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The Application of TAPM for Site Specific Wind Energy Forecasting

机译：TAPM在特定地点风能预测中的应用

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The energy industry uses weather forecasts for determining future electricity demand variations due to the impact of weather, e.g., temperature and precipitation. However, as a greater component of electricity generation comes from intermittent renewable sources such as wind and solar, weather forecasting techniques need to now also focus on predicting renewable energy supply, which means adapting our prediction models to these site specific resources. This work assesses the performance of The Air Pollution Model (TAPM), and demonstrates that significant improvements can be made to only wind speed forecasts from a mesoscale Numerical Weather Prediction (NWP) model. For this study, a wind farm site situated in North-west Tasmania, Australia was investigated. I present an analysis of the accuracy of hourly NWP and bias corrected wind speed forecasts over 12 months spanning 2005. This extensive time frame allows an in-depth analysis of various wind speed regimes of importance for wind-farm operation, as well as extreme weather risk scenarios. A further correction is made to the basic bias correction to improve the forecast accuracy further, that makes use of real-time wind-turbine data and a smoothing function to correct for timing-related issues. With full correction applied, a reduction in the error in the magnitude of the wind speed by as much as 50% for “hour ahead” forecasts specific to the wind-farm site has been obtained.
机译：能源行业使用天气预报来确定由于天气（例如温度和降水）的影响而导致的未来电力需求变化。但是，由于发电的更大一部分来自间歇性可再生能源，例如风能和太阳能，因此天气预报技术现在还需要集中于预测可再生能源的供应，这意味着将我们的预测模型适应这些特定地点的资源。这项工作评估了空气污染模型（TAPM）的性能，并表明可以仅对中尺度数值天气预报（NWP）模型中的风速预报进行重大改进。在这项研究中，对位于澳大利亚塔斯马尼亚州西北部的风电场进行了调查。我对2005年的12个月内每小时NWP的准确性和偏差校正后的风速预测进行了分析。这一广泛的时间范围可以深入分析对风电场运营以及极端天气至关重要的各种风速状况风险情景。对基本偏差校正进行了进一步校正，以进一步提高预测准确性，该校正利用实时风力涡轮机数据和平滑功能来校正与时间相关的问题。进行全面校正后，针对风电场站点的“提前一小时”预报已将风速大小的误差降低了50％。

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