發(fā)布時間：2018-03-15 00:26

  本文選題：風(fēng)電　切入點：時間序列　出處：《華中科技大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著全經(jīng)濟(jì)的發(fā)展,不可再生能源逐漸減少。為了應(yīng)對這一問題,新能源成為了發(fā)展和研究的熱門領(lǐng)域。風(fēng)能由于清潔和可再生成為了研究的重點,但是風(fēng)電的隨機(jī)性對電力系統(tǒng)帶來了重大的影響,同時我國風(fēng)資源分布不均,大型風(fēng)電生產(chǎn)基地都在遠(yuǎn)離負(fù)荷中心的位置,造成了輸送的困難,棄風(fēng)嚴(yán)重。為此必須對風(fēng)電出力的特性進(jìn)行詳細(xì)的分析,根據(jù)風(fēng)電特性制定相應(yīng)的電力系統(tǒng)建設(shè)與控制策略。目前對于風(fēng)電出力特性的研究大都停留在定性研究階段,無法全面的反映風(fēng)電出力特性,相關(guān)工作急需開展。風(fēng)電出力時間序列對于風(fēng)電接入電力系統(tǒng)的研究必不可少,目前已經(jīng)有大量關(guān)于短期風(fēng)電功率預(yù)測的研究,但此類研究計算方法復(fù)雜,預(yù)測時間大都不能超過3天,對于長時間尺度的風(fēng)電出力時間序列,主要有風(fēng)速和時間序列法,物理法根據(jù)風(fēng)速模型結(jié)合風(fēng)機(jī)出力曲線得到風(fēng)電功率,需要考慮尾流效應(yīng)等多種風(fēng)電場現(xiàn)實因素,計算復(fù)雜;時間序列法包括傳統(tǒng)的MCMC(蒙特卡洛馬爾科夫鏈)法和AMRA(自回歸滑動平均模型)法,它們都有著明顯的缺陷,對風(fēng)電出力特性的刻畫也不夠全面。為了解決以上兩個問題,本文對國內(nèi)外24個風(fēng)電場/群的歷史數(shù)據(jù)進(jìn)行了研究,總結(jié)了風(fēng)電出力的特性,包括均值方差,自相關(guān)系數(shù)、不同時間尺度的出力概率分布,波動特性等,并對不同年份的出力概率分布進(jìn)行了對比�；陲L(fēng)電出力的概率分布特性、自相關(guān)特性與波動特性,提出了使用Copula理論的時間序列生成方法,對該方法進(jìn)行了大量仿真分析,對比了國內(nèi)外風(fēng)電場原始序列以及MCMC方法生成的時間序列,驗證了該方法的精度,該方法能夠很好的反映風(fēng)電出力特性。
[Abstract]:With the development of the whole economy, non-renewable energy is gradually decreasing. In order to deal with this problem, new energy has become a hot area of development and research. Wind energy has become the focus of research because of clean and renewable energy. However, the randomness of wind power has a great impact on the power system. At the same time, the distribution of wind resources in China is uneven, and the large wind power production bases are located far from the load center, resulting in the difficulty of transmission. For this reason, the characteristics of wind power output must be analyzed in detail, and the corresponding power system construction and control strategies should be formulated according to the wind power characteristics. At present, the research on wind power output characteristics mostly stays at the stage of qualitative research. The wind power generation time series is indispensable for wind power to be connected to the power system, and there has been a lot of research on short-term wind power prediction. However, this kind of research and calculation methods are complex, and most of them can not be predicted for more than 3 days. For a long time scale wind power generation time series, there are mainly wind speed and time series methods. According to the wind speed model combined with the wind force curve, the physical method can get the wind power, which needs to consider the wake effect and other practical factors of wind farm, so the calculation is complicated. The time series methods include the traditional MCMC (Monte Carlo Markov chain) method and the AMRA( autoregressive moving average model) method. Both of them have obvious defects, and the characterization of wind power output characteristics is not comprehensive. In order to solve the above two problems, In this paper, the historical data of 24 wind farms / clusters at home and abroad are studied, and the characteristics of wind power output are summarized, including mean variance, autocorrelation coefficient, probability distribution of output force at different time scales, fluctuation characteristics, etc. Based on the probability distribution characteristics of wind power output, autocorrelation and fluctuation characteristics, a time series generation method using Copula theory is proposed, and a large number of simulations are carried out. By comparing the original sequence of wind farm at home and abroad and the time series generated by MCMC method, the accuracy of the method is verified, and the method can well reflect the characteristics of wind power output.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TM614

【相似文獻(xiàn)】

相關(guān)期刊論文 前3條

1 楊超;黃達(dá);張永興;吳俊宏;;基于Copula理論的巖體抗剪強(qiáng)度參數(shù)估值[J];巖石力學(xué)與工程學(xué)報;2013年12期

2 蔡菲;嚴(yán)正;趙靜波;馮冬涵;郭軍;胡殿剛;;基于Copula理論的風(fēng)電場間風(fēng)速及輸出功率相依結(jié)構(gòu)建模[J];電力系統(tǒng)自動化;2013年17期

3 ;[J];;年期

相關(guān)碩士學(xué)位論文 前1條

1 解陳力;基于風(fēng)電出力特性和Copula理論的風(fēng)電時間序列生成[D];華中科技大學(xué);2015年

，

本文編號：1613634