电网运行学习环境（L2RPN）的设计与实现
Design and implementation of an environment for Learning to Run a Power Network (L2RPN)
摘要：
本报告总结了作为INRIA实习的一部分所做的工作，部分要求完成数学和信息学硕士学位。实习的目标是开发一个软件环境来模拟电网中的电力传输以及运营商为维护电网安全而采取的行动。我们的环境有助于通过强化学习代理自动控制电网，协助人类操作员。它可以组织基准测试，包括INRIA和RTE计划在2019年进行的机器学习挑战。我们的框架建立在开源库之上，可以在https://github.com/MarvinLer/pypownet上找到。在这份报告中，我们提出了中介结果及其在强化学习游戏中的使用。
英文摘要：
This report summarizes work performed as part of an internship at INRIA, in partial requirement for the completion of a master degree in math and informatics. The goal of the internship was to develop a software environment to simulate electricity transmission in a power grid and actions performed by operators to maintain this grid in security. Our environment lends itself to automate the control of the power grid with reinforcement learning agents, assisting human operators. It is amenable to organizing benchmarks, including a challenge in machine learning planned by INRIA and RTE for 2019. Our framework, built on top of open-source libraries, is available at https://github.com/MarvinLer/pypownet. In this report we present intermediary results and its usage in the context of a reinforcement learning game.
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。
