Review of Machine Learning in Power System

Zhibo Ma, Chi Zhang, Chen Qian
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引用次数: 8

Abstract

The trend of decentralisation and decarbonisation have been developed over the years. This has brought certain challenges to the prediction and control of the energy system using conventional method. There are some recent technology breakthrough in Machine Learning which has made some of the objectives achievable in many different aspects especially for the non-linear tasks. This paper has focused on reviewing the available machine learning technologies applied on the fault forecasting and load forecasting in power system.
电力系统机器学习研究进展
多年来,分散化和脱碳的趋势得到了发展。这给传统的能源系统预测与控制方法带来了一定的挑战。最近在机器学习方面有一些技术突破,这使得一些目标在许多不同的方面可以实现,特别是对于非线性任务。本文重点综述了现有的机器学习技术在电力系统故障预测和负荷预测中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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