本文選題：長(zhǎng)期電壓穩(wěn)定性 + 電壓穩(wěn)定動(dòng)態(tài)分析　； 參考：《山東大學(xué)》2014年博士論文

【摘要】：隨著電網(wǎng)規(guī)模的擴(kuò)大和結(jié)構(gòu)的加強(qiáng),電網(wǎng)已逐漸進(jìn)入發(fā)展飽和期。現(xiàn)階段負(fù)荷中心水平不斷增長(zhǎng),但由于環(huán)境資源的限制難以新建場(chǎng)站和線路走廊,遠(yuǎn)距離重負(fù)荷輸電的局面將會(huì)日益突出,電力系統(tǒng)的運(yùn)行越來(lái)越接近其穩(wěn)定極限。雖然電網(wǎng)在規(guī)劃時(shí)保留了一定的電壓穩(wěn)定裕度,但在遭受嚴(yán)重?cái)_動(dòng)時(shí)仍可能發(fā)生電壓不穩(wěn)定事故。電壓穩(wěn)定問(wèn)題已經(jīng)成為現(xiàn)階段電力系統(tǒng)規(guī)劃和運(yùn)行中的主要關(guān)注問(wèn)題之一。按照時(shí)間尺度和動(dòng)態(tài)演化特征電壓穩(wěn)定可以分為短期電壓穩(wěn)定和長(zhǎng)期電壓穩(wěn)定,幾十年來(lái),國(guó)內(nèi)外發(fā)生了多起由于長(zhǎng)期電壓失穩(wěn)導(dǎo)致的大面積停電事故,失穩(wěn)主要原因在于負(fù)荷的自恢復(fù)特性使其功率需求超出了輸電和發(fā)電系統(tǒng)容量,需要及時(shí)采取協(xié)調(diào)控制措施防止電壓崩潰。由于長(zhǎng)期電壓穩(wěn)定性問(wèn)題的混雜動(dòng)態(tài)特性和系統(tǒng)行為的不確定性,預(yù)測(cè)模型的精確度和計(jì)算速度成為制約在線電壓協(xié)調(diào)控制效果和可行性的重要因素。發(fā)展適合在線應(yīng)用的長(zhǎng)期電壓協(xié)調(diào)控制方法,對(duì)于防止因電壓崩潰而導(dǎo)致的大停電事故具有重要的理論意義和工程應(yīng)用價(jià)值。 在上述背景下,本文的研究把握長(zhǎng)期電壓穩(wěn)定動(dòng)態(tài)特征,量化分析電壓軌跡對(duì)于控制措施的響應(yīng)特性,基于滾動(dòng)時(shí)域的控制方法在線求取最優(yōu)電壓控制序列。針對(duì)適用于在線決策的預(yù)測(cè)模型,優(yōu)化約束,控制策略等一系列問(wèn)題進(jìn)行了研究與探索。論文的主要研究工作和創(chuàng)新成果如下： (1)電壓協(xié)調(diào)控制的優(yōu)化決策集規(guī)模由優(yōu)化目標(biāo)節(jié)點(diǎn)和控制器的數(shù)目決定。在實(shí)際應(yīng)用中,優(yōu)化目標(biāo)節(jié)點(diǎn)和控制器數(shù)量龐大,面臨決策集爆炸的難題。由于電壓控制局部性的特點(diǎn),與爆炸增長(zhǎng)的原始決策變量相比,系統(tǒng)故障場(chǎng)景中求取優(yōu)化解中的動(dòng)作控制器數(shù)目始終維持在一個(gè)較小的規(guī)模,因此對(duì)備選決策集進(jìn)行篩選是必要的。論文基于模型預(yù)測(cè)控制的思想,提出了一種滾動(dòng)篩選電壓協(xié)調(diào)控制決策集的方法。將電壓幅值和軌跡靈敏度信息作為聚類特征指標(biāo),經(jīng)過(guò)原始數(shù)據(jù)標(biāo)準(zhǔn)化后形成模糊相似矩陣,在此基礎(chǔ)上采用模糊聚類方法確定優(yōu)化目標(biāo)節(jié)點(diǎn)。根據(jù)優(yōu)化目標(biāo)節(jié)點(diǎn)電壓對(duì)于控制的響應(yīng)特性,在各控制時(shí)域初始時(shí)刻滾動(dòng)篩選控制措施。由于聚類特征指標(biāo)均源自于模型預(yù)測(cè)計(jì)算的過(guò)程量,決策集的篩選過(guò)程幾乎不消耗額外計(jì)算時(shí)間；聚類和篩選方法均考慮了電壓的動(dòng)態(tài)響應(yīng)特性,相比傳統(tǒng)的靜態(tài)指標(biāo)可以更好地計(jì)及系統(tǒng)的動(dòng)態(tài)演化趨勢(shì)。仿真結(jié)果表明,提出方法能夠在取得全局協(xié)調(diào)控制效果的前提下,大幅降低備選決策集規(guī)模,有效避免電壓協(xié)調(diào)控制的決策集爆炸問(wèn)題。 (2)基于靜態(tài)分析方法的電壓協(xié)調(diào)控制無(wú)法計(jì)及系統(tǒng)的混雜動(dòng)態(tài)特性,且依賴于系統(tǒng)穩(wěn)定平衡點(diǎn)的存在；基于動(dòng)態(tài)分析的電壓協(xié)調(diào)控制雖然能夠避免上述問(wèn)題,但通常以系統(tǒng)代數(shù)量作為優(yōu)化目標(biāo)和約束,能夠確保系統(tǒng)電壓軌跡漸進(jìn)穩(wěn)定,并使相關(guān)代數(shù)量保持在約束范圍內(nèi),但無(wú)法確保系統(tǒng)穩(wěn)定裕度滿足要求。本文提出了一種計(jì)及穩(wěn)定裕度約束的電壓協(xié)調(diào)控制方法,在電壓值協(xié)調(diào)控制時(shí)域的初始時(shí)刻,通過(guò)增加負(fù)荷功率識(shí)別系統(tǒng)在穩(wěn)定極限點(diǎn)處的分岔方式。建立相應(yīng)分岔情況下的電壓穩(wěn)定裕度指標(biāo)并推導(dǎo)其對(duì)于控制措施的靈敏度,并在此基礎(chǔ)上構(gòu)建當(dāng)前控制時(shí)域內(nèi)的電壓穩(wěn)定裕度約束。