基于改进ABC算法的含分布式电源配电网无功优化研究

发布时间：2018-04-30 21:39

本文选题：分布式电源 + 无功优化　；参考：《兰州交通大学》2017年硕士论文

【摘要】：配电网的无功优化是增强网络电压水平、降低网络损耗、保障电力网安全稳定运行的一项重要手段。采用在配电网中安装DG(Distributed Generation,分布式能源)可在一定程度上缓解目前所面临的能源危机,达到节能减排,环保低碳的目标。但是DG加入配电网使网络中的潮流分布发生变化,从而使配电网的规划、运行以及控制方式发生改变。本文研究含DG的配电网的无功优化问题,所做的主要工作如下:(1)本文构建含DG配电网的无功优化模型,其以减少系统的网损为目标,且考虑系统电压的稳定性指标以及DG的无功调节的能力。同时基于无功裕度值的计算,确定无功补偿点。模型以DG的无功出力以及电容器组投切组数作为无功优化模型的控制变量,以网络中负荷节点电压作为其状态变量,经过优化并网DG的无功出力大小以及所配置的电容器组的无功补偿量达到对含DG配电网无功优化的目的。(2)对含不同DG的潮流算法进行改进。首先将DG分别等效为不同的节点类型,通过前推回代法求解含不同DG的潮流计算。在处理PV节点时,通过无功分摊原理设定无功初值,采用无功补偿的方法进行功率修正。在IEEE33节点配电系统上,对含不同DG的配电网进行潮流计算。仿真结果表明,DG的接入能提升系统节点电压。(3)提出一种MABC(Modified Artificial Bee Colony,改进的人工蜂群)算法。通过借鉴DE(Differential Evolution,差分进化)算法的突变算子,使跟随蜂的搜索策略受个体目前所获得的最优值的引导,并加入扰动项,使算法的全局探索与局部开采能力得以平衡。此外,根据标准ABC算法中侦察蜂搜寻机制的不足,本文融合一般反向学习策略的思想,生成之前遗弃蜜源的反向解,加强了侦察蜂的搜寻经验,进一步提高算法的搜索效率。在仿真实验中可以发现,改进的算法保持了ABC算法简单容易实现的特点,增强了全局收敛性,有效提高了算法的收敛速度和收敛精度。(4)本文采用IEEE33以及美国PGE69节点系统进行MATLAB仿真测试,分别使用本文提出的MABC算法、标准ABC算法和文献中的IABC算法进行优化计算并比较,测试结果验证了本文所搭建的含DG配电网无功优化数学模型和提出的MABC算法的有效性,其能够使配电系统中的无功功率分布得以合理的优化。此优化方案可有效提高配电网的电压水平和电力系统运行的稳定性。
[Abstract]:Reactive power optimization is an important means to enhance network voltage level, reduce network loss and ensure the safe and stable operation of power network. Installing DG(Distributed Generation (distributed Energy) in the distribution network can partly alleviate the current energy crisis and achieve the goal of saving energy and reducing emissions and protecting environment and low carbon. However, the distribution of power flow in the distribution network is changed by adding DG to the distribution network, and the planning, operation and control mode of the distribution network are changed. In this paper, the reactive power optimization problem of distribution network with DG is studied. The main work is as follows: 1) in this paper, the reactive power optimization model of distribution network with DG is constructed, which aims at reducing the network loss of the system. The stability index of system voltage and the ability of reactive power regulation of DG are also considered. At the same time, the reactive power compensation point is determined based on the calculation of reactive power margin. In the model, the reactive power of DG and the number of capacitor switching groups are taken as the control variables of the model, and the load node voltage in the network is taken as the state variable. The power flow algorithm with different DG is improved by optimizing the reactive power output of DG and the reactive power compensation of the capacitor bank to optimize the reactive power of distribution network with DG. First, the DG is equivalent to different node types, and the power flow calculation with different DG is solved by the forward pushback method. In dealing with PV nodes, the reactive power initial value is set by the reactive power allocation principle, and the reactive power compensation method is used to correct the power. The power flow of distribution network with different DG is calculated on IEEE33 node distribution system. The simulation results show that the access of DG can increase the node voltage of the system. (3) A MABC(Modified Artificial Bee colony algorithm is proposed. By using the mutation operator of the DE(Differential evolution (differential evolution) algorithm, the search strategy of the following bee is guided by the optimal value obtained by the individual at present, and the disturbance term is added to balance the global exploration and the local mining ability of the algorithm. In addition, according to the deficiency of search mechanism of reconnaissance bee in standard ABC algorithm, this paper combines the idea of general reverse learning strategy to generate the reverse solution of abandoned honey source, which strengthens the search experience of reconnaissance bee, and further improves the search efficiency of the algorithm. In the simulation experiment, it can be found that the improved algorithm keeps the characteristic of ABC algorithm simple and easy to realize, and enhances the global convergence. The convergence speed and precision of the algorithm are improved effectively. (4) in this paper, IEEE33 and PGE69 node system are used to carry out MATLAB simulation test, and the MABC algorithm, standard ABC algorithm and IABC algorithm in literature are used to optimize and compare, respectively, the proposed MABC algorithm, the standard ABC algorithm and the IABC algorithm in the literature. The test results verify the validity of the mathematical model of reactive power optimization with DG and the proposed MABC algorithm, which can optimize the distribution of reactive power in distribution system. This optimization scheme can effectively improve the voltage level of distribution network and the stability of power system operation.
【学位授予单位】：兰州交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM714.3

【参考文献】