...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Energy Resources Technology >Trio-V Wind Analyzer: A Generic Integral System for Wind Farm Suitability Design and Power Prediction Using Big Data Analytics
【24h】

Trio-V Wind Analyzer: A Generic Integral System for Wind Farm Suitability Design and Power Prediction Using Big Data Analytics

机译：Trio-V风分析仪：使用大数据分析进行风电场适应性设计和功率预测的通用集成系统

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

A fast-growing worldwide interest is directed toward green energies. Due to the huge costs of wind farms establishment, the location for wind farms should be carefully determined to achieve the optimum return of investment. Consequently, researches have been conducted to investigate land suitability prior to wind plants development. The generated data from the sensors detecting a potential land can be very huge, fast in generation, heterogeneous, and incomplete, which become seriously difficult to process using traditional approaches. In this paper, we propose Trio-V Wind Analyzer (WA) that handles data volume, variety, and veracity to identify the most suitable location for wind energy development in any study area using a modified version of multicriteria evaluation (MCE). It utilizes principal component analysis (PCA) and our proposed Double-Reduction Optimum Apriori (DROA) to analyze most of the environmental, physical, and economical criteria. In addition, Trio-V WA recommends the suitable turbines and proposes the adequate turbines' layout distribution, predicting the expected power generated based on the recommended turbine's specifications using a regression technique. Thus, Trio-V WA provides an integral system of land evaluation for potential investment in wind farms. Experiments indicate 80% and 95% average accuracy for land suitability degree and power prediction, respectively, with efficient performance.
机译：全球范围内快速增长的关注点是绿色能源。由于风电场建设的巨大成本，应谨慎确定风电场的位置，以实现最佳的投资回报。因此，已经进行了研究以调查风力发电厂开发之前的土地适宜性。由传感器检测到的潜在土地所生成的数据可能非常庞大，生成速度快，异构且不完整，使用传统方法很难处理。在本文中，我们提出了Trio-V风分析仪（WA），该方法可以处理数据量，变化和准确性，以使用修改后的多准则评估（MCE）版本在任何研究区域中确定最适合风能开发的位置。它利用主成分分析（PCA）和我们提出的“双折减最优先验（DROA）”来分析大多数环境，物理和经济标准。此外，Trio-V WA推荐了合适的涡轮机并提出了适当的涡轮机布局分布，并使用回归技术根据推荐的涡轮机规格预测了预期的发电量。因此，Trio-V WA为潜在的风电场投资提供了一个完整的土地评估系统。实验表明，土地适宜度和功率预测的平均准确度分别为80％和95％，并且具有高效的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号