通过近似策略优化获得AC OPF解决方案，以实现安全和经济的电网运行
Deriving AC OPF Solutions via Proximal Policy Optimization for Secure and Economic Grid Operation
摘要：
最优潮流（OPF）是电力系统中一个非常基本但又至关重要的优化问题，其目的是求解一个特定的目标函数（例如：发电机成本），同时保持系统稳定安全运行。在本文中，我们采用了最先进的人工智能（AI）技术训练一个代理，旨在解决交流最优潮流问题，其中考虑了非线性功率平衡方程。利用改进的IEEE-14节点系统验证了该方法的有效性。试验结果表明，人工智能技术在电力系统运行中具有很大的应用潜力。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
