一种提升电力系统韧性的新型主动防御策略
A Novel Proactive Operation Strategy to Enhance Power System Resilience
张焕青 1刘春明 1赵宇龙 1赵家成 1付晴玉1
作者信息
- 1. 华北电力大学电气与电子工程学院,北京市 昌平区 102206
- 折叠
摘要
韧性描述了电力系统抵抗并从极端事件中快速恢复的能力,采取主动防御的调度策略可有效提高系统韧性,然而传统模型求解速度慢、无法在线应用,且调度过程中易产生不必要的切负荷,因此基于滚动优化思路提出了一种新的主动防御调度策略,在提升韧性的同时降低了求解时间并且扩大了安全裕度.首先,将极端事件下系统状态的不确定性转移建模成马尔可夫状态转移模型;其次,基于马尔可夫决策过程建立了考虑过载风险的主动防御模型,采用滚动优化的思想对其进行求解;最后,采用基于马尔可夫蒙特卡洛的韧性评估方法在IEEE24节点模型上验证了上述方法的有效性,结果表明该方法比传统模型缩短了 76％的求解时间、降低了 15.6％的失负荷.
Abstract
Resilience describes the ability to resist and quickly recover from extreme events and proactive operation can effectively improve resilience. However, traditional model is hard to solve, cannot be applied online, and have unnecessary offload, this article proposes a new proactive operation model based on rolling optimization, which improves the resilience while reducing the solution time and expanding the security margin. Firstly, the uncertainty in the transition of system state driven by extreme events is modeled as a Markov state transition model. Secondly, a proactive operation model considering overload risk is established based on Markov decision processes, and its solution is obtained using rolling optimization approach. Finally, the effectiveness is verified on the IEEE24 node model using a Markov Chain Monte-Carlo based resilience evaluation method. The results show that the model proposed in this article shortens the solution time by 76％, reduces the offload by 15.6％.
关键词
极端事件/电力系统韧性/主动防御/马尔可夫决策Key words
extreme events/power system resilience/proactive operation/Markov decision process引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
维普
万方数据