On the parameters of performance of combined refrigeration and power plants

Combined Refrigeration and Power (CRP) plants generate power and refrigerate a thermal load simultaneously from the same fuel. The overall efficiency is a parameter based on the first law generally used to quantify the fuel saving, in the sense that a plant that has greater overall efficiency saves more fuel than others to generate the same useful energy. However, the literature shows that the overall efficiency and other parameters of performance are defined in several different ways. This heterogeneity is not desirable when considering a coherent and universally accepted parameter of performance based on the first law. In this work, some parameters found in the literature are critically analyzed in order to indicate the most proper one. The indicated parameter is then formally analyzed in order to verify its mathematical consistency. The primary energy rate is considered the most well-suited parameter based on the first law to characterize the performance of a CRP plant. © 2013 Elsevier Ltd and IIR.

Proposta de metodologia para análise de eficiência hidro-energética e ambiental: estudo de caso da agroindústria

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Development of a knowledge-based system for cogeneration plant design: Verification, validation and lessons learned

This paper presents the development of a knowledge-based system (KBS) prototype able to design natural gas cogeneration plants, demonstrating new features for this field. The design of such power plants represents a synthesis problem, subject to thermodynamic constraints that include the location and sizing of components. The project was developed in partnership with the major Brazilian gas and oil company, and involved interaction with an external consultant as well as an interdisciplinary team. The paper focuses on validation and lessons learned, concentrating on important aspects such as the generation of alternative configuration schemes, breadth of each scheme description created by the system, and its module to support economic feasibility analysis. (C) 2014 Elsevier B.V. All rights reserved.

Phytotoxicity of Tagetes erecta L. and Tagetes patula L. on plant germination and growth

This study evaluated the phytotoxic potential and antioxidant activity of Tagetes patula and Tagetes erecta, and total phenols and flavonoids of the extracts were quantified. Laboratory bioassays for both pre- and post-emergence were performed in Lactuca sativa L. seeds and in the Allium cepa seeds test. The antioxidant activity was evaluated by DPPH radical scavenging and reducing power of iron, besides total phenols and flavonoids quantification in the extracts. Thus, was observed a reduction in the mitotic index when in compared with the negative control. Was observed also a reduction the germination and development of tested seedlings and was verified a considerable antioxidant potential and presence of flavonoids and phenolic compounds in the extracts. According to these results, it is possible to conclude that T. erecta and T. patula have phytotoxic compounds that may enhance and expand their use in the management of organic agriculture, mainly in vegetables.

Within-plant isoprene oxidation confirmed by direct emissions of oxidation products methyl vinyl ketone and methacrolein

Isoprene is emitted from many terrestrial plants at high rates, accounting for an estimated 1/3 of annual global volatile organic compound emissions from all anthropogenic and biogenic sources combined. Through rapid photooxidation reactions in the atmosphere, isoprene is converted to a variety of oxidized hydrocarbons, providing higher order reactants for the production of organic nitrates and tropospheric ozone, reducing the availability of oxidants for the breakdown of radiatively active trace gases such as methane, and potentially producing hygroscopic particles that act as effective cloud condensation nuclei. However, the functional basis for plant production of isoprene remains elusive. It has been hypothesized that in the cell isoprene mitigates oxidative damage during the stress-induced accumulation of reactive oxygen species (ROS), but the products of isoprene-ROS reactions in plants have not been detected. Using pyruvate-2-13C leaf and branch feeding and individual branch and whole mesocosm flux studies, we present evidence that isoprene (i) is oxidized to methyl vinyl ketone and methacrolein (iox) in leaves and that iox/i emission ratios increase with temperature, possibly due to an increase in ROS production under high temperature and light stress. In a primary rainforest in Amazonia, we inferred significant in plant isoprene oxidation (despite the strong masking effect of simultaneous atmospheric oxidation), from its influence on the vertical distribution of iox uptake fluxes, which were shifted to low isoprene emitting regions of the canopy. These observations suggest that carbon investment in isoprene production is larger than that inferred from emissions alone and that models of tropospheric chemistry and biotachemistryclimate interactions should incorporate isoprene oxidation within both the biosphere and the atmosphere with potential implications for better understanding both the oxidizing power of the troposphere and forest response to climate change.

Design of an indirectly fired gas turbine integrated with an organic rankine cycle unit for combined heat and power production

