摘要
分布式电源(DG)的选址和定容是微电网的重要组成部分,通过建立以有功网损、电压偏移量、DG投资与运行成本为目标的多目标优化模型,提出了一种改进正交优化群智能算法对分布式电源进行规划.将分布式电源规划应用于正交试验中,并且在正交试验的DG容量方差分析中加入方差比例分析,为DG的规划提供搜索方向和搜索范围,寻求最优解.最后通过实际算例仿真计算并与遗传算法相比较,验证了该算法的有效性和优异性,为分布式电源的规划提供了新的思路.
The location and sizing of distributed generation（DG） is an important part of micro grids. A multiohjective optimization model of active power loss, voltage offset and the DG＇s cost of investment and operation is established. An improved orthogonal optimization swarm intelligence algorithm is proposed for distrib- uted generation planning. The DG is applied to orthogonal test. The variance ratio analysis is added to variance analysis of the DG capacity in orthogonal test. Orthogonal optimization swarm intelligence algorithm provide search direction and search scope for the planning of DG to find the optimal solution. Finally, compared with the genetic algorithm, the effectiveness and the advantages of the proposed algorithm are verified by a practi- cal example. The orthogonal optimization swarm intelligence algorithm provides a new idea for the planning of the distributed generation.
出处
《三峡大学学报（自然科学版）》
CAS
北大核心
2018年第1期59-63,共5页
Journal of China Three Gorges University：Natural Sciences
基金
国家自然科学基金项目(51407104)
关键词
分布式电源
改进正交优化群智能算法
选址和定容
多目标优化
distributed generation（DG）
improved orthogonal optimization swarm intelligence algorithm
location and sizing
multiobjective optimization
