Utilizing STATCON to Resolve Delayed Voltage Recovery Problem in SEC-WR

Du, Mingming; Han, Minxiao; Cao, Zongjie; Chu, F.Y.; Ei-Kady, Moe

doi:10.1109/appeec.2009.4918958

Cited by 7 publications

(1 citation statement)

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“…The control actions to mitigate the FIDVR problem can be classified as supply-side solutions and demand-side solutions. The most popular supply-side solution applied by utilities is the implementation of FACTS devices such as SVC [18] and static condenser [19] to increase reactive power support. However, these devices are very expensive and cost approximately $20-50 million per installation.…”

Section: B Literature Reviewmentioning

confidence: 99%

Physics-informed Evolutionary Strategy based Control for Mitigating Delayed Voltage Recovery

Du¹,

Huang²,

Huang³

et al. 2021

Preprint

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In this work we propose a novel data-driven, realtime power system voltage control method based on the physicsinformed guided meta evolutionary strategy (ES). The main objective is to quickly provide an adaptive control strategy to mitigate the fault-induced delayed voltage recovery (FIDVR) problem. Reinforcement learning methods have been developed for the same or similar challenging control problems, but they suffer from training inefficiency and lack of robustness for "corner or unseen" scenarios. On the other hand, extensive physical knowledge has been developed in power systems but little has been leveraged in learning-based approaches. To address these challenges, we introduce the trainable action mask technique for flexibly embedding physical knowledge into RL models to rule out unnecessary or unfavorable actions, and achieve notable improvements in sample efficiency, control performance and robustness. Furthermore, our method leverages past learning experience to derive surrogate gradient to guide and accelerate the exploration process in training. Case studies on the IEEE 300-bus system and comparisons with other state-of-the-art benchmark methods demonstrate effectiveness and advantages of our method.

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Section: B Literature Reviewmentioning

confidence: 99%