摘要
分布式电源的接入不仅改变了电网的潮流分布和拓扑结构,而且使微电网系统的状态估计面临新的挑战。基于有限的实时量测和包含分布式电源节点的伪量测提出微电网状态估计量(MGSE),并分别采用改进的传统加权最小二乘法(WLS)和粒子群智能算法(PSO)对微电网进行求解。利用Matlab对一典型欧洲低压微电网系统的状态估计进行仿真,验证了该估计量能准确地描述系统的状态,并比较了两种算法的优劣,为含微电网的电力系统预测控制和性能优化提供了基础。
The installation of distributed generation（ DG） not only alters the power flow distribution and topology of the grid,but also makes the state estimation in micro-grid systems face more challenges. This paper presented a micro-grid state estimator（ MGSE） based on few real-time telemetered measurements and pseudo measurements for the DG bus,and used the improved traditional WLS algorithm and PSO intelligent algorithm respectively to solve the model. The test results of a typical European low voltage micro-grid system demonstrate the MGSE can accurately describe the system＇s state. The paper compared the advantages and disadvantages of the two algorithms,which is the basis for predictive control and performance optimization of the micro-grid.
出处
《电器与能效管理技术》
2014年第16期33-38,共6页
Electrical & Energy Management Technology
基金
国家科技支撑计划课(2013BAA01B04)
关键词
状态估计
微电网
加权最小二乘法
粒子群算法
state estimation
micro-grid
WLS algorithm
particle swarm optimization（PSO）
