Deriving AC OPF Solutions via Proximal Policy Optimization for Secure and Economic Grid Operation
Systems and Control
2020-04-09 v2 Systems and Control
Abstract
Optimal power flow (OPF) is a very fundamental but vital optimization problem in the power system, which aims at solving a specific objective function (ex.: generator costs) while maintaining the system in the stable and safe operations. In this paper, we adopted the start-of-the-art artificial intelligence (AI) techniques to train an agent aiming at solving the AC OPF problem, where the nonlinear power balance equations are considered. The modified IEEE-14 bus system were utilized to validate the proposed approach. The testing results showed a great potential of adopting AI techniques in the power system operations.
Keywords
Cite
@article{arxiv.2003.12584,
title = {Deriving AC OPF Solutions via Proximal Policy Optimization for Secure and Economic Grid Operation},
author = {Yuhao Zhou and Bei Zhang and Chunlei Xu and Tu Lan and Ruisheng Diao and Di Shi and Zhiwei Wang and Wei-Jen Lee},
journal= {arXiv preprint arXiv:2003.12584},
year = {2020}
}