若優(yōu)化時(shí)刻系統(tǒng)存在穩(wěn)定平衡點(diǎn),則電壓協(xié)調(diào)控制模型中考慮穩(wěn)定裕度約束；反之則僅針對(duì)電壓幅值進(jìn)行優(yōu)化。優(yōu)化過(guò)程以采樣周期為間隔在線滾動(dòng)進(jìn)行,不僅能夠?qū)收虾蟮碾妷悍颠M(jìn)行優(yōu)化,還能夠確保系統(tǒng)維持一定的穩(wěn)定裕度。 (3)電力系統(tǒng)在運(yùn)行過(guò)程中存在很多不確定因素,且長(zhǎng)期電壓穩(wěn)定時(shí)間尺度下的綜合負(fù)荷難以精確建模,電壓協(xié)調(diào)控制研究中使用的預(yù)測(cè)模型幾乎不可能與實(shí)際系統(tǒng)運(yùn)行狀態(tài)完全匹配。采用模型預(yù)測(cè)控制方法進(jìn)行電壓協(xié)調(diào)控制能夠在一定程度上解決上述問(wèn)題,但其控制效果受控制時(shí)域參數(shù)的影響較大。在其他時(shí)域參數(shù)不變的情況下,控制時(shí)域越小,需要求取的控制步數(shù)越少,相應(yīng)計(jì)算時(shí)間越少,控制決策更加激進(jìn),但有可能會(huì)進(jìn)一步擴(kuò)大模型不匹配誤差,降低優(yōu)化效率；控制時(shí)域越大,控制效果更加平滑,但計(jì)算時(shí)間也會(huì)隨之增加�，F(xiàn)有研究均根據(jù)具體算例確定控制時(shí)域參數(shù),且控制時(shí)域參數(shù)在優(yōu)化過(guò)程中恒定不變。針對(duì)上述情況,提出了一種基于自適應(yīng)控制時(shí)域參數(shù)的電壓協(xié)調(diào)控制策略。預(yù)測(cè)時(shí)域內(nèi)通過(guò)時(shí)域仿真確定評(píng)估目標(biāo)節(jié)點(diǎn),并求取電壓對(duì)于備選控制措施的軌跡靈敏度,取每個(gè)預(yù)測(cè)時(shí)域結(jié)束時(shí)刻評(píng)估目標(biāo)節(jié)點(diǎn)電壓對(duì)于備選控制的軌跡靈敏度建立靈敏度矩陣,在控制調(diào)節(jié)速率的約束下評(píng)估當(dāng)前優(yōu)化步數(shù)下的評(píng)估目標(biāo)節(jié)點(diǎn)的累計(jì)電壓最大恢復(fù)值,建立極限調(diào)壓能力指標(biāo),根據(jù)該指標(biāo)在優(yōu)化過(guò)程中自適應(yīng)調(diào)整控制時(shí)域參數(shù),使其能夠根據(jù)系統(tǒng)運(yùn)行狀態(tài)及演化趨勢(shì)自適應(yīng)調(diào)整：在系統(tǒng)故障初期,電壓偏移較大,為防止大幅度調(diào)節(jié)控制器加劇模型不匹配導(dǎo)致的預(yù)測(cè)偏差,降低優(yōu)化效率,優(yōu)化會(huì)采用較大的控制時(shí)域參數(shù)。隨著優(yōu)化的滾動(dòng)進(jìn)行,預(yù)測(cè)電壓幅值逐漸接近其參考值,控制時(shí)域參數(shù)逐漸減小,可減少計(jì)算時(shí)間,加快故障后電壓恢復(fù)速度和優(yōu)化過(guò)程的收斂。 (4)針對(duì)長(zhǎng)期電壓穩(wěn)定問(wèn)題,提出了一種基于分段校正模型的在線電壓協(xié)調(diào)控制策略。通過(guò)廣域測(cè)量信息線性近似預(yù)測(cè)周期內(nèi)系統(tǒng)動(dòng)態(tài)狀態(tài)變量的軌跡,結(jié)合時(shí)標(biāo)分解方法避免優(yōu)化過(guò)程中使用連續(xù)動(dòng)態(tài)方程,并且討論了離散動(dòng)態(tài)的處理方式。預(yù)測(cè)模型在控制周期初始時(shí)刻根據(jù)廣域測(cè)量信息進(jìn)行校正,使其能夠跟蹤實(shí)際系統(tǒng)的運(yùn)行狀態(tài),確保預(yù)測(cè)結(jié)果的可信性。通過(guò)假設(shè)負(fù)荷自恢復(fù)動(dòng)態(tài),提出了一種針對(duì)分段校正模型節(jié)點(diǎn)電壓對(duì)于控制響應(yīng)的預(yù)測(cè)方法,根據(jù)線性系統(tǒng)的疊加性質(zhì)轉(zhuǎn)化最優(yōu)電壓協(xié)調(diào)控制模型。在確保控制效果的同時(shí)大幅降低了計(jì)算復(fù)雜度。
[Abstract]:With the expansion of grid scale and the strengthening of the structure , the grid has gradually entered the development saturation period . At present , the load center is continuously increasing , but due to the shortage of environmental resources it is difficult to build new station and line corridor , the situation of long - distance heavy load transmission will become more and more close to its stability limit .

