本文選題：電力系統(tǒng)恢復 + 網(wǎng)絡重構(gòu)��； 參考：《浙江大學》2017年碩士論文

【摘要】：近幾年國內(nèi)外發(fā)生了多起大面積停電事故,如2003年8·14美加大停電、2012年印度大停電、2015年廣東湛江電網(wǎng)受臺風影響引起的大面積停電事故、2015年土耳其"3.31"大停電事故等為電力系統(tǒng)的安全穩(wěn)定運行敲響了警鐘。一旦發(fā)生大面積停電,如果沒有事先制定的恢復預案,就會造成重大的經(jīng)濟損失。因此,有必要深入而系統(tǒng)地研究電力系統(tǒng)的事故處理及完全或部分停電后的恢復問題,這對減少故障影響和停電損失,確保事故發(fā)生后能安全、快速、智能地恢復供電,具有十分重要的理論和實際意義。大停電后的電力系統(tǒng)恢復可分為黑啟動、網(wǎng)絡重構(gòu)和負荷恢復三個階段。網(wǎng)絡重構(gòu)階段的主要任務是盡快為失電機組送電并逐步建立起一個穩(wěn)定的網(wǎng)架結(jié)構(gòu),為下一階段全面恢復負荷打下堅實的基礎(chǔ)。網(wǎng)絡重構(gòu)階段的系統(tǒng)恢復策略總體上可分為兩類:串行恢復和并行恢復。串行恢復策略在大多數(shù)發(fā)電機并網(wǎng)前接力恢復各廠站;并行恢復策略將系統(tǒng)分成幾個子系統(tǒng)先各自獨立恢復,待各子系統(tǒng)恢復完成后再通過并網(wǎng)來實現(xiàn)整個系統(tǒng)的恢復。在此背景下,本文對基于加權(quán)網(wǎng)絡節(jié)點重要度的網(wǎng)絡重構(gòu)策略以及電力系統(tǒng)分區(qū)恢復問題展開研究,并取得了一定的研究成果:1、首先針對介數(shù)法、節(jié)點刪除法、節(jié)點收縮法等傳統(tǒng)方法在評價加權(quán)網(wǎng)絡節(jié)點重要度時存在的不足,提出了節(jié)點重要度評價矩陣方法,綜合考慮了節(jié)點位置和鄰接點貢獻信息。在此基礎(chǔ)上,發(fā)展了一種改進的網(wǎng)絡重構(gòu)雙層優(yōu)化模型。上層模型以最大化系統(tǒng)可用發(fā)電容量為目標,以非黑啟動機組獲得啟動功率的時間為優(yōu)化變量;下層模型以恢復路徑平均節(jié)點重要度最大為目標來確定發(fā)電機節(jié)點的恢復路徑。在下層模型中,通過調(diào)節(jié)系數(shù)改變線路權(quán)重中線路電容與操作時間的比重,以避免恢復路徑所需時間過長而導致待恢復機組無法盡快恢復的問題。2、提出了基于半監(jiān)督譜聚類的黑啟動分區(qū)策略。首先,采用節(jié)點間的電氣距離這個因素為線路權(quán)重賦值,在此基礎(chǔ)上建立電力系統(tǒng)無向加權(quán)圖,進而依據(jù)比例割集準則建立黑啟動分區(qū)策略。該策略由兩步構(gòu)成:第一步建立待恢復機組的分組模型,其以最大化系統(tǒng)發(fā)電量和最小化恢復線路總電容為目標,從而保證機組的安全快速啟動;第二步以得到的機組分組信息為基礎(chǔ),利用半監(jiān)督譜聚類算法求解黑啟動分區(qū)模型。為了克服傳統(tǒng)k-means算法對初始聚類中心敏感的缺點,在利用半監(jiān)督譜聚類算法對特征向量進行聚類的最后一步采用了k-means++算法對特征向量進行聚類。3、提出了黑啟動分區(qū)中用于網(wǎng)絡簡化的電流追蹤法。首先,針對黑啟動分區(qū)問題的特點構(gòu)建電力系統(tǒng)無向加權(quán)圖,線路權(quán)值定義為線路的有功潮流;然后依據(jù)多路規(guī)范割集準則建立黑啟動分區(qū)問題的數(shù)學模型。之后采用三步方法求解得到黑啟動分區(qū)結(jié)果:1)以最大化系統(tǒng)發(fā)電量為目標建立待恢復機組的分組模型,并采用遺傳算法求解該模型得到機組分組信息;2)以得到的機組分組信息為基礎(chǔ),采用電流追蹤法計算得到支路電流中各電源分量,并以此為基礎(chǔ)對電力網(wǎng)絡圖進行簡化;3)利用譜聚類算法求解針對簡化后的電力網(wǎng)絡圖的黑啟動分區(qū)模型,最后把在簡化過程中被合并的節(jié)點還原即得到最終的黑啟動分區(qū)結(jié)果。最后對本文研究工作進行了總結(jié),并指出了接下去可以繼續(xù)研究改進的方面。
[Abstract]:In recent years, there have been a number of large area blackouts at home and abroad, such as the 8. 14 American blackout in 2003, the large blackout in India in 2012, the large area blackout caused by the impact of typhoon in Zhanjiang power grid in Guangdong in 2015, and the "3.31" blackout in Turkey in 2015. If there is no pre planned recovery plan, it will cause significant economic losses. Therefore, it is necessary to systematically study the accident treatment of the power system and the recovery after a complete or partial power outage, which will reduce the impact of the fault and the loss of power outage, and ensure that the power supply can be safely, quickly and intelligently after the accident. The restoration of power system after blackout can be divided into three stages: black start, network reconfiguration and load recovery. The main task of the network reconfiguration stage is to send electricity to the power loss unit as soon as possible and gradually establish a stable network frame structure to lay a solid foundation for the next stage full recovery load. The system recovery strategy in the stage can be divided into two categories: serial recovery and parallel recovery. The serial recovery strategy restores the stations before most generators are connected to the grid. The parallel recovery strategy divides the system into several subsystems, and the recovery of the whole system is realized after the subsystems are restored. In this context, this paper studies the network reconstruction strategy based on the weight of weighted network nodes and the problem of partition restoration in power system, and obtains some research results. 