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DATA ANALYSIS FOR PES APPLICATIONS:AN INNOVATIVE USE OF DATA MINING TECHNIQUES

机译:PE应用程序的数据分析:数据挖掘技术的创新使用

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In this paper we analyze data mining methods and tools, highlighting the leading power system management applications where they are used. It's well-known that power energy system management requires handling an ever-growing amount of data coming from three main sources:1. field data recording devices, distributed throughout the system;2. centralized databases, storing data such as those coming from control SCADA systems;3. data warehouses storing data from simulations made while planning or maintaining the system and its components.The goal is to extract the information from the large amount of data we have, developing the opportunities for wiser ways to support decision making and the starting point for data processing is the discover of the patterns to be searched for and the definition of the models to be extracted from data.Data patterns and model are difficult to be discovered and their detection requires complex calculus and thorough specific domain knowledge. Moreover, even if one is a good expert in the field, there are patterns and models that human brain is not well-suited to find.
机译:在本文中,我们分析了数据挖掘方法和工具,重点介绍了使用它们的领先电力系统管理应用程序。众所周知,电力能源系统管理需要处理来自三个主要来源的数量不断增长的数据: 1.现场数据记录设备,分布在整个系统中; 2.集中式数据库,存储诸如来自控制SCADA系统的数据; 3.数据仓库,用于存储在计划或维护系统及其组件时进行的仿真得出的数据。 目的是从我们拥有的大量数据中提取信息,为更明智的决策支持方法提供机会,而数据处理的起点是发现要搜索的模式以及确定模型的方式从数据中提取。 数据模式和模型很难被发现,其检测需要复杂的演算和全面的特定领域知识。而且,即使一个人是该领域的优秀专家,也存在不适合人类大脑寻找的模式和模型。

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