基于自适应多行为模式鱼群算法的电能计量设备运维作业优化研究

随着网络化、信息化技术在电力行业的深入推广,传统的电能计量设备运维作业模式早已无法满足当今的管理需求。针对传统运维作业模式中所存在的路径规划不科学,作业过程耗时长、能耗高,且难以实时掌握和调整运维作业进度等问题,首先建立基于智能优化算法的电能计量设备运维作业优化模型,并提出了一种自适应多行为模式的人工鱼群算法完成对该优化模型的求解。仿真实验表明,所提出的自适应多行为模式鱼群算法对于多局部极值问题具有更好的优化精度,且能够在所建立的运维作业优化模型基础上完成对全局最优路径的求解。

Research on operating and maintaining task optimization of electric meter based on adaptive multi-behavior fish swarm algorithm

Due to the development of net and information technology in power industry,the traditional operating and maintaining mode of electric metering device (OM-EM) is not fit for the modem requirement.In terms of the weaknesses of traditional mode of OM-EM,for instance,the unscientific path planning,long time cost and high energy cost,and the difficulty in grasping and adjusting process of OM-EM work,this paper proposes a rew method.A novel multi-behavior fish swarm algorithm (MB-FSA) is proposed,and is also utilized in solving OM-EM problem based on the mathematical model which is also built in this study.Experimental simulation result shows that the proposed MBFSA outperforms some state-of-the-art algorithms significantly,and can solve the OM-EM problem effectively.