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首页> 外文期刊>Sustainable Energy Technologies and Assessments >Comparison of six different methods of Weibull distribution for wind power assessment: A case study for a site in the Northern region of Pakistan
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Comparison of six different methods of Weibull distribution for wind power assessment: A case study for a site in the Northern region of Pakistan

机译:威布尔分布的六种不同风能评估方法的比较:以巴基斯坦北部地区为例

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摘要

Pakistan is one of those countries that heavily dependent on hydrocarbon fuel for energy production which results in severe climate change. Although renewable energy resources, like wind, are available in abundance, they are not completely utilized due to which energy crises of the country increases day by day. This study comprehensively elaborates the potential of wind power of a site located in the Northern part of Pakistan. The potential of wind power for the site was accessed and analyzed by using two years (2016-18) wind data at four heights (80, 60, 40 and 20m from sea level). Six numerical methods are used for the estimation of Weibull parameters (shape 'k' and scale 'c'). Using these parameters, Weibull mean velocity, power density, and energy density are computed at all mast heights for each year. The seasonal wind characteristics parameters and power density are also calculated. Among these methods, the modified maximum likelihood method (MMLM) is found to be the most effective method to represent the wind data, while the graphical method (GM) showed the weakest fit. Root mean square error (RMSE), determination of coefficient (R-2), and mean bias error (MBE) are computed to validate the computed results. Wind power potential assessment of the calculated data shows that the proposed location is appropriate for small scale wind energy generation.
机译:巴基斯坦是那些严重依赖碳氢化合物燃料生产能源的国家之一,导致严重的气候变化。尽管像风这样的可再生能源资源非常丰富,但由于该国的能源危机日益增加,它们并未得到充分利用。这项研究全面阐述了位于巴基斯坦北部的风电场的潜力。通过使用两年(2016-18)四个高度(海平面80、60、40和20m)的风力数据来访问和分析该站点的风力潜力。六种数值方法用于估计威布尔参数(形状“ k”和比例尺“ c”)。使用这些参数,可以计算每年所有桅杆高度的威布尔平均速度,功率密度和能量密度。还计算了季节性风特征参数和功率密度。在这些方法中,改进的最大似然法(MMLM)被认为是表示风数据的最有效方法,而图形方法(GM)则显示了最弱的拟合度。计算均方根误差(RMSE),确定系数(R-2)和平均偏差误差(MBE)以验证计算结果。对计算数据的风电潜力评估表明,建议的位置适合小规模风能发电。

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