本文關(guān)鍵詞： 配電網(wǎng)重構(gòu) 分布式電源 多種負(fù)荷方式 蟻群算法 遺傳算法 潮流計(jì)算　出處：《南京理工大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：配電網(wǎng)重構(gòu)是提高電力系統(tǒng)運(yùn)行的安全性和穩(wěn)定性的有效方法。而分布式電源(Distributed Generation, DG)的接入,使得原有單電源的網(wǎng)絡(luò)變成了多電源的網(wǎng)絡(luò),同時DG的容量和安裝位置直接關(guān)系到配電網(wǎng)的電能質(zhì)量、電壓分布、短路電流大小以及線路的潮流分布等,帶來的后果就是原有網(wǎng)絡(luò)重構(gòu)的目標(biāo)函數(shù),約束條件不再適用于現(xiàn)有網(wǎng)絡(luò),因此研究含DG的配電網(wǎng)重構(gòu)具有十分重要的意義。 本文首先對DG做了一些等效和簡化處理,并以簡單配電網(wǎng)為例,嚴(yán)格論證和推導(dǎo)了不同容量的DG出力、DG在系統(tǒng)中接入位置對于系統(tǒng)網(wǎng)損的影響。在潮流計(jì)算中,依據(jù)PV節(jié)點(diǎn)、PI節(jié)點(diǎn)、PQ(V)節(jié)點(diǎn)所具有的不同特點(diǎn)分別建立了相應(yīng)的潮流計(jì)算模型,還提出了一種考慮最大負(fù)荷,一般負(fù)荷,最小負(fù)荷的3種負(fù)荷方式的重構(gòu)模型,在每一種負(fù)荷方式下,都進(jìn)行一次潮流計(jì)算,這樣使得重構(gòu)方案更加接近最優(yōu)解。 本文以基本環(huán)路中打開的開關(guān)為基因位構(gòu)成染色體,染色體數(shù)即為基本環(huán)路數(shù),這樣可以極大程度的縮小搜索空間,提高算法的搜索效率。通過對遺傳算法和蟻群算法優(yōu)缺點(diǎn)的比較,提出了遺傳算法與蟻群算法動態(tài)融合的新算法。主要原理是首先利用遺傳算法的快速全局搜索能力生成信息素的分布,然后利用蟻群算法的正反饋收斂機(jī)制尋找最短路徑,求精確解。遺傳算法中交叉率PC和變異率Pm的選擇和調(diào)節(jié)可以更快速的選擇最優(yōu)路徑,提高算法的收斂代數(shù),在配電網(wǎng)中表現(xiàn)為快速的逃離不可行區(qū)域,蟻群算法的正反饋機(jī)制快速的使得優(yōu)質(zhì)染色體的比例明鮮增加,解的質(zhì)量得到了極大的提高,而且蟻群算法的融入加快了收斂速度；同時螞蟻以微小的出錯概率從原有配電網(wǎng)中進(jìn)行選擇,從而保證了解的多樣性,有效的防止GA-ACO的早熟。通過對IEEE16、 IEEE33節(jié)點(diǎn)的仿真,驗(yàn)證了上述算法的可以性。
[Abstract]:Distribution network reconfiguration is an effective method to improve the security and stability of power system. At the same time, the capacity and installation position of DG are directly related to the power quality, voltage distribution, short circuit current and power flow distribution of the distribution network. The result is the objective function of the original network reconfiguration. The constraints are no longer applicable to existing networks, so it is very important to study the reconfiguration of distribution networks with DG. In this paper, we first do some equivalent and simplified treatment to DG, and take simple distribution network as an example, we strictly demonstrate and deduce the influence of DG's access position in the system with different capacity on the system's network loss. According to the different characteristics of PV / Pi node / PQ / V) node, the corresponding power flow calculation models are established, and a reconstruction model of three load modes considering maximum load, general load and minimum load is proposed. In each load mode, a power flow calculation is carried out, which makes the reconstruction scheme closer to the optimal solution. In this paper, the open switch in the basic loop is used as the gene site to construct the chromosome, and the number of chromosomes is the number of the basic loops, which can greatly reduce the search space. Improve the search efficiency of the algorithm. By comparing the advantages and disadvantages of genetic algorithm and ant colony algorithm, A new algorithm for dynamic fusion of genetic algorithm and ant colony algorithm is proposed. Firstly, the fast global search ability of genetic algorithm is used to generate the distribution of pheromone, and then the convergence mechanism of ant colony algorithm is used to find the shortest path. The selection and adjustment of crossover rate PC and mutation rate pm in genetic algorithm can select the optimal path more quickly, improve the convergence algebra of the algorithm, and quickly escape the infeasible region in the distribution network. The positive feedback mechanism of ant colony algorithm can increase the proportion of high quality chromosome and improve the quality of solution greatly, and the integration of ant colony algorithm accelerates the convergence speed. At the same time, ants select from the original distribution network with small error probability, so as to ensure the diversity of understanding, and effectively prevent the precocity of GA-ACO. The simulation of IEEE 16 and IEEE33 nodes verifies the feasibility of the above algorithm.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TM732

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