本文關鍵詞：計及風電出力優(yōu)化或電動汽車充電站規(guī)劃的配電網(wǎng)重構　出處：《華北電力大學》2015年碩士論文　論文類型：學位論文

  更多相關文章： 配電網(wǎng)重構 遺傳算法 雙饋風機 電動汽車充電站 拓撲分析

【摘要】：配電網(wǎng)重構作為提高電力系統(tǒng)靈活性、經(jīng)濟性與可靠性的重要內容,受到越來越的重視。配電網(wǎng)重構的目的是是尋求滿足供電可靠性和網(wǎng)絡運行約束的一組最優(yōu)的決策變量,實現(xiàn)經(jīng)濟性、可靠性和停電范圍最小。以配電網(wǎng)是否動態(tài)重構分類,主要分為靜態(tài)和動態(tài)重構。常見重構優(yōu)化方法有：改進窮舉法、人工智能算法(粒子群算法、禁忌搜索法、遺傳算法和免疫算法等)和混合算法等。遺傳算法作為智能尋優(yōu)方法,將自然選擇與遺傳機制引入到數(shù)學原理中,在配電網(wǎng)重構中應用最為廣泛,但仍存在易局部收斂、存在不可行解或網(wǎng)架變化后不再適用等問題。本文提出的改進遺傳算法基于拓撲分析,能很好地避免不可行解并彌補適應性差的不足。該算法的關鍵是動態(tài)拓撲分析程序的設置和遺傳算子的改進。通過拓撲分析,簡化網(wǎng)絡并尋找所有可行樹基,提高重構速度；拓撲分析方法只需提供連接鏈表,可以適用于任意開環(huán)配電網(wǎng)及故障后網(wǎng)絡,具有一般適用性和動態(tài)性；引入校驗遺傳算子,將子代種群中的不可行個體轉變?yōu)榭尚袀�體,使得求解過程只在可行解空間進行,避免環(huán)網(wǎng)和“孤島”的出現(xiàn)。為了進一步驗證本文所提算法的適用性,本文在配電網(wǎng)供電側加入雙饋風力發(fā)電機,在分析其工作機理、數(shù)學模型和交替迭代法計算潮流的基礎上,研究計及雙饋風電機出力優(yōu)化的配電網(wǎng)重構模型；在用電用戶側加入電動汽車充電站(Electric Vehicle Charging Station, EVCS),建立EVCS規(guī)劃和配電網(wǎng)重構的協(xié)同優(yōu)化模型并給出算例分析。本文選取IEEE33節(jié)點配電網(wǎng)系統(tǒng),并基于Matlab軟件進行仿真,實驗結果證明：這種方法建立在動態(tài)拓撲分析的基礎上,符合配電網(wǎng)運行特點,有效避免不可行解的出現(xiàn)；與同類方法相比,在減小搜索空間、加快計算速度、提高適用性和保證可行性與動態(tài)性方面具備優(yōu)越性。該算法不僅適用于正常運行時的靜態(tài)重構,也適用于網(wǎng)架結構改變后的動態(tài)重構；能很好的適用于包含雙饋風機的配電網(wǎng)重構；也能有效解決EVCS規(guī)劃和配電網(wǎng)重構的整體優(yōu)化問題。
[Abstract]:Distribution network reconfiguration is an important content to improve the flexibility, economy and reliability of power system. The purpose of distribution network reconfiguration is to find a set of optimal decision variables to meet the power supply reliability and network operation constraints to achieve economic efficiency. The reliability and blackout range are the minimum. The distribution network is divided into static and dynamic reconfiguration. The common reconfiguration optimization methods are: improved exhaustive method, artificial intelligence algorithm (particle swarm optimization). Tabu search method, genetic algorithm and immune algorithm) and hybrid algorithm. As intelligent optimization method, genetic algorithm introduces natural selection and genetic mechanism into mathematical principles, and is most widely used in distribution network reconfiguration. However, there are still some problems such as easy local convergence, infeasible solution or no longer applicable after the change of grid. The improved genetic algorithm proposed in this paper is based on topological analysis. The key of this algorithm is the setting of dynamic topological analysis program and the improvement of genetic operator. Through topology analysis, the network can be simplified and all feasible tree bases can be found. Improving the speed of reconstruction; The topology analysis method only needs to provide the linked list, and it can be applied to any open-loop distribution network and the network after failure, which is of general applicability and dynamic. By introducing the check genetic operator, the infeasible individual in the offspring population is transformed into the feasible individual, so that the solution process is only carried out in the feasible solution space. In order to further verify the applicability of the proposed algorithm, a doubly-fed wind turbine is added to the power supply side of the distribution network, and its working mechanism is analyzed. On the basis of mathematical model and alternating iteration method to calculate power flow, the reconfiguration model of distribution network considering the optimization of output force of doubly-fed air motor is studied. Electric Vehicle Charging Station (EVCSs) is added to the electric vehicle charging station on the power user side. The cooperative optimization model of EVCS planning and distribution network reconfiguration is established and an example is given. In this paper, IEEE33 node distribution network system is selected and simulated based on Matlab software. The experimental results show that this method is based on dynamic topology analysis, accords with the characteristics of distribution network operation, and effectively avoids the emergence of infeasible solutions. Compared with the similar methods, this algorithm has advantages in reducing the search space, speeding up the calculation speed, improving the applicability and ensuring the feasibility and dynamics. This algorithm is not only suitable for static reconstruction in normal operation. It is also suitable for the dynamic reconstruction after the change of the grid structure. It can be applied to the reconfiguration of distribution network including doubly-fed fan. It can also effectively solve the overall optimization problem of EVCS planning and distribution network reconfiguration.
【學位授予單位】：華北電力大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：U491.8;TM727;TM614

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