發(fā)布時(shí)間：2018-01-31 12:31

  本文關(guān)鍵詞： 雙饋機(jī)組 次同步振蕩 奈奎斯特穩(wěn)定判據(jù) 復(fù)轉(zhuǎn)矩系數(shù)法 附加阻尼控制器 RBF神經(jīng)網(wǎng)絡(luò)　出處：《南京理工大學(xué)》2017年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：中國(guó)能源發(fā)展戰(zhàn)略已將大規(guī)模開(kāi)發(fā)利用風(fēng)電作為其重要組成部分。由于風(fēng)力資源與負(fù)荷需求分布不一致,需將風(fēng)電大容量、遠(yuǎn)距離地向外輸送。串聯(lián)補(bǔ)償電容技術(shù)具有減小輸電線(xiàn)路損耗并同時(shí)提高線(xiàn)路輸送容量的優(yōu)點(diǎn),可作為實(shí)現(xiàn)風(fēng)電大規(guī)模外送的技術(shù)支撐,但該技術(shù)的廣泛應(yīng)用,同樣存在可能誘發(fā)風(fēng)電場(chǎng)次同步振蕩的問(wèn)題,次同步振蕩的發(fā)生嚴(yán)重影響了大規(guī)模風(fēng)電基地及外送系統(tǒng)的安全穩(wěn)定運(yùn)行。針對(duì)含雙饋機(jī)組DFIG(Doubly-Fed Induction Generator)風(fēng)電場(chǎng)經(jīng)串補(bǔ)并網(wǎng)引起的次同步振蕩(Sub-synchronous Oscillation,SSO)問(wèn)題,本文進(jìn)行了以下方面的研究:1.對(duì)DFIG風(fēng)電場(chǎng)經(jīng)串聯(lián)電容并網(wǎng)系統(tǒng)進(jìn)行了詳細(xì)的數(shù)學(xué)建模,具體包括風(fēng)能捕獲的空氣動(dòng)力學(xué)模型、風(fēng)力機(jī)軸系傳動(dòng)系統(tǒng)模型、雙饋感應(yīng)發(fā)電機(jī)模型、直流電容動(dòng)態(tài)過(guò)程模型、轉(zhuǎn)子側(cè)變換器控制模型、網(wǎng)側(cè)變換器控制模型、輸線(xiàn)模型等。通過(guò)坐標(biāo)變換實(shí)現(xiàn)dq解耦控制,并對(duì)轉(zhuǎn)子側(cè)變換器和網(wǎng)側(cè)變換器的PI控制方式進(jìn)行了詳細(xì)闡述。2.用基于阻抗的奈奎斯特穩(wěn)定判據(jù)對(duì)DFIG風(fēng)電場(chǎng)次同步振蕩進(jìn)行初步分析,驗(yàn)證風(fēng)速、串聯(lián)補(bǔ)償度對(duì)風(fēng)電場(chǎng)次同步振蕩的影響。再通過(guò)復(fù)轉(zhuǎn)矩系數(shù)法進(jìn)行詳細(xì)分析,在發(fā)電機(jī)轉(zhuǎn)子上附加小信號(hào)增量,得到電氣阻尼曲線(xiàn),最后使用時(shí)域仿真法直觀(guān)的驗(yàn)證了分析結(jié)果。當(dāng)風(fēng)速越小、串補(bǔ)度越大,就越容易發(fā)生感應(yīng)發(fā)電機(jī)效應(yīng)(induction generator effect,IGE),引發(fā)次同步振蕩。此外,轉(zhuǎn)子側(cè)變換器的電流內(nèi)環(huán)的比例和積分參數(shù)越大,越容易導(dǎo)致由風(fēng)電機(jī)組控制器引發(fā)的次同步控制相互作用(sub-synchronous control interaction,SSCI),這是風(fēng)電場(chǎng)特有的次同步振蕩形式。3.在DFIG風(fēng)電場(chǎng)次同步振蕩機(jī)理分析的基礎(chǔ)上,采用附加阻尼控制器的方法來(lái)抑制次同步振蕩。用復(fù)轉(zhuǎn)矩系數(shù)法得到的電氣阻尼最低點(diǎn)的頻率和需要補(bǔ)償?shù)慕嵌?來(lái)計(jì)算附加阻尼控制器的移相環(huán)節(jié)參數(shù),并利用粒子群智能算法對(duì)附加阻尼控制器的參數(shù)進(jìn)行尋優(yōu),附加阻尼控制器可以補(bǔ)償電氣阻尼,提高系統(tǒng)的穩(wěn)定性。4.本文提出了轉(zhuǎn)子側(cè)變換器電磁轉(zhuǎn)矩Te控制外環(huán)采用RBF神經(jīng)網(wǎng)絡(luò)控制取代傳統(tǒng)PI控制的方法。在不同風(fēng)速及不同串補(bǔ)的情況下,轉(zhuǎn)矩環(huán)的RBF神經(jīng)網(wǎng)絡(luò)的自學(xué)習(xí)能力使得PID控制器具有自適應(yīng)性,可適應(yīng)雙饋風(fēng)電場(chǎng)不同串補(bǔ)以及不同風(fēng)速下的復(fù)雜的運(yùn)行工況。采用傳統(tǒng)PI控制參數(shù)會(huì)誘發(fā)次同步振蕩,仿真證明本文所設(shè)計(jì)的RBF神經(jīng)網(wǎng)絡(luò)控制器對(duì)次同步振蕩具有良好的抑制效果。
[Abstract]:The large-scale development and utilization of wind power has been regarded as an important part of China's energy development strategy. Because the distribution of wind power resources and load demand is not consistent, large capacity of wind power is needed. The series compensation capacitor technology has the advantages of reducing the transmission line loss and increasing the transmission capacity at the same time. It can be used as the technical support to realize large-scale wind power delivery, but this technology is widely used. It is also possible to induce sub-synchronous oscillation in wind farms. The occurrence of sub-synchronous oscillation has seriously affected the safe and stable operation of large-scale wind power base and outgoing system. The subsynchronous oscillation of Doubly-Fed Induction generator