本文選題：配電網(wǎng)重構(gòu) + 風(fēng)電　； 參考：《東北電力大學(xué)》2017年碩士論文

【摘要】：配電網(wǎng)重構(gòu)是配電網(wǎng)優(yōu)化運行的一項重要措施,配電網(wǎng)中包含少量的聯(lián)絡(luò)開關(guān)和大量的分段開關(guān),配電網(wǎng)重構(gòu)就是重新組合配電網(wǎng)中這些開關(guān)的開合狀態(tài),從而使配電網(wǎng)運行于最佳狀態(tài)。近年來,風(fēng)電等分布式電源在電網(wǎng)中的滲透率逐年增加,配電網(wǎng)需要考慮隨之而來的不確定性。傳統(tǒng)的配電網(wǎng)重構(gòu)方案已不能適應(yīng)如今的配電網(wǎng)形勢,因此有必要研究計及分布式電源影響的配電網(wǎng)重構(gòu)。本文選取風(fēng)電這一典型的分布式電源作為研究對象,建立了基于網(wǎng)損和網(wǎng)損期望值的多場景配電網(wǎng)重構(gòu)數(shù)學(xué)模型,采用了基于“排同存異”的環(huán)路編碼策略,制定了基于場景分析法和二進制粒子群算法的最優(yōu)方案確定策略。基于風(fēng)速的Weibull分布模型,分別研究了不考慮負(fù)荷季節(jié)變化特性的配電網(wǎng)重構(gòu)和考慮負(fù)荷季節(jié)變化特性的配電網(wǎng)重構(gòu),研究中采用了基于wasserstein距離的場景劃分方法對風(fēng)電場景進行劃分,考慮負(fù)荷季節(jié)變化特性時,采用了基于K-means的聚類方法對各季節(jié)的典型日負(fù)荷曲線進行聚類,提取出各季節(jié)的典型負(fù)荷狀態(tài),并對負(fù)荷聚類的有效性進行了驗證。考慮到兩參數(shù)Weibull分布模型不包含時序信息,也無法體現(xiàn)出風(fēng)電的季節(jié)性變化特征,本文采用一種基于K-means聚類的風(fēng)速場景縱橫消減算法。該方法無需知道風(fēng)速的概率分布函數(shù),通過對各季節(jié)的歷史風(fēng)速數(shù)據(jù)縱向和橫向的消減,生成各季節(jié)的風(fēng)速場景集,據(jù)此研究了考慮風(fēng)電季節(jié)變化特性的配電網(wǎng)重構(gòu),并對風(fēng)電場景劃分的有效性進行了驗證。借助IEEE33節(jié)點配電網(wǎng)系統(tǒng)對不同情況下的配電網(wǎng)重構(gòu)進行仿真計算,得到了各個情況下的重構(gòu)方案,驗證了本文建立的多場景配電網(wǎng)重構(gòu)模型和求解方法的有效性。本文的數(shù)學(xué)模型、求解方法以及重構(gòu)結(jié)果能為運行人員提供參考。
[Abstract]:Distribution network reconfiguration is an important measure in the optimal operation of distribution network. The distribution network contains a small number of contact switches and a large number of piecewise switches. Distribution network reconfiguration is to recombine the switching state of these switches in the distribution network. Thus, the distribution network runs in the best condition. In recent years, the permeability of distributed generation, such as wind power, has been increasing year by year. The traditional reconfiguration scheme of distribution network can not adapt to the current situation of distribution network, so it is necessary to study the reconfiguration of distribution network considering the influence of distributed generation. This paper selects wind power as a typical distributed power source as the research object, establishes the mathematical model of multi-scene distribution network reconfiguration based on network loss and network loss expectation value, and adopts the loop coding strategy based on "same arrangement, same storage and difference". An optimal scheme determination strategy based on scenario analysis and binary particle swarm optimization (BPSO) is proposed. Based on the Weibull distribution model of wind speed, the reconfiguration of distribution network without considering the seasonal variation of load and the reconfiguration of distribution network with consideration of seasonal variation of load are studied respectively. In the research, the scene partition method based on wasserstein distance is used to divide the wind power scene. When considering the seasonal variation of load, K-means clustering method is used to cluster the typical daily load curve of each season. The typical load states of each season were extracted and the validity of load clustering was verified. Considering that the two-parameter Weibull distribution model does not contain time series information and can not reflect the seasonal variation of wind power, this paper uses a K-means clustering algorithm to reduce wind speed scene. This method does not need to know the probability distribution function of wind speed. By reducing the historical wind speed data of each season vertically and horizontally, the scene set of wind speed in each season is generated. Based on this, the distribution network reconstruction considering the seasonal variation characteristics of wind power is studied. The validity of wind power scene partition is verified. With the help of IEEE33 node distribution network system, the reconfiguration of distribution network under different conditions is simulated and calculated, and the reconfiguration scheme in each case is obtained, which verifies the validity of the multi-scene distribution network reconfiguration model and the solution method established in this paper. The mathematical model, solution method and reconstruction result can provide reference for operators.
【學(xué)位授予單位】：東北電力大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM711

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本文編號：2061041