基于深度学习算法的电力系统自动化调度方法
Power System Automatic Dispatching Method Based on Deep Learning Algorithms
王永兴1
作者信息
- 1. 中建八局(山东)设计咨询有限公司,山东潍坊 261000
- 折叠
摘要
本研究旨在探讨基于深度学习算法的电力系统自动化调度方法,具体构建了电力系统自动化调度模型,并通过Actor-Critic(AC)算法和改进的异步优势Actor-Critic(A3C)算法优化调度策略.研究通过模拟实验验证深度学习算法在电力系统调度中的有效性,实验结果表明改进A3C算法在电力供需匹配和系统稳定性方面表现最佳.
Abstract
This study aims to explore the method of power system automatic dispatching based on deep learning algorithms.Specifically,a power system automatic dispatching model is constructed,and the dispatching strategy is optimized through the Actor-Critic(AC)algorithm and the improved Asynchronous Advantage Actor-Critic(A3C)algorithm.The study verifies the effectiveness of deep learning algorithms in power system dispatching through simulation experiments.The experimental results show that the improved A3C algorithm performs best in terms of power supply and demand matching and system stability.
关键词
深度学习算法/电力系统/自动调度Key words
deep learning algorithms/power system/automatic dispatching引用本文复制引用
出版年
2024
NETL
NSTL
万方数据