基于改进多目标差分灰狼算法的配电网无功优化

Reactive Power Optimization of Distribution Network Based on Improved Multi-objective Differential Gray Wolf Optimization

  • 摘要: 配电系统静止同步补偿器(Distribution Static Compensator,DSTATCOM)接入配电网能够有效解决高渗透率的光伏与时变负荷对主动配电网带来的影响.对含DSTATCOM与并联电容器组(capacitor banks,CB)的配电网进行协调无功优化能够有效解决分布式光伏以及时序负荷对系统电能质量的影响.本文以有功网损、电压偏差以及补偿容量最小为目标函数,建立了DSTATCOM与CB的配电网协调无功优化模型.针对原始灰狼算法(gray wolf optimization,GWO)中不足,提出多目标差分灰狼算法(multi-objective differential evolution gray wolf optimization,MODEGWO).最后以IEEE 33节点系统为例,引入某地区典型日光伏与负荷的时序波动功率,对含DSTATCOM与并联电容器组进行协调无功优化,得到动态运行策略.仿真结果验证了所提模型与算法的正确性与有效性.

     

    Abstract: Distribution static compensator (DSTATCOM)can effectively solve the impact of high penetration of photovoltaic and time-varying load on the active distribution network.Coordination reactive power optimization of distribution network with DSTATCOM and shunt capacitor banks (CB)can solve the impacts on power quality, which is attributed to the time-varying nature of photovoltaic and loads.This paper, considering the active power loss, voltage deviation, and compensation capacity as objective functions, establishes the coordination reactive power optimization model of DSTATCOM and CB.Aiming at the shortcomings of the original gray wolf algorithm (GWO), multi-objective differential evolution gray wolf optimization (MODEGWO)is proposed.The IEEE 33 system is selected as an example.Coordination reactive power optimization between DSTATCOM and CB is carried out, taking into account the time-varying photovoltaic system and load, and the dynamic operation strategy is obtained.The simulation results verify the rationality and validity of the proposed model.

     

/

返回文章
返回