865 resultados para Short-term energy
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Wind speed forecasting has been becoming an important field of research to support the electricity industry mainly due to the increasing use of distributed energy sources, largely based on renewable sources. This type of electricity generation is highly dependent on the weather conditions variability, particularly the variability of the wind speed. Therefore, accurate wind power forecasting models are required to the operation and planning of wind plants and power systems. A Support Vector Machines (SVM) model for short-term wind speed is proposed and its performance is evaluated and compared with several artificial neural network (ANN) based approaches. A case study based on a real database regarding 3 years for predicting wind speed at 5 minutes intervals is presented.
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Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year
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The hypothesis that dairy cows partially suckling their calves would ovulate following removal of calves when restored to positive energy balance by a short-term increase in supplementation was investigated in 65 crossbred cows. Five treatments (T1, T2, T3, T4, and T5) that differed in the amount of total concentrate fed from calving to week 24 were involved. Calves were allowed to suck residual milk to 12 weeks of age. Energy balance was estimated by measuring intake, milk yield and organic matter digestibility. The occurrence of ovulation was determined by the analysis of milk progesterone (P4) concentration. Four groups that were receiving additional supplementation were restored to positive energy balance, while the control group (T I) remained in negative energy balance. The percentage of cows ovulating was 36%, 58%, 92%, 90% and 60% for T1, T2, T3, T4 and T5, respectively (P = 0.026). Comparison of the timing of ovulation for combined results from T1+T2 and T3+T4+T5 estimated mean time to fail to ovulate as 110 +/- 9.0 and 87 +/- 7.6 days, respectively (p = 0.023). The percentage of the cows showing oestrus was 9%, 8%, 33%, 40% and 40% for T1, T2, T3, T4 and T5, respectively (P = 0.197). Short-term increases in supplementation are unlikely to be an attractive means of reducing calving intervals.
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Abstract We present a refined parametric model for forecasting electricity demand which performed particularly well in the recent Global Energy Forecasting Competition (GEFCom 2012). We begin by motivating and presenting a simple parametric model, treating the electricity demand as a function of the temperature and day of the data. We then set out a series of refinements of the model, explaining the rationale for each, and using the competition scores to demonstrate that each successive refinement step increases the accuracy of the model’s predictions. These refinements include combining models from multiple weather stations, removing outliers from the historical data, and special treatments of public holidays.
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In the last years, phototherapy has becoming a promising tool to improve skeletal muscle recovery after exercise, however, it was not compared with other modalities commonly used with this aim. In the present study we compared the short-term effects of cold water immersion therapy (CWIT) and light emitting diode therapy (LEDT) with placebo LEDT on biochemical markers related to skeletal muscle recovery after high-intensity exercise. A randomized double-blind placebo-controlled crossover trial was performed with six male young futsal athletes. They were treated with CWIT (5A degrees C of temperature [SD +/- 1A degrees]), active LEDT (69 LEDs with wavelengths 660/850 nm, 10/30 mW of output power, 30 s of irradiation time per point, and 41.7 J of total energy irradiated per point, total of ten points irradiated) or an identical placebo LEDT 5 min after each of three Wingate cycle tests. Pre-exercise, post-exercise, and post-treatment measurements were taken of blood lactate levels, creatine kinase (CK) activity, and C-reactive protein (CRP) levels. There were no significant differences in the work performed during the three Wingate tests (p > 0.05). All biochemical parameters increased from baseline values (p < 0.05) after the three exercise tests, but only active LEDT decreased blood lactate levels (p = 0.0065) and CK activity (p = 0.0044) significantly after treatment. There were no significant differences in CRP values after treatments. We concluded that treating the leg muscles with LEDT 5 min after the Wingate cycle test seemed to inhibit the expected post-exercise increase in blood lactate levels and CK activity. This suggests that LEDT has better potential than 5 min of CWIT for improving short-term post-exercise recovery.
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In this paper, short term hydroelectric scheduling is formulated as a network flow optimization model and solved by interior point methods. The primal-dual and predictor-corrector versions of such interior point methods are developed and the resulting matrix structure is explored. This structure leads to very fast iterations since it avoids computation and factorization of impedance matrices. For each time interval, the linear algebra reduces to the solution of two linear systems, either to the number of buses or to the number of independent loops. Either matrix is invariant and can be factored off-line. As a consequence of such matrix manipulations, a linear system which changes at each iteration has to be solved, although its size is reduced to the number of generating units and is not a function of time intervals. These methods were applied to IEEE and Brazilian power systems, and numerical results were obtained using a MATLAB implementation. Both interior point methods proved to be robust and achieved fast convergence for all instances tested. (C) 2004 Elsevier Ltd. All rights reserved.
