基于分布式双投射层循环神经网络的多总线直流微电网的最佳控制,考虑总线电压调节
Yuanyuan Zhu1, Fan Yang1, Guoyu Lin2
1College of Mechanical & Electronic Engineering, Nanjing Forestry University, Nanjing, 210037, PR China.
ISA transactions
|June 27, 2025
概括
这项研究引入了一个新的控制方法,用于DC微电网与插电负载. 它优化成本和功率损耗,同时调节电压,确保稳定的运行.
科学领域:
- 电气工程 电气工程
- 控制系统 控制系统
- 可再生能源系统可再生能源系统
背景情况:
- 在DC微电网中,插电负载的日益集成带来了重大的控制挑战.
- 传统的控制策略与这些负载的动态性质作斗争,影响了电网的稳定性和效率.
- 保持总线电压调节对于可靠运行至关重要.
研究的目的:
- 为DC微电网开发一种新的控制策略,以适应插电负载.
- 为了共同优化发电成本和输电线输电损失.
- 确保在动态负载条件下有效调节总线电压.
主要方法:
- 引入虚拟负载节点,以促进插即用功能.
- 克朗减值的应用用于通过GD节点间接控制负载节点电压.
- 开发一个分布式的双投射层循环神经网络 (DRNN) 进行实时最佳控制.
- 利用利亚普诺夫合成来证明DRNN的收.
主要成果:
- 拟议的DRNN有效地保持合电压和电流在安全的运行范围内.
- 通过DG节点操纵证明了负载总线电压的间接控制.
- 模拟验证了拟议的控制方法的插即用能力和整体有效性.
- 对比分析证实了比传统方法的优势.
结论:
- 呈现的虚拟负载节点概念和DRNN提供了一个强大的解决方案,用于控制用Plug-and-Play负载控制直流微电网.
- 该方法成功地平衡了经济调度 (发电成本) 与运营效率 (减少功率损失) 和电压稳定性.
- 这项工作为现代动态直流微电网系统的实时最佳控制提供了重大进步.
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