the weighted least-square minimization. A procedure is used to remove from the identification the parameters with negligible impact. To avoid over-fitting, the equivalent is tuned for multiple large-disturbance simulations. A recursive procedure is used to select the smallest possible subset of disturbances involved in the least-square minimization. Simulation results with a 75-bus MV test-system are reported. They show that the equivalent is able to reproduce with good accuracy the discontinuous controls of inverter-based generators, such as reactive current injection and tripping.

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.

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.

Virtually developing of automotive power systems is currently experiencing increasing significance due to elevated vehicular electrification and automation of driving functions. The analysis of system-inherent disturbances requires accurate simulation models for both short-term transients or long-term driving cycles. The electrical behavior of electromechanical actuators such as brake or steering highly depends on the mechanical environmental interaction being dependent many variables. This contribution presents a methodology to extract abstracted models of machine driven actuators on the basis of an electric steering. The dynamics of a complex electromechanical model are investigated using pulse response analysis for differentiated operation points. The obtained model reduction is implemented in a frequency-dependent equivalent circuit.