wind farm caused by serialization and grid connection (. Sub-synchronous Oscillation. In this paper, the following aspects are studied: 1. The detailed mathematical model of DFIG wind farm through the series capacitance grid-connected system, including the aerodynamic model of wind energy capture, is presented in this paper. Wind turbine shafting transmission system model, doubly-fed induction generator model, DC capacitor dynamic process model, rotor side converter control model, grid-side converter control model. Through coordinate transformation, dq decoupling control is realized. The Pi control mode of the rotor side converter and the grid side converter is described in detail. 2. The subsynchronous oscillation of DFIG wind farm is preliminarily analyzed by using the Nyquist stability criterion based on impedance to verify the wind speed. The influence of series compensation degree on the sub-synchronous oscillation of wind farm is analyzed in detail by the method of complex torque coefficient, and the electrical damping curve is obtained by adding small signal increment to the generator rotor. Finally, the time domain simulation method is used to verify the analysis results intuitively. When the wind speed is smaller, the series compensation degree is larger. The more likely the induction generator effect generator effect will lead to subsynchronous oscillation. The ratio and integral parameters of the current inner loop of the rotor side converter are larger. The more easily the sub-synchronous control interaction caused by the wind turbine controller is caused by SSCI). This is the special sub-synchronous oscillation form of wind farm. 3. Based on the analysis of sub-synchronous oscillation mechanism of DFIG wind farm. The method of additional damping controller is used to suppress the sub-synchronous oscillation, and the phase shift parameters of the additional damping controller are calculated by using the frequency of the lowest point of electrical damping obtained by the method of complex torque coefficient and the angle to be compensated. Particle swarm optimization algorithm is used to optimize the parameters of the additional damping controller, which can compensate the electrical damping. In this paper, the RBF neural network control is used to replace the traditional Pi control in the outer loop of electromagnetic torque Te control of the rotor side converter. Under different wind speed and different series compensation, this paper proposes a method to improve the stability of the system. The self-learning ability of the torque loop RBF neural network makes the PID controller self-adaptive. It can adapt to complicated operation conditions under different series compensation and different wind speed of doubly-fed wind farm. Using traditional Pi control parameters can induce sub-synchronous oscillation. The simulation results show that the designed RBF neural network controller has good suppression effect on subsynchronous oscillation.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TM614;TM712

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