实时数据获取方法用于使用物联网支持的风力模拟器评估DFIG风能发电系统的性能
R Sitharthan1, M Rajesh2, R Senthil Kumar3
1Centre for Smart Grid Technologies, Vellore Institute of Technology, Chennai, Tamil Nadu, India. sitharthan.r@vit.ac.in.
Scientific reports
|November 18, 2025
概括
本研究介绍了一种基于物联网的系统,用于实时分析风能. 它可以预测风能发电系统的性能评估,提高电网可靠性.
科学领域:
- 电气工程 电气工程
- 可再生能源系统可再生能源系统
- 物联网 (IoT) 的物联网 (IoT) 的物联网.
背景情况:
- 增加风能集成需要先进的系统可靠性和性能评估方法.
- 目前的方法可能缺乏风能发电系统的实时数据处理和预测能力.
- 通过各种可再生能源确保电网的效率和稳定性是一个关键的挑战.
研究的目的:
- 为风力发电系统 (WPGS) 提供基于物联网的实时数据收集和分析方法.
- 开发一个智能,支持物联网的风力模拟器,用于在各种条件下评估风力轮机的性能.
- 利用基于云的分析来进行预测分析和WPGS的性能评估.
主要方法:
- 使用了一台支持物联网的风力模拟器,配有1千瓦的双源感应发电机 (DFIG) 和无刷直流 (BLDC) 电机.
- 在VEE Pro平台上开发了一个风力轮机模型,集成IoT-NodeRed,云API和FPGA控制器.
- 在全球天气数据和模拟器控制之间实现了实时同步,延迟时间为180ms.
主要成果:
- 实验结果表明,在理论和模拟器功率输出之间,模型准确度为87% (平均绝对百分比误差).
- 该系统实现了95%的健康指数可靠性.
- 记录了0.999的近单位电网功率系数.
结论:
- 拟议的基于物联网的系统为实时风能分析提供了具有成本效益,可扩展性和适应性的解决方案.
- 这种方法提高了在动态条件下的风力发电系统性能评估.
- 这些发现支持正在进行的可再生能源电网集成的研究和开发.
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