本文選題：分布式電源　切入點(diǎn)：地區(qū)電網(wǎng)　出處：《廣東工業(yè)大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：近年來,隨著能源問題和環(huán)境問題日益突出,新能源的開發(fā)利用逐漸得到人們的重視,風(fēng)機(jī)和小水電等分布式電源由于其自身的清潔性及可再生性等優(yōu)點(diǎn),使得其越來越多的被引入到電力系統(tǒng)當(dāng)中。而電力系統(tǒng)的無功優(yōu)化是保證電網(wǎng)安全、經(jīng)濟(jì)運(yùn)行的有效手段,也是降低網(wǎng)絡(luò)損耗、提高電壓質(zhì)量的重要措施。因此,含分布式電源的電網(wǎng)無功優(yōu)化研究有著重要意義。 由于分布式電源的環(huán)保無污染等優(yōu)點(diǎn),近年來分布式發(fā)電技術(shù)越來越普及,本文詳細(xì)分析了分布式發(fā)電技術(shù)的特點(diǎn)以及在并入電網(wǎng)之后對(duì)電網(wǎng)電壓,網(wǎng)損和電能質(zhì)量的影響。選取了風(fēng)機(jī)、小水電和光伏這三種比較有代表性的分布式電源,介紹了他們的發(fā)電原理以及目前的研究現(xiàn)狀。根據(jù)地區(qū)電網(wǎng)的實(shí)際特點(diǎn),將小水電和風(fēng)機(jī)并入到了電網(wǎng)中。通過分析小水電和風(fēng)機(jī)的數(shù)學(xué)模型,將小水電作為PQ節(jié)點(diǎn),風(fēng)機(jī)作為PV節(jié)點(diǎn),接入到一個(gè)實(shí)際的地區(qū)電網(wǎng)中,采用牛頓拉夫遜法,進(jìn)行潮流的仿真計(jì)算。并且根據(jù)潮流計(jì)算的結(jié)果分析了分布式電源對(duì)地區(qū)電網(wǎng)電壓,網(wǎng)損和電能質(zhì)量的影響。 量子進(jìn)化算法作為一種常見的人工智能算法,在進(jìn)化過程中隨著變量的增多會(huì)出現(xiàn)早熟現(xiàn)象和陷入局部最優(yōu)等缺點(diǎn)。因此,本文提出了NW-QEA算法,在量子進(jìn)化算法的迭代過程中加入了NW小世界的網(wǎng)絡(luò)模型,采用隨機(jī)化加邊的方法動(dòng)態(tài)地改變種群個(gè)體的鄰域拓?fù)浣Y(jié)構(gòu),從而增加了種群個(gè)體的多樣性,大大提高了算法的全局探索能力。并且利用NW-QEA算法對(duì)IEEE-14節(jié)點(diǎn)和IEEE-57進(jìn)行了無功優(yōu)化的仿真,通過和其它算法的對(duì)比,證明了NW-QEA算法的可行性與有效性。 最后,對(duì)某地區(qū)實(shí)際電網(wǎng)的算例進(jìn)行了仿真,此電網(wǎng)加入了風(fēng)機(jī)和小水電這兩種分布式電源,本文在此基礎(chǔ)上,建立了含分布式電源的無功優(yōu)化模型,利用NW-QEA算法對(duì)其進(jìn)行了無功優(yōu)化的仿真計(jì)算,并且與QEA算法進(jìn)行對(duì)比,結(jié)果表明,NW-QEA算法在電力系統(tǒng)無功優(yōu)化中具有很強(qiáng)的優(yōu)越性,分布式電源能夠?qū)Φ貐^(qū)電網(wǎng)的無功優(yōu)化產(chǎn)生很大的影響,從而保證了電網(wǎng)的安全經(jīng)濟(jì)運(yùn)行。
[Abstract]:In recent years, with the increasingly prominent energy and environmental problems, the development and utilization of new energy has been gradually attached importance to, fan and small hydropower and other distributed power generation due to its own clean and renewable advantages. The reactive power optimization of the power system is an effective means to ensure the security and economic operation of the power network, and it is also an important measure to reduce network losses and improve the voltage quality. The research of reactive power optimization with distributed generation is of great significance. In recent years, the distributed generation technology has become more and more popular because of its advantages of environmental protection and no pollution. This paper analyzes the characteristics of the distributed generation technology and the voltage of the grid after being merged into the grid. The influence of network loss and power quality. Three representative distributed power sources, namely fan, small hydropower and photovoltaic, are selected, and their generation principle and current research status are introduced. According to the actual characteristics of regional power grid, By analyzing the mathematical model of small hydropower and fan, small hydropower is used as PQ node and fan as PV node, which is connected to a practical regional power network, and Newton Raphson method is used. According to the results of power flow calculation, the influence of distributed power generation on the voltage, network loss and power quality of regional power network is analyzed. As a common artificial intelligence algorithm, quantum evolutionary algorithm (QEA) has the disadvantages of precocity and local optimization with the increase of variables. Therefore, NW-QEA algorithm is proposed in this paper. In the iterative process of quantum evolutionary algorithm, the network model of NW small world is added, and the neighborhood topological structure of the population is dynamically changed by the method of randomization and edge addition, thus increasing the diversity of the population individual. The NW-QEA algorithm is used to simulate the reactive power optimization of IEEE-14 node and IEEE-57. The feasibility and effectiveness of NW-QEA algorithm are proved by comparing with other algorithms. Finally, the simulation of the actual power grid in a certain area is carried out, in which two kinds of distributed generation, fan and small hydropower, are added. Based on this, a reactive power optimization model with distributed generation is established in this paper. The NW-QEA algorithm is used to simulate the reactive power optimization and compared with the QEA algorithm. The results show that the NW-QEA algorithm has a strong superiority in the reactive power optimization of power system. Distributed generation can greatly affect the reactive power optimization of regional power network, thus ensuring the safe and economical operation of the power grid.
【學(xué)位授予單位】：廣東工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM714.3

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