In the last years, the European countries have paid increasing attention to renewable sources and greenhouse emissions. The Council of the European Union and the European Parliament have established ambitious targets for the next years. In this scenario, biomass plays a prominent role since its life cycle produces a zero net carbon dioxide emission. Additionally, biomass can ensure plant operation continuity thanks to its availability and storage ability. Several conventional systems running on biomass are available at the moment. Most of them are performant either in the large-scale or in the small power range. The absence of an efficient system on the small-middle scale inspired this thesis project. The object is an innovative plant based on a wet indirectly fired gas turbine (WIFGT) integrated with an organic Rankine cycle (ORC) unit for combined heat and power production. The WIFGT is a performant system in the small-middle power range; the ORC cycle is capable of giving value to low-temperature heat sources. Their integration is investigated in this thesis with the aim of carrying out a preliminary design of the components. The targeted plant output is around 200 kW in order not to need a wide cultivation area and to avoid biomass shipping. Existing in-house simulation tools are used: They are adapted to this purpose. Firstly the WIFGT + ORC model is built; Zero-dimensional models of heat exchangers, compressor, turbines, furnace, dryer and pump are used. Different fluids are selected but toluene and benzene turn out to be the most suitable. In the indirectly fired gas turbine a pressure ratio around 4 leads to the highest efficiency. From the thermodynamic analysis the system shows an electric efficiency of 38%, outdoing other conventional plants in the same power range. The combined plant is designed to recover thermal energy: Water is used as coolant in the condenser. It is heated from 60°C up to 90°C, ensuring the possibility of space heating. Mono-dimensional models are used to design the heat exchange equipment. Different types of heat exchangers are chosen depending on the working temperature. A finned-plate heat exchanger is selected for the WIFGT heat transfer equipment due to the high temperature, oxidizing and corrosive environment. A once-through boiler with finned tubes is chosen to vaporize the organic fluid in the ORC. A plate heat exchanger is chosen for the condenser and recuperator. A quasi-monodimensional model for single-stage axial turbine is implemented to design both the WIFGT and the ORC turbine. The system simulation after the components design shows an electric efficiency around 34% with a decrease by 10% compared to the zero-dimensional analysis. The work exhibits the system potentiality compared to the existing plants from both technical and economic point of view.

Plant and arthropod community sensitivity to rainfall manipulation but not nitrogen enrichment in a successional grassland ecosystem

Grasslands provide many ecosystem services including carbon storage, biodiversity preservation and livestock forage production. These ecosystem services will change in the future in response to multiple global environmental changes, including climate change and increased nitrogen inputs. We conducted an experimental study over 3 years in a mesotrophic grassland ecosystem in southern England. We aimed to expose plots to rainfall manipulation that simulated IPCC 4th Assessment projections for 2100 (+15 % winter rainfall and −30 % summer rainfall) or ambient climate, achieving +15 % winter rainfall and −39 % summer rainfall in rainfall-manipulated plots. Nitrogen (40 kg ha−1 year−1) was also added to half of the experimental plots in factorial combination. Plant species composition and above ground biomass were not affected by rainfall in the first 2 years and the plant community did not respond to nitrogen enrichment throughout the experiment. In the third year, above-ground plant biomass declined in rainfall-manipulated plots, driven by a decline in the abundances of grass species characteristic of moist soils. Declining plant biomass was also associated with changes to arthropod communities, with lower abundances of plant-feeding Auchenorrhyncha and carnivorous Araneae indicating multi-trophic responses to rainfall manipulation. Plant and arthropod community composition and plant biomass responses to rainfall manipulation were not modified by nitrogen enrichment, which was not expected, but may have resulted from prior nitrogen saturation and/or phosphorus limitation. Overall, our study demonstrates that climate change may in future influence plant productivity and induce multi-trophic responses in grasslands.

Plant diversity drives soil microbial biomass carbon in grasslands irrespective of global environmental change factors

Soil microbial biomass is a key determinant of carbon dynamics in the soil. Several studies have shown that soil microbial biomass significantly increases with plant species diversity, but it remains unclear whether plant species diversity can also stabilize soil microbial biomass in a changing environment. This question is particularly relevant as many global environmental change (GEC) factors, such as drought and nutrient enrichment, have been shown to reduce soil microbial biomass. Experiments with orthogonal manipulations of plant diversity and GEC factors can provide insights whether plant diversity can attenuate such detrimental effects on soil microbial biomass. Here, we present the analysis of 12 different studies with 14 unique orthogonal plant diversity × GEC manipulations in grasslands, where plant diversity and at least one GEC factor (elevated CO2, nutrient enrichment, drought, earthworm presence, or warming) were manipulated. Our results show that higher plant diversity significantly enhances soil microbial biomass with the strongest effects in long-term field experiments. In contrast, GEC factors had inconsistent effects with only drought having a significant negative effect. Importantly, we report consistent non-significant effects for all 14 interactions between plant diversity and GEC factors, which indicates a limited potential of plant diversity to attenuate the effects of GEC factors on soil microbial biomass. We highlight that plant diversity is a major determinant of soil microbial biomass in experimental grasslands that can influence soil carbon dynamics irrespective of GEC.