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In this paper a method for solving the Short Term Transmission Network Expansion Planning (STTNEP) problem is presented. The STTNEP is a very complex mixed integer nonlinear programming problem that presents a combinatorial explosion in the search space. In this work we present a constructive heuristic algorithm to find a solution of the STTNEP of excellent quality. In each step of the algorithm a sensitivity index is used to add a circuit (transmission line or transformer) to the system. This sensitivity index is obtained solving the STTNEP problem considering as a continuous variable the number of circuits to be added (relaxed problem). The relaxed problem is a large and complex nonlinear programming and was solved through an interior points method that uses a combination of the multiple predictor corrector and multiple centrality corrections methods, both belonging to the family of higher order interior points method (HOIPM). Tests were carried out using a modified Carver system and the results presented show the good performance of both the constructive heuristic algorithm to solve the STTNEP problem and the HOIPM used in each step.
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In this paper, a method for solving the short term transmission network expansion planning problem is presented. This is a very complex mixed integer nonlinear programming problem that presents a combinatorial explosion in the search space. In order to And a solution of excellent quality for this problem, a constructive heuristic algorithm is presented in this paper. In each step of the algorithm, a sensitivity index is used to add a circuit (transmission line or transformer) or a capacitor bank (fixed or variable) to the system. This sensitivity index is obtained solving the problem considering the numbers of circuits and capacitors banks to be added (relaxed problem), as continuous variables. The relaxed problem is a large and complex nonlinear programming and was solved through a higher order interior point method. The paper shows results of several tests that were performed using three well-known electric energy systems in order to show the possibility and the advantages of using the AC model. ©2007 IEEE.
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In this paper, the short term transmission network expansion planning (STTNEP) is solved through a specialized genetic algorithm (SGA). A complete AC model of the transmission network is used, which permits the formulation of an integrated power system transmission network expansion planning problem (real and reactive power planning). The characteristics of the proposed SGA to solve the STTNEP problem are detailed and an interior point method is employed to solve nonlinear programming problems during the solution steps of the SGA. Results of tests carried out with two electrical energy systems show the capabilities of the SGA and also the viability of using the AC model to solve the STTNEP problem. © 2009 IEEE.
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Fossil fuels such as diesel are being gradually replaced by biodiesel, a renewable energy source, cheaper and less polluting. However, little is known about the toxic effects of this new energy source on aquatic organisms. Thus, we evaluated biochemical biomarkers related to oxidative stress in Nile tilapia (Oreochromis niloticus) after two and seven exposure days to diesel and pure biodiesel (B100) and blends B5 and B20 at concentrations of 0.01 and 0.1mLL -1. The hepatic ethoxyresorufin-O-deethylase activity was highly induced in all groups, except for those animals exposed to B100. There was an increase in lipid peroxidation in liver and gills in the group exposed to the higher concentration of B5. All treatments caused a significant increase in the levels of 1-hydroxypyrene excreted in the bile after 2 and 7d, except for those fish exposed to B100. The hepatic glutathione-S-transferase increased after 7d in animals exposed to the higher concentration of diesel and in the gill of fish exposed to the higher concentration of pure diesel and B5, but decreased for the two tested concentrations of B100. Superoxide dismutase, catalase and glutathione peroxidase also presented significant changes according to the treatments for all groups, including B100. Biodiesel B20 in the conditions tested had fewer adverse effects than diesel and B5 for the Nile tilapia, and can be suggested as a less harmful fuel in substitution to diesel. However, even B100 could activate biochemical responses in fish, at the experimental conditions tested, indicating that this fuel can also represent a risk to the aquatic biota. © 2011 Elsevier Ltd.