1. Firstly, the shortcomings of the traditional methods, such as the mediate method, the node deletion method, the node contraction method, and so on, are proposed to evaluate the importance of the weighted network nodes. On the basis of this, an improved two-layer optimization model for network reconfiguration is developed. On the basis of this, the upper model aims at maximizing the power generation capacity of the system, and the time of obtaining the starting power from the non black startup unit is the optimization variable; the lower layer model is used to restore the path. In the lower layer model, the proportion of the line capacitance and operation time in the weight of the line is changed in the lower layer model in order to avoid the problem that the recovery path is too long and the recovery unit can not recover as soon as possible, which is based on the semi supervised spectral aggregation. The black start partition strategy of class. First, using the electrical distance among nodes to assign the weight of the line to the weight of the line, the undirected weighted graph of the power system is set up on this basis, and then the black start partition strategy is set up according to the proportional cut set criterion. The strategy is composed of two steps: the first step is to establish the group model of the unit to be restored, which is to maximize the system. In order to overcome the disadvantages of the traditional K-means algorithm for the initial clustering, the semi supervised spectrum clustering algorithm is used to overcome the shortcomings of the traditional K-means algorithm for the initial clustering. In the last step of clustering the eigenvectors, the k-means++ algorithm is used to cluster the feature vectors.3, and the current tracing method for network simplification in the black start partition is proposed. First, the undirected weighted graph of the power system is constructed for the characteristics of the black start partition problem. The mathematical model of the black start partition problem is established by the standard cut set criterion. After that, the results of the black start partition are solved by the three step method: 1) the group model of the unit to be restored is set up to maximize the system power generation, and the genetic algorithm is used to get the information of the unit group, and 2) based on the information of the unit grouping obtained. The current tracking method is used to calculate all the power components in the branch current, and the power network graph is simplified on this basis. 3) the black start partition model for the simplified electric network graph is solved by spectral clustering algorithm. Finally, the final black start partition result is obtained by reducing the joint node in the simplified process. Finally, the result of the black start partition is obtained. This paper summarizes the research work in this paper, and points out the following aspects that can be further studied and improved.

【學位授予單位】：浙江大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TM73;TM711

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本文編號：1875000