设计和实施用于使用近似动态编程和人工神经网络的微电网应用的通用转换器
K Suresh1, E Parimalasundar2, B Hemanth Kumar2
1Department of Electrical and Electronics Engineering, Christ Deemed to Be University, Bangalore, India.
Scientific reports
|September 8, 2024
概括
本研究介绍了一种用于微电网的全新通用直流-直流和直流-交流转换器,该转换器采用近似动态编程和人工神经网络 (ADP-ANN) 设计. 它有效地处理电池和交流电源,减少对多功能能源应用的组件需求.
科学领域:
- 电气工程 电气工程
- 电力电子 电力电子 电力电子
- 人工智能的人工智能
背景情况:
- 微电网需要多功能电力转换解决方案.
- 现有的转换器通常具有组件冗余性和有限的操作模式.
- 多种能源 (电池,交流) 的高效整合至关重要.
研究的目的:
- 引入一种全新的通用DC-DC和DC-AC转换器设计.
- 为了提高效率并减少微电网电力转换中的组件数量.
- 利用近似动态编程和人工神经网络 (ADP-ANN) 进行最佳控制.
主要方法:
- 一个使用相同的终端和开关用于切割机和逆变器功能的通用转换器的设计.
- 实施近似动态编程和人工神经网络 (ADP-ANN) 进行控制.
- 在五种操作模式中开发和测试3000W原型.
主要成果:
- 转换器在直流 (电池) 和交流输入方面都表现出高效的运行.
- 实现了最小的开关使用和组件冗余.
- 实验验证证了系统在各种微电网场景中的稳定性和适应性.
结论:
- 这种全新的通用转换器为微电网提供了降低复杂度和提高效率.
- 通过ADP-ANN集成,可以实现最佳的性能和适应性.
- 潜在的应用包括微电网,电动汽车和可再生能源系统.
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