【摘要】：由于能源短缺和環(huán)境污染問(wèn)題日益嚴(yán)重,風(fēng)能作為一種可再生、無(wú)污染的新能源得到了大力的推廣,同時(shí)風(fēng)力發(fā)電技術(shù)也已經(jīng)發(fā)展成熟,接入電網(wǎng)的風(fēng)電容量逐漸增加。但是風(fēng)力發(fā)電的波動(dòng)性和不可控性對(duì)電力系統(tǒng)安全可靠運(yùn)行產(chǎn)生了影響,因此對(duì)計(jì)及風(fēng)電場(chǎng)電力系統(tǒng)進(jìn)行可靠性評(píng)估顯得尤為重要。本文介紹了計(jì)及風(fēng)電場(chǎng)的發(fā)輸電系統(tǒng)可靠性評(píng)估的流程,主要是對(duì)風(fēng)電場(chǎng)的風(fēng)速建模預(yù)測(cè)、風(fēng)電場(chǎng)可靠性建模和結(jié)合可靠性評(píng)估方法對(duì)發(fā)輸電系統(tǒng)可靠性進(jìn)行研究。主要工作如下所示:1.針對(duì)時(shí)間序列法在非平穩(wěn)風(fēng)速預(yù)測(cè)中精度差的問(wèn)題,本文提出了一種ARIMA-BP組合預(yù)測(cè)模型,有效的提高了非平穩(wěn)風(fēng)速序列的預(yù)測(cè)精度。2.考慮到風(fēng)電場(chǎng)風(fēng)速的獨(dú)特性,建立風(fēng)電場(chǎng)模型,主要包括風(fēng)電場(chǎng)輸出功率模型、風(fēng)電場(chǎng)尾流效應(yīng)模型和風(fēng)機(jī)停運(yùn)模型,為下文中的可靠性評(píng)估打下基礎(chǔ)。3.結(jié)合重要抽樣和控制變量思想的改進(jìn)了重要抽樣法,該方法結(jié)合了重要抽樣法和控制變量法的特性,同時(shí)在重要抽樣里面采用舍取控制法選取適合重要概率函數(shù),最終實(shí)現(xiàn)系統(tǒng)的狀態(tài)概率分布函數(shù)的優(yōu)化,避免在常規(guī)蒙特卡羅法電力系統(tǒng)可靠性評(píng)估過(guò)程中效率偏低和算法退化的問(wèn)題,有效地提高了電力系統(tǒng)可靠性評(píng)估的計(jì)算效率。4.根據(jù)改進(jìn)的重要抽樣法對(duì)接入風(fēng)電場(chǎng)的IEEE-RTS可靠性測(cè)試系統(tǒng)進(jìn)行可靠性評(píng)估,計(jì)算可靠性指標(biāo)和收斂判據(jù),驗(yàn)證該算法的優(yōu)越性。
[Abstract]:As a result of energy shortage and environmental pollution, wind energy as a renewable, non-polluting new energy has been vigorously promoted. At the same time, wind power generation technology has been developed and the wind capacity connected to the power grid has gradually increased. However, the volatility and uncontrollability of wind power generation have an impact on the safe and reliable operation of power system, so it is very important to evaluate the reliability of power system considering wind farm. This paper introduces the process of reliability evaluation of power generation and transmission system considering wind farm, mainly studies the wind speed modeling and prediction of wind farm, the reliability modeling of wind farm and the reliability evaluation method of power generation and transmission system. The main work is as follows: 1. In order to solve the problem of poor precision of time series method in the prediction of non-stationary wind speed, this paper presents a ARIMA-BP combined forecasting model, which can effectively improve the prediction accuracy of non-stationary wind speed series. 2. Considering the uniqueness of wind speed of wind farm, the wind farm model is established, which includes wind farm output power model, wind farm wake effect model and wind turbine outage model. The important sampling method is improved by combining the important sampling and the control variable idea. The method combines the characteristics of the important sampling method and the control variable method. At the same time, the appropriate important probability function is selected by the rejection control method in the important sampling. Finally, the state probability distribution function of the power system is optimized to avoid the problems of low efficiency and algorithm degradation in the process of reliability evaluation of power system by conventional Monte Carlo method, and the computational efficiency of power system reliability evaluation is improved effectively. 4. According to the improved important sampling method, the reliability of IEEE-RTS reliability test system connected to wind farm is evaluated, the reliability index and convergence criterion are calculated, and the superiority of the algorithm is verified.
【學(xué)位授予單位】：上海電機(jī)學(xué)院
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TM614

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