Current Issue : January - March Volume : 2020 Issue Number : 1 Articles : 5 Articles
Wind power has an increasing share of the Brazilian energy market and\nmay represent 11.6% of total capacity by 2024. For large hydro-thermal systems\nhaving high-storage capacity, a complementarity between hydro and\nwind production could have important effects. The current optimization\nmodels are applied to dispatch power plants to meet the market demand\nand optimize the generation dispatches considering only hydroelectric and\nthermal power plants. The remaining sources, including wind power,\nsmall-hydroelectric plants and biomass plants, are excluded from the optimization\nmodel and are included deterministically. This work introduces a general\nmethodology to represent the stochastic behavior of wind production\naimed at the planning and operation of large interconnected power systems.\nIn fact, considering the generation of the wind power source stochastically\ncould show the complementarity between the hydro and wind power production,\nreducing the energy price in the spot market with the reduction of\nthermal power dispatches. In addition to that, with a reduction in wind power\nand a simultaneous dry-season occurrence, this model, is able to show the\nneed of thermal power plants dispatches as well as the reduction of the risk of\nenergy shortages....
In this paper, a method is proposed to estimate wind turbulence parameters using\nmeasurements recorded by a conically scanning coherent Doppler lidar with two different elevation\nangles. This methodology helps determine the anisotropy of the spatial correlation of wind velocity\nturbulent fluctuations. The proposed method was tested in a field experiment with a Stream Line\nlidar (Halo Photonics, Brockamin, Worcester, United Kingdom) under stable temperature\nstratification conditions in the atmospheric boundary layer. The results show that the studied\nanisotropy coefficient in a stable boundary layer may be up to three or larger....
This paper describes the numerical study of nonstratified airflow over a real\ncomplex terrain. Attention is focused on the mechanism of a local strong\nwind induced by a topographic effect. In order to clarify the mechanism of\nthe occurrence of strong winds accompanied by the effects of terrain, the use\nof a numerical simulation is very effective, in which conditions can be set\nwithout the influence of ground roughness and temperature distribution. As a\nresult, airflow converged to a small basin of mountain terrain in the upper\nstream, and local strong wind was generated leeward along the slope of the\nmountain terrain. Furthermore, the influence of the reproduction accuracy of\ngeographical features, that is, horizontal grid resolution, was examined. Consequently,\nto reproduce the above-mentioned local strong wind, it was shown\nthat horizontal grid resolution from 50 m to about 100 m was necessary....
In order to explore the internal wind field flow characteristics of T4-72 type\ncentrifugal fan, the three-dimensional model was established based on PRO/E\nsoftware. Combined with computational fluid Dynamics Software Fluent 6.3,\nthe standard model and SIMPLEC algorithm were used to simulate the wind\nfield inside the fan. Analysis of the flow characteristics, velocity distributed\nand pressure distributed of the internal fluid model of the T4-72 centrifugal\nfan, combined with the theoretical formula to obtain the full pressure, power\nand efficiency performance parameters of the fan. The centrifugal fan performance\ncurve is drawn. While compared with the experimental data, it is\nfound that the internal flow disturbance is strong when the fan is running\nunder low load condition and high load condition, which affects the performance\nof the fan and reduces the life of the fan. The numerical simulation\nresults are consistent with the experimental results. The overall performance\nparameters of the fan are in good agreement, verifying the reliability of the\nsimulation results; when the fan works between 1 - 1.4 times the rated flow\nrate, it can obtain a more stable flow field while maintaining higher efficiency,\nwhich provides a new idea for the optimization of the subsequent fan....
This paper proposed the SVD (singular value decomposition) clustering algorithm to cluster wind turbines into some group for a\nlarge offshore wind farm, in order to reduce the high-dimensional problem in wind farm power control and numerical simulation.\nFirstly, wind farm wake relationship matrixes are established considering the wake effect in an offshore wind farm, and the SVD of\nwake relationship matrixes is used to cluster wind turbines into some groups by the fuzzy clustering algorithm. At last, the Horns\nRev offshore wind farm is analyzed to test the clustering algorithm, and the clustering result and the power simulation show the\neffectiveness and feasibility of the proposed clustering strategy....
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