【摘要】：風(fēng)電并網(wǎng)影響系統(tǒng)經(jīng)濟(jì)性和安全性。為提高風(fēng)電系統(tǒng)經(jīng)濟(jì)性,有必要量化分析并網(wǎng)風(fēng)電對(duì)網(wǎng)損的影響�？紤]雙饋感應(yīng)風(fēng)電機(jī)組(Double-Fed Induction Generator,DFIG)內(nèi)部損耗時(shí),受風(fēng)速變化影響的機(jī)組有功出力在潮流求解前未知,傳統(tǒng)網(wǎng)損靈敏度模型不能直接反應(yīng)風(fēng)速波動(dòng)的影響,無法直接用于含DFIG的風(fēng)電系統(tǒng)。同時(shí)隨著風(fēng)電并網(wǎng)容量增加,需要風(fēng)電機(jī)組參與系統(tǒng)調(diào)頻以維持頻率安全性。動(dòng)態(tài)潮流算法將功率擾動(dòng)分擔(dān)給調(diào)頻機(jī)組,可量化系統(tǒng)頻率,在穩(wěn)態(tài)分析中常用于計(jì)算功率擾動(dòng)后系統(tǒng)潮流分布與頻率偏移。現(xiàn)有動(dòng)態(tài)潮流文獻(xiàn)針對(duì)同步機(jī)組,未考慮風(fēng)電機(jī)組參與系統(tǒng)調(diào)頻。針對(duì)上述問題,本文基于DFIG詳細(xì)潮流模型,對(duì)含DFIG風(fēng)電系統(tǒng)的網(wǎng)損優(yōu)化和動(dòng)態(tài)潮流算法進(jìn)行了研究,論文主要內(nèi)容和創(chuàng)新點(diǎn)如下:(1)基于最大功率點(diǎn)跟蹤方式,擴(kuò)展傳統(tǒng)網(wǎng)損靈敏度模型,提出系統(tǒng)有功網(wǎng)損對(duì)風(fēng)速靈敏度,以量化風(fēng)速對(duì)有功網(wǎng)損的影響程度和趨勢(shì)。算例結(jié)果表明負(fù)的靈敏度指標(biāo)反映系統(tǒng)有功網(wǎng)損隨風(fēng)速上升而減小,反之隨風(fēng)速上升而增大;靈敏度指標(biāo)絕對(duì)值越大,風(fēng)速對(duì)有功網(wǎng)損影響越明顯。所提靈敏度指標(biāo)可作為風(fēng)電機(jī)組無功控制方式和風(fēng)電場(chǎng)并網(wǎng)位置選擇的輔助參考依據(jù)。(2)引入DFIG內(nèi)部約束,基于DFIG具體調(diào)頻策略在動(dòng)態(tài)潮流計(jì)算中修正其相關(guān)參數(shù),使其參與系統(tǒng)一次調(diào)頻;量化DFIG機(jī)組慣性使其參與加速功率分擔(dān),提出考慮DFIG參與系統(tǒng)一次調(diào)頻的動(dòng)態(tài)潮流模型。結(jié)合算例發(fā)現(xiàn)DFIG慣性受風(fēng)速和減載水平影響;系統(tǒng)加速功率為負(fù)時(shí),在相同減載水平下,輸入風(fēng)速越高,DFIG機(jī)組有功備用越大,對(duì)系統(tǒng)頻率支持能力越強(qiáng)。(3)現(xiàn)有經(jīng)濟(jì)調(diào)度研究雖有涉及系統(tǒng)頻率和SG調(diào)頻能力,但忽略風(fēng)電或以風(fēng)電功率代替具體風(fēng)電機(jī)組。為在經(jīng)濟(jì)調(diào)度中考慮DFIG的一次調(diào)頻能力,將上節(jié)所述考慮DFIG參與調(diào)頻的動(dòng)態(tài)潮流算法引入經(jīng)濟(jì)調(diào)度,提出計(jì)及DFIG參與一次調(diào)頻的概率最優(yōu)潮流模型。模型計(jì)及風(fēng)速預(yù)測(cè)誤差概率特性,通過權(quán)重系數(shù)在優(yōu)化目標(biāo)中引入預(yù)測(cè)誤差引起的頻率偏移。結(jié)合算例驗(yàn)證了所提模型的有效性,發(fā)現(xiàn)通過選擇適合的目標(biāo)函數(shù)權(quán)重系數(shù),可兼顧發(fā)電成本和預(yù)測(cè)誤差引起的頻率偏移,以獲得較好的經(jīng)濟(jì)性和安全性。
[Abstract]:Wind power grid connection affects system economy and safety. In order to improve the economy of wind power system, it is necessary to quantitatively analyze the influence of grid-connected wind power on network loss. Considering the internal loss of Double-Fed Induction induction wind turbine (Double-Fed Induction generator), the active power output of the unit affected by the wind speed change is unknown before the power flow is solved, and the traditional network loss sensitivity model can not directly reflect the influence of wind speed fluctuation. Cannot be directly used in wind power systems with DFIG. At the same time, with the increase of wind power grid capacity, wind turbines are required to participate in frequency regulation to maintain frequency safety. The dynamic power flow algorithm shares the power disturbance to the frequency modulation unit and quantifies the frequency of the system. It is often used to calculate the power flow distribution and frequency offset of the system after the power disturbance in the steady-state analysis. The existing dynamic power flow literature is aimed at synchronous units and does not consider the wind turbine participating in the frequency modulation of the system. Aiming at the above problems, based on the detailed power flow model of DFIG, this paper studies the power loss optimization and dynamic power flow algorithm of wind power system with DFIG. The main contents and innovations of this paper are as follows: (1) based on the maximum power point tracking method, Based on the traditional sensitivity model of network loss, the sensitivity of active power network loss to wind speed is proposed to quantify the influence degree and trend of wind speed on active power network loss. The results show that the negative sensitivity index reflects that the active power network loss decreases with the increase of the wind speed, whereas increases with the increase of the wind speed, and the greater the absolute value of the sensitivity index, the more obvious the influence of the wind speed on the loss of the active power network. The proposed sensitivity index can be used as an auxiliary reference for wind turbine reactive power control mode and wind farm grid connection location selection. (2) introducing DFIG internal constraints and modifying its parameters in dynamic power flow calculation based on specific frequency modulation strategy of DFIG. The dynamic power flow model considering the participation of DFIG in the primary frequency modulation of the system is put forward by quantifying the inertia of the DFIG unit to make it participate in the acceleration power sharing. Combined with an example, it is found that the inertia of DFIG is affected by wind speed and load reduction level, and when the acceleration power of the system is negative, under the same load reduction level, the higher the input wind speed is, the greater the active power reserve of the unit is. The stronger the system frequency support ability is. (3) although the current economic dispatch research involves the system frequency and SG frequency modulation capability, it ignores the wind power or replaces the specific wind turbine with wind power. In order to consider the primary frequency modulation capability of DFIG in economic scheduling, the dynamic power flow algorithm considering the participation of DFIG in frequency modulation is introduced into economic scheduling, and a probabilistic optimal power flow model considering DFIG participation in primary frequency modulation is proposed. Considering the probability characteristic of wind speed prediction error, the frequency offset caused by prediction error is introduced into the optimization target by weight coefficient. The validity of the proposed model is verified by an example. It is found that by selecting the appropriate weight coefficient of the objective function, the generation cost and the frequency offset caused by the prediction error can be taken into account in order to obtain better economy and security.
【學(xué)位授予單位】：合肥工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM614

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