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含大型風(fēng)電場的電力系統(tǒng)潮流優(yōu)化研究

發(fā)布時間:2018-03-20 05:20

  本文選題:風(fēng)電場 切入點:風(fēng)速相關(guān)性 出處:《華北電力大學(xué)》2014年碩士論文 論文類型:學(xué)位論文


【摘要】:鑒于風(fēng)電的隨機性與相關(guān)性等不確定性因素,如何在保證安全和可靠供電的前提下更加合理地利用風(fēng)能,是一個亟待解決且十分必要的問題。電力系統(tǒng)的最優(yōu)潮流為上述問題提供了有效的解決途徑。針對有大型風(fēng)電場接入的電力系統(tǒng)的潮流優(yōu)化問題,研究與探討了風(fēng)電場分組等值建模、具有相關(guān)性的風(fēng)電場風(fēng)速建模、含風(fēng)電場電力系統(tǒng)的最優(yōu)潮流模型與計算,提出了新的建模算法,為含風(fēng)電場電力系統(tǒng)的潮流優(yōu)化研究提供了新的思路。 考慮風(fēng)電場內(nèi)機組間尾流的相互影響,,提出了一種計及尾流效應(yīng)的風(fēng)電場等值建模方法。該方法定義了“尾流影響因子”以表征機組間尾流影響的程度,并以此作為風(fēng)電場內(nèi)風(fēng)電機組的分組依據(jù)。對風(fēng)電機組進行分組及合并等值后,得到風(fēng)電場的多機等值模型。算例結(jié)果顯示,與傳統(tǒng)等值方法相比,該模型更加準(zhǔn)確地體現(xiàn)了風(fēng)電場的功率輸出特性。 針對風(fēng)電場間風(fēng)速具有相關(guān)性的特點,提出了基于Copula函數(shù)的相關(guān)性風(fēng)速建模方法。該方法利用Copula函數(shù)構(gòu)建多風(fēng)電場間風(fēng)速的聯(lián)合概率分布,進而生成具有相關(guān)性的風(fēng)速分布樣本空間,根據(jù)風(fēng)電機組的出力特性可得到各風(fēng)電場出力。算例表明,模型有效地描述了風(fēng)電場間具有相關(guān)性的風(fēng)速,得到的多元風(fēng)速樣本可用于含風(fēng)電場集群的電力系統(tǒng)的潮流優(yōu)化分析。 傳統(tǒng)的最優(yōu)潮流模型與算法多以確定性模型作為前提,然而風(fēng)電的接入為電力系統(tǒng)帶來了不確定性因素?紤]到這一問題,介紹了基于機會約束規(guī)劃的最優(yōu)潮流模型,并利用基于隨機模擬技術(shù)的粒子群優(yōu)化算法作為求解方法。 風(fēng)電場的接入勢必對電力系統(tǒng)的可用輸電能力(ATC)產(chǎn)生影響,在上述模型的基礎(chǔ)上,建立了基于最優(yōu)潮流的含風(fēng)電場電力系統(tǒng)的ATC計算模型,并對模型進行了求解。IEEE30節(jié)點和IEEE118節(jié)點測試系統(tǒng)算例表明,風(fēng)速的隨機性和相關(guān)性、風(fēng)電場所在的節(jié)點位置、機會約束規(guī)劃的置信水平等因素都對系統(tǒng)的可用輸電能力有一定影響,為含風(fēng)電場電力系統(tǒng)的規(guī)劃與運行提供了參考和依據(jù)。
[Abstract]:In view of the uncertainties such as the randomness and correlation of wind power, how to make more rational use of wind energy on the premise of ensuring safe and reliable power supply, The optimal power flow of power system provides an effective way to solve the above problems. This paper studies and discusses wind farm grouping equivalent modeling, wind speed modeling with correlation, optimal power flow model and calculation of wind farm power system, and puts forward a new modeling algorithm. It provides a new idea for the study of power flow optimization in power system with wind farm. Considering the interaction between units in wind farm, a wind farm equivalent modeling method considering wake effect is proposed. In this method, the "wake influence factor" is defined to characterize the degree of wakes influence between units. After grouping and merging the wind turbine units, the multi-machine equivalent model of wind farm is obtained. The results show that compared with the traditional equivalent method, the wind power unit is divided into two groups. The model more accurately reflects the power output characteristics of the wind farm. According to the correlation of wind speed between wind farms, a method of wind speed modeling based on Copula function is proposed, which uses Copula function to construct the joint probability distribution of wind speed between multi-wind farms. Then the wind velocity distribution sample space with correlation is generated, and the wind farm output force can be obtained according to the wind turbine output characteristics. Numerical examples show that the model can effectively describe the wind speed with correlation between wind farms. The multivariate wind speed samples obtained can be used for power flow optimization analysis of power systems with wind farm clusters. Most of the traditional optimal power flow models and algorithms are based on deterministic models, but the access of wind power brings uncertainty to power system. Considering this problem, an optimal power flow model based on opportunistic constrained programming is introduced. The particle swarm optimization algorithm based on stochastic simulation technology is used as the solution. The connection of wind farm is bound to have an effect on the available transmission capacity of power system. Based on the above model, the ATC calculation model of power system with wind farm based on optimal power flow is established. An example of the test system for solving the. IEEE30 and IEEE118 nodes shows that the wind speed is randomness and correlation, and the location of the node in which the wind farm is located. The confidence level of the chance constrained programming has a certain influence on the available transmission capacity of the system, which provides a reference and basis for the planning and operation of the power system with wind farm.
【學(xué)位授予單位】:華北電力大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2014
【分類號】:TM614

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