【作者】 王庆荣；

【导师】 王瑞峰； 杨保成；

【作者基本信息】 兰州交通大学 ， 电气工程（专业学位）， 2019， 硕士

【摘要】 配电网是连接输电线路和用户的重要枢纽,极需提高配电网供电可靠性和电能利用效率应对大规模DG(Distributed Generation,分布式电源)的接入和电力市场化的发展。配电网重构通过改变系统的运行结构从而改变潮流分布,是提高配电网供电质量最经济的手段,对配电网进行多目标优化重构研究具有一定价值。首先,对配电网重构的理论依据进行了阐述,分析了几种典型DG的工作原理以及DG并网对配电网规划和供电可靠性的影响,介绍了前推回代潮流计算法以及DG的潮流计算模型。同时分析PSO(Particle Swarm Optimization,粒子群算法)和SFLA(Shuffled Frog Leaping Algorithm,混洗蛙跳算法)的优缺点,对其进行简化融合得到IPSO(Improved Particle Swarm Optimization,改进粒子群算法)。根据配电网运行结构的特点,采用基于环网十进制编码策略,利用蚁群随机生成树结合IPSO制定了配电网重构策略。其次,建立以有功功率损耗最小、电压偏移指数最低、馈线负荷均衡度最优为目标的配电网静态重构模型,通过Pareto支配获取最优解集,再根据模糊隶属度获取标准化满意度实现多目标优化。通过Matlab仿真软件,对含DG的IEEE-33节点配电系统进行静态重构仿真验证,结果表明,基于IPSO的配电网多目标优化静态重构可以减少有功网损,降低电压偏移指数,改善负荷均衡度,相比PSO算法,迭代次数和寻优时间均有所降低。基于IPSO配电网多目标优化静态重构模型寻优效率高,可以提高配电网的供电质量。最后,分析了单一的以欧氏距离或者皮尔逊为相似度量的不足,将一种基于形态相似和幅值相近的改进双层聚类算法应用到负荷聚类中,根据负荷聚类完成重构时段划分,以有功功率损耗最小、电压偏移指数最低、馈线负荷均衡度最优以及开关操作次数最少为目标建立配电网动态重构模型。仿真结果表明,改进双层聚类可以有效根据形态与幅值进行负荷聚类且具有一定的抗干扰能力,相比静态重构,基于IPSO的配电网多目标优化动态重构降低开关操作次数的同时保证了配电网供电质量。基于IPSO的配电网多目标优化动态重构模型可以提高配电网的供电可靠性和经济性。更多还原

【Abstract】 Distribution network is an important hub for connecting transmission lines and users.It is urgent to improve the power supply reliability and power utilization efficiency of distribution network in order to respond massive access to Distributed Generation(DG)and the development of power marketization.Distribution network reconfiguration changes the power flow distribution by changing the operating structure of the system,it is the most economical means to improve the power supply quality of the distribution network.It is valuable that multi-objective optimization reconstruction of distribution network is studied.Firstly,the theoretical basis of distribution network reconfiguration is explained,the working principle of several kinds of DG and the impact of DG on distribution network planning and power supply reliability is analyzed.The forward and backward power flow calculation is introduced,the power flow calculation model of DG is described.The advantages and disadvantages of the Particle Swarm Optimization(PSO)and the Shuffled Frog Leaping Algorithm(SFLA)are analyzed,Improve Particle Swarm Optimization(IPSO)is obtained through simplification and fusion.According to the characteristics of the distribution network operation structure,the ring-based decimal coding strategy is adopted,using ant colony random spanning tree combine with IPSO to design distribution network reconstruction strategy.Secondly,static reconstruction model of distribution network with minimum active power loss,the lowest voltage offset index and optimal feeder load balance is established.Multi-objective optimization is achieved through the Pareto dominance principle to obtain the optimal solution set,and then obtaining the standardized satisfaction degree based on fuzzy membership degree.Through Matlab simulation software,static reconfiguration simulation verification is establish based on IEEE-33 node power distribution system with DG.The results show that multi-objective optimization static reconstruction of distribution network based on IPSO can reduce active power loss and voltage offset index,and can improve load balance.Multi-objective optimization static reconstruction of distribution network based on IPSO can reduce the iteration times,and can shorten the optimization time compared to PSO.Multi-objective optimization static reconstruction model of distribution network based on IPSO has high efficiency,and can improve the power quality of the distribution network.Finally,deficiency is analyzed when Euclidean distance or Pearson correlation coefficient is as similarity measure.An improved two-layer clustering algorithm based on morphological similarity and similar amplitude is applied to load clustering,and the reconstruction period is divided according to load clustering.Dynamic reconstruction model of distribution network is established with minimum active power loss,the lowest voltage offset index,minimum feeder load balance and minimum times of switching operation.The simulation results show that the improved two-layer clustering can cluster load based on morphology and magnitude effectively and has definite anti-interference ability.Compared with static reconstruction,multi-objective optimization dynamic reconstruction of distribution network based on IPSO reduces the times of switching operation while ensures the power quality of distribution network.Multi-objective optimization dynamic reconstruction model of distribution network based on IPSO can improve power supply reliability and economy of distribution network.更多还原