摘要
在基于鼠笼式感应发电机(SCIG)和静态无功补偿器(SVC)的风电网络中,风速的变化导致风功率变化,为了优化电压分布,需要将SVC和其他无功设备以最优的方式投入。目前的优化方法基于有功损耗最小和电压偏差最小这两个目标函数。SVC无功功率储备(SVC-RPR)最大作为一个新的目标函数被引入。3个目标函数按照一定的权重合成一个总的目标函数,并采用粒子群优化算法(PSO)对该目标函数进行求解。最后建立无功优化方案模型进行测试仿真,得到对SVC进行有效控制可以很好地改善电压分布的结论。
In a wind power network based on squirrel-cage induction generator （SCIG）and SVC,the change of wind speed causes the change of wind power. In this case,in order to optimize voltage distribution,the SVC and other reactive equipment should be put in the best way. At present,the optimization methods mainly based on two objective functions of minimizing the total active power losses and the total voltage deviations. The SVC reactive power reserve （SVC-RPR）is added to the problem as a third objective function to be maximized with the purpose of further compensation usage during dynamic operation. The three objective functions are synthesized to a general objective function according to certain weights. And then,the PSO is used to solve the objective function. At last, reactive power optimization model is built and the simulation is tested,the conclusion is the voltage distribution is improved obviously with the effective control of SVC.
出处
《电力科学与工程》
2014年第3期73-78,共6页
Electric Power Science and Engineering
关键词
无功优化控制
粒子群优化算法
SVC-RPR
SCIG
optimal reactive power control
SVC-RPR
SCIG
PSO
