• Energy Research
• engineering and technology close
• BR close
• CL close

The technological development and the low rate of effective improvement of the energetic efficiency in Brazil demonstrate the necessity of work in the area. The aim of this paper is to explore energy efficiency with emphasis in lighting, though an energy audit, which conducted a comprehensive analysis on two aspects, types lamps and the lighting quality. The work achieved a reduction in lighting consumption of 60%, totaling a saving value of R$ 91.747,93 over the life of the system. The investment was paid over a period of one year and two months, it is show a much higher profit than using the investment capital in another financial market application and its rate of return calculated at 7,66% per month and a Payback estimated return one year and eight months.

Sugarcane biorefineries, despite their contribution to sustainable transportation fuels and mitigation of carbon emissions in the mobility sector, produce a large amount of carbon dioxide in their conversion processes. According to the Paris climate agreement, a carbon neutral energy system has to be launched in the years to come, and in this scenario, greenhouse gases emission free industrial processes and alternative carbon sources will be needed. Therefore, this paper presents the evaluation of carbon mass balance of a typical Brazilian ethanol mill to better understand its potential for energy and carbon yield improvement. Due to the fact that Brazilian sugarcane mills are evolving from first generation to integrated first and second generation plant, four different scenarios were analysed. For a first generation plant without (S-I) and with conversion of straw to electricity (S-II) and for the integrated plant (S-III), results of carbon mass balance showed that the harvested sugarcane carbon was mainly converted into CO2 and in a smaller proportion into ethanol. In the modelled cases S-I to S-III the conversion of sugarcane carbon into CO2 and ethanol ranged from 41% to 53% and 17%-22%, respectively. Because this carbon amount in the CO2 flows provides an interesting platform to both increase the bioenergy produced and the harvested carbon-to-fuels ratio, a fourth scenario (S-IV) that studies the integration of power-to-gas (PtG) technologies into the mill was also considered. PtG can increase the sugarcane fuels energy content from 9.3 kW/ha to 33.6 kW/ha using 1361.3 MWe of electricity, increasing the amount of sugarcane carbon transformed into sugarcane based fuels to 54% and converting CO2 into a high value added product.

In response to the intensification of eco-friendly routes as a strategy to access compounds of interest, extraction based on hydrothermal technologies is an efficient method to obtain high yields of compounds present in lignocellulosic materials. Accordingly, this study investigated the effects of the combination of ultrasonic pretreatments (energy density, 1.23 × 103-37.6 × 103 J/cm3; reaction time, 15 and 60 min) and subcritical water hydrolysis (SWH) (temperature, 220°C; flow rate, 10-30 mL/min; and reaction time, 0.5-15 min) on sugar yield profile from residual biomass of rice, soybean, and pecan. A characterization of the sugars present in the hydrolyzed solutions by high-performance liquid chromatography (HPLC) and a physicochemical evaluation of biomasses by Fourier-transform infrared spectroscopy (FT-IR) was performed. The highest yield reported were 23.8/100 g biomass, 14.4/100 g biomass, and 6.0/100 g biomass for pecan shell, rice shell, and soybean straw, respectively. Cellobiose, glucose, xylose, and arabinose were quantified by the HPLC, as well as inhibitors and organic acids. FT-IR indicated the compositions of the fresh and pretreated samples. Appropriately, the combined application of ultrasonic and SWH methods supported the valorization and optimization of high potential materials generated in agricultural processing.

Considerando a importância do conhecimento das paisagens, a possibilidade que ele abre para uso de forma racional dos recursos naturais, o estudo teve como objetivos identificar as características geoambientais, delimitar e mapear as unidades ambientais do município de Juazeiro do Piauí, bem como avaliar as potencialidades e limitações em cada uma das unidades mapeadas. O município estudado localiza-se no Território de Desenvolvimento dos Carnaubais, nordeste do estado do Piauí. A metodologia utilizada no trabalho empregou a abordagem integrada associada a técnicas de campo, laboratório e cartografia digital, fato que possibilitou a efetuação o mapeamento das unidades ambientais, considerando os aspectos topo-morfológicos. Desse modo, foram mapeadas as seguintes unidades geoambientais: Superfície Pedimentada Dissecada em Morros/Colinas e Formas Tabulares de Juazeiro do Piauí, Patamares Estruturais da Bacia do rio Poti e o Vale da Bacia do rio Poti. Ressalta-se que as referidas unidades apresentam potencialidades e limitações distintas para fins de exploração racional dos recursos naturais, dentre as potencialidades pode-se destacar as extensas áreas planas a suave onduladas, solos desenvolvidos (Latossolos), baixa severidade climáticas em alguns trechos; ao passo que as limitações dizem respeito a áreas com relevo forte ondulado a montanhoso, solos jovens (Neossolos Litólicos). O estudo foi relevante, pois permitiu conhecer de forma integrada a área do município de Juazeiro do Piauí, contribuindo para o planejamento e o uso sustentável dos mesmos no município.

