基于移動多代理的配電網(wǎng)故障恢復研究
發(fā)布時間：2018-08-30 10:42
【摘要】：隨著智能電網(wǎng)的推廣和發(fā)展，越來越多的分布式電源和微網(wǎng)接入配電網(wǎng)，使得配電網(wǎng)的結構愈漸復雜。傳統(tǒng)的優(yōu)化算法已經(jīng)不能完全滿足配電網(wǎng)故障恢復重構的需要，尋找一種新的方法策略去適應配電網(wǎng)的復雜多變顯得尤為重要。本文基于配電網(wǎng)故障恢復的研究背景，綜合了當前的研究現(xiàn)狀，就目前配電網(wǎng)故障恢復中可能存在的問題，進行了如下研究： 首先，介紹了配電網(wǎng)故障恢復過程中需要反復進行計算的兩部分：拓撲分析和潮流計算。對比了深度優(yōu)先搜索算法和廣度優(yōu)先搜索算法的優(yōu)劣，根據(jù)配電網(wǎng)的輻射狀運行結構，采用基于廣度優(yōu)先搜索的拓撲分析算法。并在對比了幾種不同的潮流計算方法的基礎上，選擇前推回代法作為本文的潮流計算方法。 其次，將移動多代理技術應用于含分布式電源的配電網(wǎng)故障恢復研究中。建立了故障恢復的數(shù)學模型，并通過構建控制中心代理和子任務代理來實現(xiàn)配電網(wǎng)的故障恢復任務，其中，子任務代理中嵌入蟻群算法進行配電網(wǎng)故障恢復的優(yōu)化。通過子任務代理的動態(tài)聯(lián)盟，減小蟻群算法的尋優(yōu)范圍，提高了搜索效率。算例仿真表明了該策略的有效性。 最后，本文考慮了多類型分布式電源以微網(wǎng)形式接入智能配電網(wǎng)的情況。首先對微網(wǎng)中的多類型分布式電源進行分析，將其隨機功率模型轉(zhuǎn)化為分時段或分場景的恒定功率模型。考慮到故障發(fā)生背景的不同，分別從連續(xù)故障和非連續(xù)故障兩方面進行故障設置，，并采用基于移動多代理的演化算法對配電網(wǎng)的多目標進行優(yōu)化，最后結合含微網(wǎng)的算例驗證了該算法的有效性。
[Abstract]:With the promotion and development of smart grid, more and more distributed generation and microgrid are connected to distribution network, which makes the structure of distribution network more and more complex. The traditional optimization algorithm can not fully meet the needs of distribution network fault recovery and reconfiguration. It is particularly important to find a new method strategy to adapt to the complex and changeable distribution network. Based on the research background of distribution network fault recovery, this paper synthesizes the current research status, and carries out the following research on the possible problems in distribution network fault recovery: first, This paper introduces two parts, topology analysis and power flow calculation, which need to be calculated repeatedly in the process of distribution network fault recovery. The advantages and disadvantages of depth-first search algorithm and breadth-first search algorithm are compared. According to the radial operation structure of distribution network, the topological analysis algorithm based on breadth-first search is adopted. On the basis of comparing several different power flow calculation methods, the forward pushback method is chosen as the power flow calculation method in this paper. Secondly, the mobile multi-agent technology is applied to the research of distribution network fault recovery with distributed generation. The mathematical model of fault recovery is established, and the control center agent and sub-task agent are constructed to realize the fault recovery task of distribution network, in which ant colony algorithm is embedded in the sub-task agent to optimize the fault recovery of distribution network. The optimization range of ant colony algorithm is reduced by dynamic alliance of subtask agent, and the search efficiency is improved. The simulation results show the effectiveness of the strategy. Finally, this paper considers the situation that multi-type distributed power supply is connected to smart distribution network in microgrid form. Firstly, the multi-type distributed power generation in microgrid is analyzed, and its stochastic power model is transformed into a constant power model with time or scene. Considering the difference of fault occurrence background, fault setting is carried out from two aspects of continuous fault and discontinuous fault, and the multi-objective distribution network is optimized by evolutionary algorithm based on mobile multi-agent. Finally, the effectiveness of the algorithm is verified by an example with microgrid.
【學位授予單位】：燕山大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM711
本文編號：2212829
[Abstract]:With the promotion and development of smart grid, more and more distributed generation and microgrid are connected to distribution network, which makes the structure of distribution network more and more complex. The traditional optimization algorithm can not fully meet the needs of distribution network fault recovery and reconfiguration. It is particularly important to find a new method strategy to adapt to the complex and changeable distribution network. Based on the research background of distribution network fault recovery, this paper synthesizes the current research status, and carries out the following research on the possible problems in distribution network fault recovery: first, This paper introduces two parts, topology analysis and power flow calculation, which need to be calculated repeatedly in the process of distribution network fault recovery. The advantages and disadvantages of depth-first search algorithm and breadth-first search algorithm are compared. According to the radial operation structure of distribution network, the topological analysis algorithm based on breadth-first search is adopted. On the basis of comparing several different power flow calculation methods, the forward pushback method is chosen as the power flow calculation method in this paper. Secondly, the mobile multi-agent technology is applied to the research of distribution network fault recovery with distributed generation. The mathematical model of fault recovery is established, and the control center agent and sub-task agent are constructed to realize the fault recovery task of distribution network, in which ant colony algorithm is embedded in the sub-task agent to optimize the fault recovery of distribution network. The optimization range of ant colony algorithm is reduced by dynamic alliance of subtask agent, and the search efficiency is improved. The simulation results show the effectiveness of the strategy. Finally, this paper considers the situation that multi-type distributed power supply is connected to smart distribution network in microgrid form. Firstly, the multi-type distributed power generation in microgrid is analyzed, and its stochastic power model is transformed into a constant power model with time or scene. Considering the difference of fault occurrence background, fault setting is carried out from two aspects of continuous fault and discontinuous fault, and the multi-objective distribution network is optimized by evolutionary algorithm based on mobile multi-agent. Finally, the effectiveness of the algorithm is verified by an example with microgrid.
【學位授予單位】：燕山大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM711
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