本文選題：光伏出力 + 隨機(jī)性��； 參考：《電力系統(tǒng)自動(dòng)化》2017年01期

【摘要】：準(zhǔn)確刻畫(huà)光伏出力的隨機(jī)特性對(duì)分析光伏電站并網(wǎng)的影響具有重要的作用。然而受日地運(yùn)動(dòng)和大尺度天氣過(guò)程影響,光伏出力整體上卻表現(xiàn)出日周期性和年周期性而并非一個(gè)單純的隨機(jī)序列,因此從光伏出力序列中區(qū)分規(guī)律性與隨機(jī)性特征并正確提取出其隨機(jī)性分量顯得尤為重要。根據(jù)不同物理因素的影響,基于太陽(yáng)輻射模型和最小二乘原理,提出了一種光伏出力隨機(jī)性分量的提取方法。基于該提取方法,利用甘肅及德國(guó)的光伏實(shí)測(cè)數(shù)據(jù)對(duì)所提隨機(jī)性分量進(jìn)行了詳細(xì)的統(tǒng)計(jì)特性分析。
[Abstract]:It is very important to describe the random characteristics of photovoltaic output accurately for analyzing the influence of grid-connected photovoltaic power station. However, under the influence of solar-terrestrial motion and large-scale weather processes, photovoltaic forces on the whole show diurnal periodicity and annual periodicity rather than a simple random sequence. Therefore, it is very important to distinguish the regularity and randomness from the photovoltaic force sequence and extract the random components correctly. Based on the solar radiation model and the least square principle, a method for extracting the random components of photovoltaic force is proposed according to the influence of different physical factors. Based on this method, the statistical characteristics of the random components are analyzed in detail by using the measured photovoltaic data from Gansu and Germany.
【作者單位】： 強(qiáng)電磁工程與新技術(shù)國(guó)家重點(diǎn)實(shí)驗(yàn)室(華中科技大學(xué));ABB(中國(guó))有限公司 ABB中國(guó)研究院;
【基金】：國(guó)家重點(diǎn)研發(fā)計(jì)劃智能電網(wǎng)技術(shù)與裝備專(zhuān)項(xiàng)項(xiàng)目(2016YFB0900400,2016YFB0900403)~~
【分類(lèi)號(hào)】：TM615

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