The design of energy systems usually requires technical, economical and environmental analysis. However, the growth of systems failure due to unpredictable low-probability external events makes the consideration of resilience in this design also important. Although there is no standard metric for resilience quantification yet, it is known that it should consider system configuration, operation time and total or partial energy generation during and after the event, as well as the components repair probability and time. A proposal for resilience quantification in four cogeneration plants was previously developed based on components stochastic failures and verification of their consequences in the plant energy generation. The present work aims to continue the development of this metric by including in its calculation the repair probability of the components, their repairing time and the plant downtime during the repair, essential parameters for resilience quantification. Two new metrics are proposed and simulations with 0, 50% and 75% of repair probability of the components are made in software CLIPS. One of the metrics is able to evaluate the influence of repairment in system resilience, while the other one predicts plant downtime during operation. The metrics point to S#2 as the most resilient system and S#3 as the most affect by repairing.

Abstract The energy consumption of spouted bed is an important issue that has been studied from various aspects. In order to investigate the energy consumption of the equipment, several experiments of drying of sorghum bicolor [Sorghum bicolor (L) Moench] were conducted and the results were evaluated looking for the energy performance of the spouted bed. A methodology that takes into account the mechanical energy necessary to maintain the spout regime on the global energy efficiency was proposed and the performance was determined based on the drying efficiency, energy efficiency, and specific energy consumption with and without the term corresponding to the mechanical contribution. This methodology permits a more rigorous evaluation of the energy performance of drying equipment. The percentage increase of the specific energy consumption due to inclusion of the mechanical energy was greater at higher loads and at lower temperatures, demonstrating that this term represented a significant portion of the energy consumption of the process.

In this study, a methodology for automatic recognition of multiple simultaneous types of partial discharges (PDs) in hydro-generator stator windings was proposed. All the seven PD sources typical in rotating machines were considered, and up to three simultaneous sources could be identified. The functionality of identifying samples with no valid PDs was also incorporated using a new technique. The data set was composed of phase-resolved partial discharge (PRPD) patterns obtained from on-line measurements of hydro-generators. From an input PRPD, noise and interference were removed with an improved version of an image-based denoising algorithm previously proposed by the authors. Then, a novel image-based algorithm that separates partially superposed PD clouds was proposed, by decomposing the input pattern into two sub-PRPDs containing discharges of different natures. From the sub-PRPDs, one extracts features quantifying the PD distribution over amplitudes and the contour of PD clouds. Those features are fed as inputs to several artificial neural networks (ANNs), each of which solves a part of the classification problem and acts as a block of a larger system. Once trained, ANNs work collaboratively to identify an unknown sample. Good results were obtained, with overall accuracies ranging from 88% to 94.8% for all the considered PD sources.

With the recent advancements in power electronics for wind turbines (WTs) and increasing penetration of wind energy, wind power plants (WPP) have become necessary contributors of reactive power support for the bulk power system. Balancing reactive power support with individual WT operating requirements in a cost-effective manner is a challenge for WPP designers. In this paper, we present a methodology to optimize the WPP reactive power capability as seen from the point of common coupling (PCC), accounting for steady-state operating capabilities of the WPP equipment. Thus, the proposed methodology determines the configuration of the tap-changing transformers within the WPP that maximizes the amount of reactive power the WPP can either consume or inject to the network, considering uncertain levels of wind power generation and voltage magnitudes at the PCC. The optimized reactive power capability (ORPC) problem is initially formulated as a mixed-integer nonlinear programming (MINLP) model. Then, a set of efficient linearization techniques are used to obtain a mixed-integer linear programming (MILP) model that can be solved via off-the-shelf mathematical programming solvers. Results demonstrate that the proposed MILP model is a scalable, flexible and accurate method to maximize the reactive power capability of WPP.