Fernando M. Camilo , Paulo J. Santos , Armando J. Pires
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引用次数: 0
摘要
风能在全球向可再生能源的转变中发挥着关键作用,需要准确的预测模型来与电网整合和有效的能源分配。这项研究验证了三个广泛使用的来源——欧洲中期天气预报中心(ERA5)、现代研究和应用回顾性分析、MERRA-2 (NASA)和风地图集——的风速预报的准确性,并对比了2022年和2023年葡萄牙Viana do Castelo附近的WindFloat大西洋海上风电场的实际发电数据。结果表明,NASA的预测是最精确的,2022年的年相对误差为5%,2023年的年相对误差为1.6%,优于其他模型。这一分析强调了经过验证的预测模型对通过多年数据进行精确的本地校准来加强可再生能源管理的重要性。研究结果还强调了建立稳定的短期负荷预测模型以实现可靠的每日能源生产的必要性。总体而言,本研究表明,将全球风数据集与局部验证相结合可以提高海上风的预测精度。在这种背景下,NASA的数据集在海上可再生能源系统的操作和规划中成为最可靠的数据集。
A comparative analysis of real and theoretical data in offshore wind energy generation
Wind energy plays a key role in the global shift towards renewable energy, requiring accurate prediction models for integration with power grids and effective energy distribution. This study validates the accuracy of wind speed forecasts from three widely used sources – European Centre for Medium-Range Weather Forecasts (ERA5), Modern-Era Retrospective Analysis for Research and Applications, MERRA-2 (NASA), and the Wind Atlas – against actual power generation data from the WindFloat Atlantic offshore wind farm near Viana do Castelo, Portugal, over the years 2022 and 2023. The results show that NASA’s forecasts were the most precise, with annual relative errors of 5 % for 2022 and 1.6% for 2023, outperforming the other models. This analysis underscores the importance of validated forecasting models to enhance renewable energy management through multi-year data for precise local calibration. The findings also emphasize the necessity of consistent short-term load forecasting models for reliable daily energy production. Overall, this research demonstrates that combining global wind datasets with local validation improves offshore wind prediction accuracy. In this context, NASA’s dataset emerges as the most reliable for operational and planning purposes in offshore renewable energy systems.