基于机器学习的控制用于高功率应用的双模块多层PWM逆变器
Ravi Teja Srungaram1, Kishore Yadlapati2
1Department of Electrical and Electronics Engineering, Jawaharlal Nehru Technological University Kakinada, Kakinada, Andhra Pradesh, India.
PloS one
|July 22, 2024
概括
本研究介绍了一种智能,机器学习控制的高功率光伏逆变器,用于高效的能源使用和最大功率提取. 新型模块化转换器设计在高功率应用中提高了可靠性和经济性能.
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
- 控制系统 控制系统
背景情况:
- 高功率光伏 (PV) 逆变器对于高效的太阳能转换至关重要.
- 现有的逆变器拓在最大限度地提取功率和在不同条件下确保可靠运行方面面临挑战.
- 需要智能控制策略来优化能源利用和电网集成.
研究的目的:
- 为高功率光伏逆变器提供一种新的拓.
- 开发和实施基于机器学习的智能控制系统,以实现最大功率提取和最佳能源利用.
- 评估拟议系统的经济性能和可靠性.
主要方法:
- 使用MATLAB/SIMULINK.设计和模拟一个模块化转换器拓.
- 开发一个集成的智能控制算法,采用机器学习.
- 对模拟结果的实验验证.
- 对运营和经济绩效与现有拓学的比较分析.
主要成果:
- 拟议的逆变器拓在模拟和实验研究中证明了可行性和有效性.
- 智能控制系统成功地实现了最大功率提取和最佳负载需求控制.
- 模块化设计通过减少组件数量和提高可靠性提供经济效益.
- 性能评估显示与现有解决方案相比,具有竞争力或优越的操作参数.
结论:
- 展示的高功率光伏逆变器拓与基于机器学习的智能控制为太阳能系统提供了可靠和经济可行的解决方案.
- 综合控制战略提高了能源利用效率和电力管理.
- 模块化设计有助于提高系统的稳定性和高功率应用的成本效益.
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