含风力发电的配电网分时段动态无功优化  

Sub-period dynamic reactive power optimization in distribution network with wind power

作　　者：凌峰 史静 

机构地区：[1]国网江苏省电力公司经济技术研究院,南京210008

出　　处：《电测与仪表》2014年第24期16-21,43,共7页Electrical Measurement & Instrumentation

摘　　要：风电场出力具有随机性,将其接入配电网会引起无功补偿设备的动作频繁。为此,提出一种先对风电场有功输出曲线进行分段,再对各个时段进行整体动态无功优化的方法。针对直接对24h风力发电曲线采用整体动态无功优化会引起维数灾导致算法难以收敛的问题,采用基于谱系聚类思想的风电场出力曲线的分段法。针对传统粒子群算法收敛到全局寻优能力较差且易陷入局部最优解的确定,采用云模型对粒子群算法的权值进行动态调整。最后,将上述算法运用于改进的IEEE 33节点系统,仿真结果表明提出的动态优化方法大大缩小了优化的时间,并减少了控制设备的动作次数,从而延长了设备的寿命。The access of wind farm causes frequent action of reactive compensation equipment in distribution network. This paper presents a new method, which first segments the wind power curve and then uses overall dynamic reactive power optimization of all periods.To deal with the problem of dimension curse and convergence problem caused by di-rect overall dynamic reactive power optimization on 24h wind power curve, this paper uses a new segmentation method based on pedigree clustering.To address the problem of traditional particle swarm optimization algorithm which con-verges to global optimal solution slowly and easily falls into local optimal solution, this paper uses cloud model to dy-namically adjust the weights in particle swarm algorithm.At last, the above mentioned algorithm is applied to the im-proved IEEE 33 distribution network.Simulation results show that the proposed dynamic optimization method reduces the optimization time and decreases the action times of control equipment, therefore extends the working life of the fa-cilities.

关 键 词：谱系聚类 分时段 配电网 整体动态无功优化 云模型 

分 类 号：TM761[电气工程—电力系统及自动化]