Shifts in microbial communities do not explain the response of grassland ecosystem function to plant functional composition and rainfall change

Ecosystem functioning in grasslands is regulated by a range of biotic and abiotic factors, and the role of microbial communities in regulating ecosystem function has been the subject of much recent scrutiny. However, there are still knowledge gaps regarding the impacts of rainfall and vegetation change upon microbial communities and the implications of these changes for ecosystem functioning. We investigated this issue using data from an experimental mesotrophic grassland study in south-east England, which had been subjected to four years of rainfall and plant functional composition manipulations. Soil respiration, nitrogen and phosphorus stocks were measured, and the abundance and community structure of soil microbes were characterised using quantitative PCR and multiplex-TRFLP analysis, respectively. Bacterial community structure was strongly related to the plant functional composition treatments, but not the rainfall treatment. However, there was a strong effect of both rainfall change and plant functional group upon bacterial abundance. There was also a weak interactive effect of the two treatments upon fungal community structure, although fungal abundance was not affected by either treatment. Next, we used a statistical approach to assess whether treatment effects on ecosystem function were regulated by the microbial community. Our results revealed that ecosystem function was influenced by the experimental treatments, but was not related to associated changes to the microbial community. Overall, these results indicate that changes in fungal and bacterial community structure and abundance play a relatively minor role in determining grassland ecosystem function responses to precipitation and plant functional composition change, and that direct effects on soil physical and chemical properties and upon plant and microbial physiology may play a more important role.

Power output fluctuations in large scale PV plants: one year observations with one second resolution and a derived analytic model

The variable nature of the irradiance can produce significant fluctuations in the power generated by large grid-connected photovoltaic (PV) plants. Experimental 1 s data were collected throughout a year from six PV plants, 18 MWp in total. Then, the dependence of short (below 10 min) power fluctuation on PV plant size has been investigated. The analysis focuses on the study of fluctuation frequency as well as the maximum fluctuation value registered. An analytic model able to describe the frequency of a given fluctuation for a certain day is proposed

Comparison of Chemical Absorbents Used for CO2 Capture in Coal-Fired Power Plants.

Climate change conference was hold in Copenhagen in 2009, global warming became the worldwide focus once again. China as a developing country has paid more attention for this environmental problem. In China, a large part of carbon dioxide is emitted to the atmosphere from combustion of fossil fuels in power plants. How to control emission of the greenhouse gas into atmosphere is becoming an urgent concern. Among numerous methods, CO2 capture is the hope to limit the amount of CO2 emitted into the air. The well-established method for CO2 capture is to remove CO2 by absorption into solutions in conventional equipment. Absorbents used for CO2 and H2S capture are important choice for CO2 capture technology. It is related to the cost and efficiency of plant directly and is essential to investigate the proposed CO2 and H2S absorbents.

Smoothing of PV power fluctuations by geographical dispersion

The quality and the reliability of the power generated by large grid-connected photovoltaic (PV) plants are negatively affected by the source characteristic variability. This paper deals with the smoothing of power fluctuations because of geographical dispersion of PV systems. The fluctuation frequency and the maximum fluctuation registered at a PV plant ensemble are analyzed to study these effects. We propose an empirical expression to compare the fluctuation attenuation because of both the size and the number of PV plants grouped. The convolution of single PV plants frequency distribution functions has turned out to be a successful tool to statistically describe the behavior of an ensemble of PV plants and determine their maximum output fluctuation. Our work is based on experimental 1-s data collected throughout 2009 from seven PV plants, 20 MWp in total, separated between 6 and 360 km.

Characteristic study, its identification and self-tuned approach to control hydro-power plants

The water time constant and mechanical time constant greatly influences the power and speed oscillations of hydro-turbine-generator unit. This paper discusses the turbine power transients in response to different nature and changes in the gate position. The work presented here analyses the characteristics of hydraulic system with an emphasis on changes in the above time constants. The simulation study is based on mathematical first-, second-, third- and fourth-order transfer function models. The study is further extended to identify discrete time-domain models and their characteristic representation without noise and with noise content of 10 & 20 dB signal-to-noise ratio (SNR). The use of self-tuned control approach in minimising the speed deviation under plant parameter changes and disturbances is also discussed.

A bankable method for the field testingor a CPV plant

The bankability of CPV projects is an important issue to pave the way toward a swift and sustained growth in this technology. The bankability of a PV plant is generally addressed through the modeling of its energy yield under a b aseline loss scenario, followed by an on-site measurement campaign aimed at verifying its energetic behavior. The main difference between PV and CPV resides in the proper CPV modules, in particular in the inclusion of optical lements and III-V multijunction cells that are much more sensitive to spectral variations than xSi cells, while the rest of the system behaves in a way that possesses many common points with xSi technology. The modeling of the DC power output of a CPV system thus requires several impo rtant second order parameters to be considered, mainly related to optics, spectral direct solar radiation, wind speed, tracker accuracy and heat dissipation of cells.

PV power forecast using a nonparametric PV model

Forecasting the AC power output of a PV plant accurately is important both for plant owners and electric system operators. Two main categories of PV modeling are available: the parametric and the nonparametric. In this paper, a methodology using a nonparametric PV model is proposed, using as inputs several forecasts of meteorological variables from a Numerical Weather Forecast model, and actual AC power measurements of PV plants. The methodology was built upon the R environment and uses Quantile Regression Forests as machine learning tool to forecast AC power with a confidence interval. Real data from five PV plants was used to validate the methodology, and results show that daily production is predicted with an absolute cvMBE lower than 1.3%.