【摘要】：風(fēng)電出力時(shí)間序列的生成是研究含風(fēng)電場(chǎng)的電力系統(tǒng)工作的前提�；跉v史風(fēng)電出力波動(dòng)特性,提出一種構(gòu)造風(fēng)電出力時(shí)間序列的方法,首先,將歷史風(fēng)電出力序列做小波濾波處理,得到較為光滑的風(fēng)電出力曲線,該曲線可看作由大小不同的波動(dòng)組成,進(jìn)一步分析不同波動(dòng)類別下小波濾波誤差的概率分布;其次,根據(jù)波峰值將波動(dòng)劃分成不同類別,并以高斯函數(shù)擬合,統(tǒng)計(jì)各月份不同類別波動(dòng)的高斯擬合函數(shù)參數(shù)的多維概率分布及波峰間隔的一維概率分布,以馬爾科夫轉(zhuǎn)移矩陣描述不同波動(dòng)類別之間的轉(zhuǎn)換概率;最后,根據(jù)統(tǒng)計(jì)結(jié)果序貫隨機(jī)抽樣波動(dòng)類別及各統(tǒng)計(jì)參數(shù),模擬生成各月風(fēng)電出力序列。通過(guò)對(duì)比歷史風(fēng)電出力序列與模擬風(fēng)電出力序列的評(píng)價(jià)指標(biāo),驗(yàn)證了該文方法的合理性。
[Abstract]:The generation of the time series of wind power output is the premise to study the work of the power system with wind electric field. Based on the characteristics of the historical wind power output, a method of constructing the time series of the wind power output is proposed. First, the historical wind power sequence is processed by the wavelet filtering to get the more smooth wind power output curve, which can be regarded as the size of the wind power. The probability distribution of the wavelet filtering error under different fluctuation categories is further analyzed. Secondly, according to the wave peak value, the fluctuation is divided into different categories, and the Gauss function is used to fit the multidimensional probability distribution of the Gauss fitting function parameters of different types of fluctuation in each month and the one dimension probability distribution of the wave peak interval. Kopf transfer matrix describes the conversion probability between different types of fluctuation. Finally, according to the statistical results of random sampling and the statistical parameters, the wind power sequence of each month is simulated, and the rationality of the method is verified by comparing the historical wind power sequence and the evaluation index of the simulated wind power output sequence.
【作者單位】： 華北電力大學(xué)電氣與電子工程學(xué)院;
【基金】：國(guó)家電網(wǎng)公司科技項(xiàng)目(5230JY14003R)
【分類號(hào)】：TM614

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本文編號(hào)：2173609