摘要
在能源紧缺、污染严重的时代背景下,分布式电源迅速普及。含分布式电源的配电网规划研究日益增多,而将分布式电源以微电网的形式考虑到配电网规划之中还鲜有研究。将不同类型的分布式电源、储能装置以微电网的形式接入配电网,充分考虑微电网加入对变电站规划和网架规划产生的影响。基于微电网系统模型,分别建立配电网规划中变电站选址定容模型及网架规划模型,利用改进粒子群算法求解上述两个多目标非线性化模型,并计算由微电网带来的变电站容量削减量及配电网故障时的可避免停电损失费用。以IEEE50节点为算例验证此模型,算例验证了所提模型有利于提高系统的可靠性和经济性,优化了网架结构,具有实际工程参考意义。
Under the background of energy shortage and severe pollution,the distributed generations spread rapidly.The study of the distribution network planning with distributed generations is also increasing.However,little research has been done into the study that is the planning of distribution network with distributed generations which are in the form of micro-grid.In this paper,different types of distributed generations and energy storing device are connected to the distribution network in the form of micro-grid.And the influence which is created as the micro-grid joins on the planning of substation and the network is fully considered.Model of substation locating and sizing and network planning is respectively established based on model of micro-grid system.The foregoing multi-objective nonlinear models are solved by using the improved particle swarm algorithm.In addition,the reduction of substation capacity and the interruption cost which can be avoided during the fault of distribution network that are both caused by micro-grid are calculated.Finally,IEEE50-node example is used to verify that the proposed model is in favor of improving the reliability and economy of the system.And it is also good for structure of the network.The model in this paper has practical engineering significance.
作者
杨昆
周晓健
夏能弘
邹龙
訾红亮
张光鑫
Yang Kun;Zhou Xiaojian;Xia Nenghong;Zou Long;Zi Hongliang;Zhang Guangxin(School of Electrical Engineering,Shanghai University of Electric Power,Shanghai 200090,China;State Grid Fuyang Power Supply Company,Fuyang 236017,Anhui,China)
出处
《电测与仪表》
北大核心
2019年第2期52-58,69,共8页
Electrical Measurement & Instrumentation
基金
国家自然科学基金资助项目(51607110)
关键词
微电网
分布式电源
配电网规划
改进粒子群算法
micro-grid
distributed generation
distribution network planning
improved particle swarm algorithm