In the above background , we study the dynamic characteristics of long - term voltage stability , quantify the response characteristics of the voltage traces to the control measures , and obtain the optimal voltage control sequences on - line based on the control method of the rolling time domain . The research and exploration of the series of problems , such as the prediction model , the optimization constraint and the control strategy , which are applicable to the online decision - making are studied . The main research and innovation results of the thesis are as follows :

( 1 ) The optimization decision - making set of voltage coordination control is determined by the number of optimization target nodes and controllers . In practical application , the number of target nodes and controllers is large , and the problem of decision - set explosion is faced . As a result of the characteristic of voltage control locality , the number of motion controllers in the optimization solution is always maintained at a smaller scale compared with the original decision variables of explosion growth .
The dynamic response characteristics of voltage are considered in clustering and screening methods . Compared with the traditional static index , the dynamic evolution trend of the system can be improved . The simulation results show that the proposed method can greatly reduce the scale of alternative decision set and avoid the decision - set explosion problem of voltage coordination control .

( 2 ) the voltage coordination control based on the static analysis method is unable to calculate the hybrid dynamic characteristic of the system and depends on the existence of the stable equilibrium point of the system ;
The voltage coordination control method based on dynamic analysis can avoid the above problems , but usually takes the system number as the optimization objective and constraint , can ensure the gradual stabilization of the system voltage track and keep the relative generation quantity within the constraint range , but can not ensure the stability margin of the system meets the requirement .
On the contrary , only the voltage amplitude is optimized . The optimization process takes the sampling period as the interval on - line rolling , not only can the voltage amplitude after the fault can be optimized , but also the stable margin of the system can be ensured .

( 3 ) There are many uncertainties in the operation of the electric power system , and it is difficult to accurately model the comprehensive load in the long - term voltage stability time scale . The prediction model used in the voltage coordination control study is almost impossible to match with the actual system operating state .
A voltage coordination control strategy based on adaptive control time domain parameters is proposed in this paper .

( 4 ) Aiming at the problem of long - term voltage stability , a line voltage coordination control strategy based on piecewise correction model is proposed . The continuous dynamic equation is avoided in the optimization process by combining the time - standard decomposition method with the time - standard decomposition method . The prediction model is used to correct the operation state of the actual system and to ensure the credibility of the prediction result .
【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM712

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