摘要
为确定并联电容器在10 kV配电网中的容量和位置,同时考虑补偿后的经济效益,将无功补偿容量最少、电能损耗最小分别作为目标函数,建立多目标无功优化模型。提出了基于多种群聚类鱼群算法的无功规划方法,该论文利用不同鱼群对不同目标分别进行优化,获得多个全局最优解,通过不同鱼群之间的食物浓度信息交换,提高鱼群逃离局部最优解的能力;该发明采用k均值聚类发对系统中节点的灵敏度进行分析聚类,确定并联电容器的安装位置,另外,将各节点的灵敏度作为鱼群的食物浓度信息,加快了算法的寻优速度。通过IEEE69系统仿真计算验证了该模型及算法的有效性和可行性。结果表明该模型及算法能够有效降低系统功率损耗,提高电压质量、减少补偿容量。
In order to determine the capacity and location in the 10kV distribution network of shunt capacitor, at the same time, considering the economic benefit compensation, n this paper, the reactive power compensation capacity and minimum power loss are used as the objective function, and the multi-objective reactive power optimization model is established. The reactive power planning methods of cluster based on fish swarm algorithm, in this paper, different fish populations are optimized to obtain multiple global optima. The ability to improve the local optimal solution by the exchange of information between different fish stocks. The sensitivity of the nodes in the system is analyzed by means of K means clustering, and the installation position of the shunt capacitor is determined. In addition, the sensitivity of each node is used as the food concentration information, and the speed of the algorithm is accelerated. The validity and feasibility of the proposed model and the algorithm are verified by IEEE69 system simulation. The results show that the proposed model and algorithm can effectively reduce the system power loss, improve voltage quality and reduce the compensation capacity.
出处
《云南电力技术》
2016年第1期6-8,25,共4页
Yunnan Electric Power
关键词
动态无功优化
鱼群算法
K均值聚类
多目标
dynamic reactive power optimization
fish swarm algorithm
K-means
multi-objective
