Search Results for author: Desong Bian

Found 2 papers, 0 papers with code

Rethink AI-based Power Grid Control: Diving Into Algorithm Design

no code implementations23 Dec 2020 Xiren Zhou, Siqi Wang, Ruisheng Diao, Desong Bian, Jiahui Duan, Di Shi

Recently, deep reinforcement learning (DRL)-based approach has shown promisein solving complex decision and control problems in power engineering domain. In this paper, we present an in-depth analysis of DRL-based voltage control fromaspects of algorithm selection, state space representation, and reward engineering. To resolve observed issues, we propose a novel imitation learning-based approachto directly map power grid operating points to effective actions without any interimreinforcement learning process.

Imitation Learning

On Training Effective Reinforcement Learning Agents for Real-time Power Grid Operation and Control

no code implementations11 Dec 2020 Ruisheng Diao, Di Shi, Bei Zhang, Siqi Wang, Haifeng Li, Chunlei Xu, Tu Lan, Desong Bian, Jiajun Duan

Deriving fast and effectively coordinated control actions remains a grand challenge affecting the secure and economic operation of today's large-scale power grid.

Optimization and Control Systems and Control Systems and Control

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