PyProD：一个机器学习友好的配电系统保护分析平台
PyProD: A Machine Learning-Friendly Platform for Protection Analytics in Distribution Systems
摘要：
本文介绍了PyProD，一个基于Python的机器学习（ML）兼容的测试平台，用于评估配电网保护方案的有效性。该测试平台旨在弥合传统配电网分析与基于ML的决策算法的能力不断增长之间的差距，特别是在保护系统设计和配置方面。PyProD被证明是能够促进有效的设计和评估的ML为基础的决策算法的保护装置在未来的配电网，其中许多分布式能源和pro-sumers渗透系统。
英文摘要：
This paper introduces PyProD, a Python-based machine learning (ML)-compatible test-bed for evaluating the efficacy of protection schemes in electric distribution grids. This testbed is designed to bridge the gap between conventional power distribution grid analysis and growing capability of ML-based decision making algorithms, in particular in the context of protection system design and configuration. PyProD is shown to be capable of facilitating efficient design and evaluation of ML-based decision making algorithms for protection devices in the future electric distribution grid, in which many distributed energy resources and pro-sumers permeate the system.
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。