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The high active and reactive power level demanded by the distribution systems, the growth of consuming centers, and the long lines of the distribution systems result in voltage variations in the busses compromising the quality of energy supplied. To ensure the energy quality supplied in the distribution system short-term planning, some devices and actions are used to implement an effective control of voltage, reactive power, and power factor of the network. Among these devices and actions are the voltage regulators (VRs) and capacitor banks (CBs), as well as exchanging the conductors sizes of distribution lines. This paper presents a methodology based on the Non-Dominated Sorting Genetic Algorithm (NSGA-II) for optimized allocation of VRs, CBs, and exchange of conductors in radial distribution systems. The Multiobjective Genetic Algorithm (MGA) is aided by an inference process developed using fuzzy logic, which applies specialized knowledge to achieve the reduction of the search space for the allocation of CBs and VRs.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Consumption of simple carbohydrates has markedly increased over the past decades, and may be involved in the increased prevalence in metabolic diseases. Whether an increased intake of fructose is specifically related to a dysregulation of glucose and lipid metabolism remains controversial. We therefore compared the effects of hypercaloric diets enriched with fructose (HFrD) or glucose (HGlcD) in healthy men. Eleven subjects were studied in a randomised order after 7 d of the following diets: (1) weight maintenance, control diet; (2) HFrD (3.5 g fructose/kg fat-free mass (ffm) per d, +35 % energy intake); (3) HGlcD (3.5 g glucose/kg ffm per d, +35 % energy intake). Fasting hepatic glucose output (HGO) was measured with 6,6-2H2-glucose. Intrahepatocellular lipids (IHCL) and intramyocellular lipids (IMCL) were measured by 1H magnetic resonance spectroscopy. Both fructose and glucose increased fasting VLDL-TAG (HFrD: +59 %, P < 0.05; HGlcD: +31 %, P = 0.11) and IHCL (HFrD: +52 %, P < 0.05; HGlcD: +58 %, P = 0.06). HGO increased after both diets (HFrD: +5 %, P < 0.05; HGlcD: +5 %, P = 0.05). No change was observed in fasting glycaemia, insulin and alanine aminotransferase concentrations. IMCL increased significantly only after the HGlcD (HFrD: +24 %, NS; HGlcD: +59 %, P < 0.05). IHCL and VLDL-TAG were not different between hypercaloric HFrD and HGlcD, but were increased compared to values observed with a weight maintenance diet. However, glucose led to a higher increase in IMCL than fructose.
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BACKGROUND Epidemiologic and experimental data have suggested that chlorogenic acid, which is a polyphenol contained in green coffee beans, prevents diet-induced hepatic steatosis and insulin resistance. OBJECTIVE We assessed whether the consumption of chlorogenic acid-rich coffee attenuates the effects of short-term fructose overfeeding, dietary conditions known to increase intrahepatocellular lipids (IHCLs), and blood triglyceride concentrations and to decrease hepatic insulin sensitivity in healthy humans. DESIGN Effects of 3 different coffees were assessed in 10 healthy volunteers in a randomized, controlled, crossover trial. IHCLs, hepatic glucose production (HGP) (by 6,6-d2 glucose dilution), and fasting lipid oxidation were measured after 14 d of consumption of caffeinated coffee high in chlorogenic acid (C-HCA), decaffeinated coffee high in chlorogenic acid, or decaffeinated coffee with regular amounts of chlorogenic acid (D-RCA); during the last 6 d of the study, the weight-maintenance diet of subjects was supplemented with 4 g fructose · kg(-1) · d(-1) (total energy intake ± SD: 143 ± 1% of weight-maintenance requirements). All participants were also studied without coffee supplementation, either with 4 g fructose · kg(-1) · d(-1) (high fructose only) or without high fructose (control). RESULTS Compared with the control diet, the high-fructose diet significantly increased IHCLs by 102 ± 36% and HGP by 16 ± 3% and decreased fasting lipid oxidation by 100 ± 29% (all P < 0.05). All 3 coffees significantly decreased HGP. Fasting lipid oxidation increased with C-HCA and D-RCA (P < 0.05). None of the 3 coffees significantly altered IHCLs. CONCLUSIONS Coffee consumption attenuates hepatic insulin resistance but not the increase of IHCLs induced by fructose overfeeding. This effect does not appear to be mediated by differences in the caffeine or chlorogenic acid content. This trial was registered at clinicaltrials.gov as NCT00827450.
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Warming of the world's oceans is predicted to have many negative effects on organisms as they have optimal thermal windows. In coastal waters, however, both temperatures and pCO2 (pH) exhibit diel variations, and biological performances are likely to be modulated by physical and chemical environmental changes. To understand how coastal zooplankton respond to the combined impacts of heat shock and increased pCO2, the benthic copepod Tigriopus japonicus were treated at temperatures of 24, 28, 32 and 36 °C to simulate natural coastal temperatures experienced in warming events, when acclimated in the short term to either ambient (LC, 390 µatm) or future CO2 (HC, 1000 µatm). HC and heat shock did not induce any mortality of T. japonicus, though respiration increased up to 32 °C before being depressed at 36 °C. Feeding rate peaked at 28 °C but did not differ between CO2 treatments. Expression of heat shock proteins (hsps mRNA) was positively related to temperature, with no significant differences between the CO2 concentrations. Nauplii production was not affected across all treatments. Our results demonstrate that T. japonicus responds more sensitively to heat shocks rather than to seawater acidification; however, ocean acidification may synergistically act with ocean warming to mediate the energy allocation of copepods.