926 resultados para wind power forecast error


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The aims of this study were to 1) determine the relationship between performance on the court-based TIVRE-Basket® test and peak aerobic power determined from a criterion lab-based incremental treadmill test and 2) to examine the test-retest reliability of the TIVRE-Basket® test in elite male basketball players. To address aim 1, 36 elite male basketball players (age 25.2 + 4.7 years, weight 94.1 + 11.4 kg, height 195.83 + 9.6 cm) completed a graded treadmill exercise test and the TIVRE-Basket® within 72 hours. Mean distance recorded during the TIVRE-Basket® test was 4001.8 + 176.4m, and mean VO2 peak was 54.7 + 2.8 ml.kg.min-1, and the correlation between the two parameters was r=0.824 (P= <0.001). Linear regression analysis identified TIVRE-Basket® distance (m) as the only unique predictor of VO2 peak in a single variable plus constant model: VO2 peak = 2.595 + ((0.13* TIVRE-Basket® distance (m)). Performance on the TIVRE-Basket® test accounted for 67.8% of the variance in VO2 peak (t=8.466, P=<.001, 95% CI 0.01 - 0.016, SEE 1.61). To address aim 2, 20 male basketball players (age 26.7±4.2; height 1.94±0.92; weight 94.0±9.1) performed the TIVRE-Basket® test on two occasions. There was no significant difference in total distance covered between Trial 1 (4138.8 + 677.3m) and Trial 2 (4188.0 + 648.8m; t = 0.5798, P = 0.5688). Mean difference between trials was 49.2 + 399.5m, with an ICC of 0.85 suggesting a moderate level of reliability. Standardised TEM was 0.88%, representing a moderate degree of trial to trial error, and the CV was 6.3%. The TIVRE-Basket® test therefore represents a valid and moderately reliable court-based sport-specific test of aerobic power for use with individuals and teams of elite level male basketball players. Future research is required to ascertain its validity and reliability in other basketball populations e.g. across age groups, at different levels of competition, in females and in different forms of the game e.g. wheelchair basketball.

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Tese de doutoramento, Sistemas Sustentáveis de Energia, Universidade de Lisboa, Faculdade de Ciências, 2016

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Energy saving, reduction of greenhouse gasses and increased use of renewables are key policies to achieve the European 2020 targets. In particular, distributed renewable energy sources, integrated with spatial planning, require novel methods to optimise supply and demand. In contrast with large scale wind turbines, small and medium wind turbines (SMWTs) have a less extensive impact on the use of space and the power system, nevertheless, a significant spatial footprint is still present and the need for good spatial planning is a necessity. To optimise the location of SMWTs, detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in this article, wind measurements and roughness maps were used to create a reliable annual mean wind speed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surface wind speed measurements were converted into meso- and macroscale wind data. The data were further processed by using seven different spatial interpolation methods in order to develop regional wind resource maps. Based on statistical analysis, it was found that the transformation into mesoscale wind, in combination with Simple Kriging, was the most adequate method to create reliable maps for decision-making on optimal production sites for SMWTs in Flanders.

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In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. (C) 2011 Elsevier Ltd. All rights reserved.

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In many countries the use of renewable energy is increasing due to the introduction of new energy and environmental policies. Thus, the focus on the efficient integration of renewable energy into electric power systems is becoming extremely important. Several European countries have already achieved high penetration of wind based electricity generation and are gradually evolving towards intensive use of this generation technology. The introduction of wind based generation in power systems poses new challenges for the power system operators. This is mainly due to the variability and uncertainty in weather conditions and, consequently, in the wind based generation. In order to deal with this uncertainty and to improve the power system efficiency, adequate wind forecasting tools must be used. This paper proposes a data-mining-based methodology for very short-term wind forecasting, which is suitable to deal with large real databases. The paper includes a case study based on a real database regarding the last three years of wind speed, and results for wind speed forecasting at 5 minutes intervals.

