本文關鍵詞： 配電網(wǎng)絡重構 潮流計算 量子粒子群算法 仿射傳播聚類算法　出處：《山東大學》2017年碩士論文　論文類型：學位論文

【摘要】：在不斷推進智能電網(wǎng)發(fā)展的大背景下,建設安全、可靠、經(jīng)濟運行的配電網(wǎng)絡逐漸成為人們所關注的焦點。由于配電網(wǎng)絡中各節(jié)點的電壓等級比較低,導致它的網(wǎng)損成為電力系統(tǒng)網(wǎng)損中不可忽視的一部分。配電網(wǎng)絡重構作為一項重要的配電網(wǎng)自動化技術,可以在不投入更多額外設備的情況下,僅對線路上開關的狀態(tài)進行調整,就可以實現(xiàn)降低網(wǎng)絡損耗,改善電壓質量的目的。在實際配電網(wǎng)絡運行過程中,負荷狀態(tài)是實時變化的,這是配電網(wǎng)絡重構中一個不易處理的問題。本文先從單個時間斷面的角度,利用隨機類算法對配電網(wǎng)絡中負荷狀態(tài)保持不變的情況進行分析。然后再從整個時間區(qū)間的角度,根據(jù)負荷狀態(tài)實時變化的情況,提出一種配電網(wǎng)絡動態(tài)重構方法。首先,本文對配電網(wǎng)絡重構問題中的基本理論作了詳細介紹,并給出了相應的潮流計算方法和數(shù)學模型。通過引入節(jié)點分層矩陣Layer M以及相應的父節(jié)點矩陣NU來描述網(wǎng)絡層次關系,結合前推回代法,實現(xiàn)同一層中數(shù)值的并行計算,從而提高了計算效率。然后把降低網(wǎng)損作為配電網(wǎng)絡重構的最終優(yōu)化目標,并給出了相應的目標函數(shù)和約束條件。其次,本文提出了一種基于IQPSO算法的配電網(wǎng)絡靜態(tài)重構方法。該方法 二考慮到QPSO算法的收斂性會受到初始種群分布情況的影響,所以引入了Logistic混沌模型來提高初始種群的遍歷能力;另外,通過對收縮—展系數(shù)α進行改進,提高了 QPSO算法的動態(tài)自適應性。在配電網(wǎng)絡靜態(tài)重構的過程中,根據(jù)網(wǎng)絡中的回路情況,采用十進制的編碼策略對粒子向量進行編碼,降低了重構過程中不可行解產(chǎn)生的比例;通過對網(wǎng)絡中節(jié)點的層次關系進行分析,給出了重構解可行性的判斷方法以及相應的處理方式;最后,介紹了該靜態(tài)重構方法的具體步驟。通過仿真計算,證明了該靜態(tài)重構方法具有正確性和快速性。最后,本文提出了基于仿射傳播聚類算法的配電網(wǎng)絡動態(tài)重構方法。該方法考慮到配電網(wǎng)絡節(jié)點負荷變化的特點,先將所研究的時間區(qū)間等間隔地劃分為若干個子區(qū)間,并認為各子區(qū)間中的負荷情況保持恒定不變,然后利用仿射傳播聚類算法對整個時間區(qū)間內的負荷狀態(tài)進行聚類,得到聚類代表點以及相應的聚類情況,并根據(jù)聚類代表點的負荷狀態(tài)進行若干次靜態(tài)重構。同時,對聚類結果中那些孤立的時間斷面作修正處理,以實現(xiàn)減少開關操作次數(shù)的目的。該方法通過節(jié)點負荷狀態(tài)的內在特征對整個時間區(qū)間進行劃分,可以有效避免主觀因素對劃分結果造成影響。通過仿真計算以及對計算結果進行分析,驗證了該動態(tài)重構方法的正確性和合理性。
[Abstract]:Under the background of continuously advancing the development of smart grid, the construction of safe, reliable and economical distribution network has gradually become the focus of attention, because of the low voltage level of each node in the distribution network. Distribution network reconfiguration, as an important distribution automation technology, can not be ignored without additional equipment. The purpose of reducing network loss and improving voltage quality can be achieved by only adjusting the state of switch on the line. During the operation of actual distribution network, the load state changes in real time. This is a difficult problem to deal with in distribution network reconfiguration. The random class algorithm is used to analyze the condition that the load state in the distribution network remains invariant, and then from the angle of the whole time interval, according to the condition of the real-time change of the load state. A dynamic reconfiguration method for distribution network is proposed. Firstly, the basic theory of distribution network reconfiguration is introduced in detail. The corresponding power flow calculation method and mathematical model are given. By introducing the node hierarchical matrix Layer M and the corresponding parent node matrix NU to describe the hierarchical relationship of the network, combined with the forward pushback method. The parallel computation of numerical value in the same layer is realized, and the efficiency of calculation is improved. Then, reducing network loss is regarded as the final optimization goal of distribution network reconfiguration, and the corresponding objective function and constraint conditions are given. Secondly. This paper presents a static reconfiguration method for distribution network based on IQPSO algorithm. The second method considers that the convergence of QPSO algorithm will be affected by the initial population distribution. So the Logistic chaotic model is introduced to improve the traversal ability of the initial population. In addition, the dynamic self-adaptability of QPSO algorithm is improved by improving the contraction-expansion coefficient 偽. In the process of static reconfiguration of distribution network, according to the loop situation in the network. The decimal coding strategy is used to encode the particle vector, which reduces the proportion of the infeasible solution in the reconstruction process. Through the analysis of the hierarchical relationship of nodes in the network, the method of judging the feasibility of the reconstruction solution and the corresponding processing methods are given. Finally, the concrete steps of the static reconstruction method are introduced. The simulation results show that the static reconstruction method is correct and fast. Finally. This paper presents a dynamic reconfiguration method for distribution network based on affine propagation clustering algorithm, which takes into account the characteristics of load variation of distribution network nodes. First, the time interval is divided into several sub-intervals at equal intervals, and it is considered that the load in each sub-interval remains constant. Then, the load state in the whole time interval is clustered by affine propagation clustering algorithm, and the representative points of clustering and the corresponding clustering situation are obtained. According to the load state of the cluster representative points, the static reconstruction is carried out several times. At the same time, the isolated time sections in the clustering results are corrected. In order to reduce the number of switching operations, the method divides the whole time interval by the inherent characteristics of the node load state. It can effectively avoid the influence of subjective factors on the partition results. The correctness and rationality of the dynamic reconstruction method are verified by simulation and analysis of the calculated results.
【學位授予單位】：山東大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TM76;TP311.13

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