摘要
面对可控资源的调度特性差异与有功-无功的强耦合性,配电网在如何实现众多资源的协调运行及其模型高效求解方面面临诸多挑战。为解决上述问题,文中计及可调资源的多时段运行特性和无功调整能力,提出一种主动配电网有功-无功协调运行与高效求解方法。首先,利用二阶锥松弛与线性化建模技术,将模型转化为二阶锥规划问题。进而基于ε-松弛,将二阶锥采用多面体进行松弛,将模型转换为0-1混合整数线性规划问题。最后,基于IEEE 33节点配电系统验证了该方法可以兼顾模型求解精度和求解效率,在实现风光充分消纳的基础上,达到节能降损、改善电压水平的目的。
Faced with the difference in dispatch characteristics of controllable resources and the strong coupling of active and reactive power,the distribution network is facing many challenges in how to realize the coordinated operation of many resources and the efficient solution of the model. To solve the above problems,an ADN active-reactive coordination operation and efficient solution method considering the multi-period operation characteristics and reactive power adjustment ability of adjustable resources are proposed. Firstly,based on the second-order cone relaxation and linearization modeling technology,the optimization model is transformed into MISOCP. Further,based on the " ε-relaxation" method,the second-order cone is relaxed by polyhedron,and the model is transformed into a 0-1 MILP that can be efficiently solved. Finally,based on the IEEE 33-node power distribution system,it is verified that the proposed method can balance the accuracy and efficiency of the model.Meanwhile,on the basis of realizing the full consumption of WT and PV,the purpose of saving energy and reducing voltage levels is achieved.
作者
邓振立
张涛
李荣
陈丽娟
DENG Zhenli;ZHANG Tao;LI Rong;CHEN Lijuan(Stale Grid Henan Eletrie Power Company Economic Research Instiute,Zhengzhou 450052,China;Stale Grid Huaian Power Supply Company of Jiangsu Electrie Power Co.,Ld.,Huaian 223001.China;State Grid Nnjing Power Supply Company of Jiangsu Electric Power Co.,Ld.,Nanjing 210019.China;School of Electrical Engineering,Southeast University,Nanjng 210096,China)
出处
《电力工程技术》
2020年第4期104-111,共8页
Electric Power Engineering Technology
基金
国家电网有限公司科技项目“客户侧分布式储能柔性协调控制与联合运行关键技术研究”。
关键词
主动配电网
有功-无功协调调度
二阶锥规划
线性化建模
ε-松弛
active distribution network
active-reactive coordination dispatch
second-order cone relaxation
linear modeling
ε-relaxation