使用可再生资源减轻织行业的超声波:PCA-WHOGBDT技术用于提高电网稳定性和电力质量
1Research Scholar, Department of Electrical and Electronics Engineering, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu, India.
ISA transactions
|April 19, 2024
概括
本研究介绍了一种使用主要组件分析 (PCA) 和基于野马优化 (WHO) 的梯度增强决策树 (GBDT) 的混合技术,以有效减少电网中的超声波. 该方法通过减轻高频波,显著提高了电力质量和电网稳定性.
科学领域:
- 电气工程 电气工程
- 电力系统分析 分析 分析
背景情况:
- 超波是高频波,对电网 (PG) 的稳定性和性能构成重大挑战.
- 现有的超缩方法在不同的电网条件下经常面临局限性.
研究的目的:
- 提出和评估一种新的混合技术,以有效减少电网中的超声波.
- 为了提高LCCL和LCL过器在减轻高频波的性能.
主要方法:
- 这是一种混合方法,它结合了主要组件分析 (PCA) 来进行数据分析和基于野生马优化 (WHO) 的梯度增强决策树 (GBDT) 来进行超调减.
- 分析网络频率变化,直流电压变化和电压噪声.
- 在弱电网和电网上实时评估拟议的战略.
主要成果:
- 拟议的PCA-WHOGBDT战略成功地将超声波降低到弱电网中的基本声波的0.2%.
- 在弱电网和刚电网类型中证明了高频波的缓解.
- 观察到LCCL和LCL过器的性能提高.
结论:
- PCA-WHOGBDT战略为混合供电电网的超调减排提供了一个有效的解决方案.
- 拟议的方法有助于提高电力系统的质量和稳定性.
- 该技术在弱电网场景中表现出高于典型水平的性能.
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