一个时间和空间集成的扩张规划方法,用于AC/DC混合分布网络
Yao Guo1, Shaorong Wang1, Dezhi Chen1
1School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Sensors (Basel, Switzerland)
|April 12, 2025
概括
本研究介绍了AC/DC混合配电网络 (AC/DC-HDNs) 的优化扩建规划方法,以管理可再生能源整合和电网可靠性. 这种新的方法利用深度强化学习来实现高效和稳定的网络规划.
科学领域:
- 电气工程 电气工程
- 电力系统工程 电力系统工程
- 计算智能是一种计算智能.
背景情况:
- 随着可再生能源和电力需求的不断增长,传统电网面临挑战.
- 交流/直流混合配电网络 (AC/DC-HDNs) 提供了提高可靠性和灵活性的解决方案.
- 由于拓,动态负载和成本,AC/DC-HDNs的扩展规划是复杂的.
研究的目的:
- 为AC/DC-HDNs提出一个时间和空间集成的扩展规划方法.
- 通过平衡经济和可靠性目标来优化规划过程.
- 为应对AC/DC-HDN扩展规划中的挑战.
主要方法:
- 基于图形理论的分布网格建模,整合空间布局.
- 对动态负载和可再生能源发电特性进行时间序列分析.
- 基于修改图表注意力网络 (MGAT) 的深度强化学习 (DRL) 进行优化.
主要成果:
- 拟议的基于MGAT的DRL算法显示了比传统方法更高的训练效率和稳定性.
- 观察到更快的趋同和累计奖励的波动减少.
- 持续较高的累积奖励表明AC/DC-HDN扩展计划的有效优化.
结论:
- 开发的方法为AC/DC-HDN的复杂扩展规划提供了有效的解决方案.
- 基于MGAT的DRL方法提高了未来电网的优化性能.
- 这项研究有助于通过增加可再生能源来实现可靠和灵活的电网扩张.
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