基于IGSO-PSO的含分布式電源的配電網(wǎng)重構研究
發(fā)布時間:2018-10-20 07:41
【摘要】:隨著現(xiàn)代電網(wǎng)的發(fā)展,對配電網(wǎng)自動化系統(tǒng)的建設與應用提出了更高的要求。配電網(wǎng)重構是配電自動化的重要功能之一,配電網(wǎng)重構作為一種不需要大量投資就可以實現(xiàn)對配電網(wǎng)優(yōu)化的手段,可以提升配電網(wǎng)電能質(zhì)量以及經(jīng)濟性,同時確保電力系統(tǒng)的安全穩(wěn)定,具有一定的研究價值。DG(Distribution Generation,分布式電源)作為一種小型的獨立電源與傳統(tǒng)電源相結合,節(jié)省偏遠地區(qū)供電投資并提高供電可靠性。分布式電源改變了配電網(wǎng)“開環(huán)設計,閉環(huán)運行”的拓撲結構,因此分布式電源的并入使得傳統(tǒng)的配電網(wǎng)重構方法不能有效的應用于實際系統(tǒng),本文對含分布式電源的配電網(wǎng)靜態(tài)重構和動態(tài)重構進行研究,主要工作內(nèi)容如下:(1)介紹幾種典型的分布式電源,從工作原理以及對配電網(wǎng)潮流計算、電能質(zhì)量等方面的影響分析,將其按照接口類型的不同劃分為PQ、PI、PV、PQ(V)四種類型,分別建立數(shù)學計算模型,為配電網(wǎng)重構做出良好的基礎。(2)在配電網(wǎng)靜態(tài)重構方面,通過分析粒子群算法和螢火蟲算法各自的優(yōu)缺點,將最小生成樹算法和改進的螢火蟲與粒子群算法結合,建立以有功損耗和負荷均衡指數(shù)最小為目標的配電網(wǎng)重構模型。以含DG的IEEE33節(jié)點配電網(wǎng)絡為算例,驗證了算法可行性與優(yōu)越性。(3)在配電網(wǎng)動態(tài)重構方面,考慮到實際配電網(wǎng)中負荷變化,將一種基于特性指標降維的聚類算法應用到負荷聚類中,將配電網(wǎng)動態(tài)重構轉(zhuǎn)化成以負荷聚類中心為負荷狀態(tài)的配電網(wǎng)靜態(tài)重構問題。
[Abstract]:With the development of modern power grid, higher requirements are put forward for the construction and application of distribution network automation system. Distribution network reconfiguration is one of the important functions of distribution automation. Distribution network reconfiguration, as a means to optimize distribution network without a lot of investment, can improve the power quality and economy of distribution network. At the same time, it ensures the safety and stability of power system, and has certain research value. DG (Distribution Generation, distributed power) as a small independent power supply combined with traditional power supply, it can save the investment of power supply in remote areas and improve the reliability of power supply. Distributed generation has changed the topology of "open-loop design and closed-loop operation" of distribution network, so the traditional reconfiguration method of distribution network can not be applied to practical system effectively. In this paper, the static reconfiguration and dynamic reconfiguration of distribution network with distributed generation are studied. The main contents are as follows: (1) introduce several typical distributed generation, from the working principle and power flow calculation of distribution network, Based on the analysis of the influence of power quality and other aspects, it is divided into four types of PQ,PI,PV,PQ (V) according to the different interface types, and the mathematical calculation models are established respectively to make a good foundation for the reconfiguration of distribution network. (2) in the aspect of static reconfiguration of distribution network, By analyzing the merits and demerits of particle swarm optimization (PSO) and firefly (Firefly) algorithm, a distribution network reconfiguration model aiming at the minimum active power loss and load balancing index is established by combining the minimum spanning tree algorithm with the improved Particle Swarm Optimization algorithm. Taking the IEEE33 node distribution network with DG as an example, the feasibility and superiority of the algorithm are verified. (3) in the aspect of dynamic reconfiguration of distribution network, the load variation in the actual distribution network is considered. A clustering algorithm based on characteristic index reduction is applied to load clustering. The dynamic reconfiguration of distribution network is transformed into a static reconfiguration problem in which the load clustering center is the load state.
【學位授予單位】:蘭州交通大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:TM711
[Abstract]:With the development of modern power grid, higher requirements are put forward for the construction and application of distribution network automation system. Distribution network reconfiguration is one of the important functions of distribution automation. Distribution network reconfiguration, as a means to optimize distribution network without a lot of investment, can improve the power quality and economy of distribution network. At the same time, it ensures the safety and stability of power system, and has certain research value. DG (Distribution Generation, distributed power) as a small independent power supply combined with traditional power supply, it can save the investment of power supply in remote areas and improve the reliability of power supply. Distributed generation has changed the topology of "open-loop design and closed-loop operation" of distribution network, so the traditional reconfiguration method of distribution network can not be applied to practical system effectively. In this paper, the static reconfiguration and dynamic reconfiguration of distribution network with distributed generation are studied. The main contents are as follows: (1) introduce several typical distributed generation, from the working principle and power flow calculation of distribution network, Based on the analysis of the influence of power quality and other aspects, it is divided into four types of PQ,PI,PV,PQ (V) according to the different interface types, and the mathematical calculation models are established respectively to make a good foundation for the reconfiguration of distribution network. (2) in the aspect of static reconfiguration of distribution network, By analyzing the merits and demerits of particle swarm optimization (PSO) and firefly (Firefly) algorithm, a distribution network reconfiguration model aiming at the minimum active power loss and load balancing index is established by combining the minimum spanning tree algorithm with the improved Particle Swarm Optimization algorithm. Taking the IEEE33 node distribution network with DG as an example, the feasibility and superiority of the algorithm are verified. (3) in the aspect of dynamic reconfiguration of distribution network, the load variation in the actual distribution network is considered. A clustering algorithm based on characteristic index reduction is applied to load clustering. The dynamic reconfiguration of distribution network is transformed into a static reconfiguration problem in which the load clustering center is the load state.
【學位授予單位】:蘭州交通大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:TM711
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相關期刊論文 前10條
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