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基于大数据的抽水蓄能服务电网研究与模型应用探索

Summary of Scientific and Technological Innovation and Research Results of Pumped Storage Service Grid Research

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【作者】 曹明良李国和孙勇魏敏

【Author】 CAO Mingliang;LI Guohe;SUN Yong;WEI Min;State Grid Xinyuan Compaany Ltd.;

【机构】 国网新源控股有限公司

【摘要】 抽水蓄能电站是电网中一种具有灵活运行特性、储能特质和事故安全备用的特殊电源,随着我国经济社会发展和能源结构调整,我国电力系统电源结构、电网规模、负荷特点、供需状况、跨区(省)输送和新能源发展发生根本性改变。本文在梳理了我国电力、抽蓄发展历程的基础上,基于电网侧、电站侧及互联网等数据,利用大数据技术手段,电网需求为导向,充分考虑了各区域电网差异性,提出了"基本功能—应用场景—服务定位多维时间尺度抽水蓄能服务电网模型"(简称FAS-T模型),利用时间尺度精准定位抽水蓄能的功能,从电网应用场景明确抽蓄在某一阶段所起到的作用,从宏观角度确定抽水蓄能的服务定位,从而形成一套规律可循的抽水蓄能服务电网功能定位理论模型。

【Abstract】 Pumped storage power station is a special power source with flexible operation characteristics, energy storage characteristics and accident safety backup. With the economic and social development and energy structure adjustment in China, China’s power system power supply structure, power grid scale, load characteristics, supply and demand situation Sub-regional(provincial) transportation and new energy development have undergone fundamental changes. Based on the development history of China’s electric power and pumping storage, based on the data of power grid side, power station side and Internet, this paper uses big data technology to guide the grid demand, fully considers the differences of regional power grids, and puts forward the basics. Function-application scenario-service positioning multi-dimensional time-scale pumped storage energy service grid mode(l FAS-T model for short), using time scale to accurately locate the function of pumped storage, clear from the grid application scenario at a certain stage The role of the service location of pumped storage is determined from a macroscopic perspective, thus forming a set of theoretical model for the functional positioning of the pumped storage service grid.

【关键词】 抽水蓄能服务电网大数据FAS-T模型
【Key words】 pumped storageservice gridbig dataFAS-T model
【基金】 国网新源控股有限公司资助项目:国网新源公司基于大数据分析的抽水蓄能电站服务电网能力研究项目(1D5746100001SGXY-2017FL01-2-3)
  • 【文献出处】 水电与抽水蓄能 ,Hydropower and Pumped Storage , 编辑部邮箱 ,2019年03期
  • 【分类号】TV743;TM73
  • 【被引频次】4
  • 【下载频次】150
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