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Electricity market players operating in a liberalized environment require adequate decision support tools, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. This paper deals with short-term predication of day-ahead spinning reserve (SR) requirement that helps the ISO to make effective and timely decisions. Based on these forecasted information, market participants can use strategic bidding for day-ahead SR market. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

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Electric vehicles (EV) offer a great potential to address the integration of renewable energy sources (RES) in the power grid, and thus reduce the dependence on oil as well as the greenhouse gases (GHG) emissions. The high share of wind energy in the Portuguese energy mix expected for 2020 can led to eventual curtailment, especially during the winter when high levels of hydro generation occur. In this paper a methodology based on a unit commitment and economic dispatch is implemented, and a hydro-thermal dispatch is performed in order to evaluate the impact of the EVs integration into the grid. Results show that the considered 10 % penetration of EVs in the Portuguese fleet would increase load in 3 % and would not integrate a significant amount of wind energy because curtailment is already reduced in the absence of EVs. According to the results, the EV is charged mostly with thermal generation and the associated emissions are much higher than if they were calculated based on the generation mix.

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This paper is about a hierarchical structure with an event-based supervisor in a higher level and a fractional-order proportional integral (FOPI) in a lower level applied to a wind turbine. The event-based supervisor analyzes the operation conditions to determine the state of the wind turbine. This controller operate in the full load region and the main objective is to capture maximum power generation while ensuring the performance and reliability required for a wind turbine to be integrated into an electric grid. The main contribution focus on the use of fractional-order proportional integral controller which benefits from the introduction of one more tuning parameter, the integral fractional-order, taking advantage over integer order proportional integral (PI) controller. Comparisons between fractional-order pitch control and a default proportional integral pitch controller applied to a wind turbine benchmark are given and simulation results by Matlab/Simulink are shown in order to prove the effectiveness of the proposed approach.

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This paper presents a comparison between proportional integral control approaches for variable speed wind turbines. Integer and fractional-order controllers are designed using linearized wind turbine model whilst fuzzy controller also takes into account system nonlinearities. These controllers operate in the full load region and the main objective is to extract maximum power from the wind turbine while ensuring the performance and reliability required to be integrated into an electric grid. The main contribution focuses on the use of fractional-order proportional integral (FOPI) controller which benefits from the introduction of one more tuning parameter, the integral fractional-order, taking advantage over integer order proportional integral (PI) controller. A comparison between proposed control approaches for the variable speed wind turbines is presented using a wind turbine benchmark model in the Matlab/Simulink environment. Results show that FOPI has improved system performance when compared with classical PI and fuzzy PI controller outperforms the integer and fractional-order control due to its capability to deal with system nonlinearities and uncertainties. © 2014 IEEE.

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This paper is on offshore wind energy conversion systems installed on the deep water and equipped with back-to-back neutral point clamped full-power converter, permanent magnet synchronous generator with an AC link. The model for the drive train is a five-mass model which incorporates the dynamic of the structure and the tower in order to emulate the effect of the moving surface. A three-level converter and a four-level converter are the two options with a fractional-order control strategy considered to equip the conversion system. Simulation studies are carried out to assess the quality of the energy injected into the electric grid. Finally, conclusions are presented. (C) 2014 Elsevier Ltd. All rights reserved.

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Coal contains trace quantities of natural radionuclides such as Th-232, U-235, U-238, as well as their radioactive decay products and 40K. These radionuclides can be released as fly ash in atmospheric emissions from coal-fired power plants, dispersed into the environment and deposited on the surrounding top soils. Therefore, the natural radiation background level is enhanced and consequently increase the total dose for the nearby population. A radiation monitoring programme was used to assess the external dose contribution to the natural radiation background, potentially resulting from the dispersion of coal ash in past atmospheric emissions. Radiation measurements were carried out by gamma spectrometry in the vicinity of a Portuguese coal-fired power plant. The radiation monitoring was achieved both on and off site, being the boundary delimited by a 20 km circle centered in the stacks of the coal plant. The measured radionuclides concentrations for the uranium and thorium series ranged from 7.7 to 41.3 Bq/kg for Ra-226 and from 4.7 to 71.6 Bq/kg for Th-232, while K-40 concentrations ranged from 62.3 to 795.1 Bq/kg. The highest values were registered near the power plant and at distances between 6 and 20 km from the stacks, mainly in the prevailing wind direction. The absorbed dose rates were calculated for each sampling location: 13.97-84.00 ηGy/h, while measurements from previous studies carried out in 1993 registered values in the range of 16.6-77.6 ηGy/h. The highest values were registered at locations in the prevailing wind direction (NW-SE). This study has been primarily done to assess the radiation dose rates and exposure to the nearby population in the surroundings of a coal-fired power plant. The results suggest an enhancement or at least an influence in the background radiation due to the coal plant past activities.

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Coal contains trace elements and naturally occurring radionuclides such as 40K, 232Th, 238U. When coal is burned, minerals, including most of the radionuclides, do not burn and concentrate in the ash several times in comparison with their content in coal. Usually, a small fraction of the fly ash produced (2-5%) is released into the atmosphere. The activities released depend on many factors (concentration in coal, ash content and inorganic matter of the coal, combustion temperature, ratio between bottom and fly ash, filtering system). Therefore, marked differences should be expected between the by-products produced and the amount of activity discharged (per unit of energy produced) from different coal-fired power plants. In fact, the effects of these releases on the environment due to ground deposition have been received some attention but the results from these studies are not unanimous and cannot be understood as a generic conclusion for all coal-fired power plants. In this study, the dispersion modelling of natural radionuclides was carried out to assess the impact of continuous atmospheric releases from a selected coal plant. The natural radioactivity of the coal and the fly ash were measured and the dispersion was modelled by a Gaussian plume estimating the activity concentration at different heights up to a distance of 20 km in several wind directions. External and internal doses (inhalation and ingestion) and the resulting risk were calculated for the population living within 20 km from the coal plant. In average, the effective dose is lower than the ICRP’s limit and the risk is lower than the U.S. EPA’s limit. Therefore, in this situation, the considered exposure does not pose any risk. However, when considering the dispersion in the prevailing wind direction, these values are significant due to an increase of 232Th and 226Ra concentrations in 75% and 44%, respectively.

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Gamma radiations measurements were carried out in the vicinity of a coal-fired power plant located in the southwest coastline of Portugal. Two different gamma detectors were used to assess the environmental radiation within a circular area of 20 km centred in the coal plant: a scintillometer (SPP2 NF, Saphymo) and a high purity germanium detector (HPGe, Canberra). Fifty urban and suburban measurements locations were established within the defined area and two measurements campaigns were carried out. The results of the total gamma radiation ranged from 20.83 to 98.33 counts per second (c.p.s.) for both measurement campaigns and outdoor doses rates ranged from 77.65 to 366.51 Gy/h. Natural emitting nuclides from the U-238 and Th-232 decay series were identified as well as the natural emitting nuclide K-40. The radionuclide concentration from the uranium and thorium series determined by gamma spectrometry ranged from 0.93 to 73.68 Bq/kg, while for K-40 the concentration ranged from 84.14 to 904.38 Bq/kg. The obtained results were used primarily to define the variability in measured environmental radiation and to determine the coal plant’s influence in the measured radiation levels. The highest values were measured at two locations near the power plant and at locations between the distance of 6 and 20 km away from the stacks, mainly in the prevailing wind direction. The results showed an increase or at least an influence from the coal-fired plant operations, both qualitatively and quantitatively.

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Energy resource scheduling is becoming increasingly important, such as the use of more distributed generators and electric vehicles connected to the distribution network. This paper proposes a methodology to be used by Virtual Power Players (VPPs), regarding the energy resource scheduling in smart grids and considering day-ahead, hour-ahead and realtime time horizons. This method considers that energy resources are managed by a VPP which establishes contracts with their owners. The full AC power flow calculation included in the model takes into account network constraints. In this paper, distribution function errors are used to simulate variations between time horizons, and to measure the performance of the proposed methodology. A 33-bus distribution network with large number of distributed resources is used.

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Proceedings of the 13th International UFZ-Deltares Conference on Sustainable Use and Management of Soil, Sediment and Water Resources - 9–12 June 2015 • Copenhagen, Denmark