基于仿真优化智能变电站巡检机器人路径研究

智能变电站巡检机器人对于保证电力系统的安全、稳定、可靠运行具有重要意义,同时具有提高巡检质量及提升能效的作用。针对实际应用中巡检机器人路径规划基于静态地图、难以应对未建模环境信息以及系统存在随机因素的问题,文中提出了一种基于仿真优化方法的巡检机器人路径策略改进的方法。首先通过巡检过程中的实时观测信息,利用随机方法产生用于仿真优化的运行样本,然后在给定的规划策略的基础上利用仿真样本进行路径策略的改进,在保证路径策略性能的同时降低机器人的计算负荷。仿真实验结果表明,所提出的方法可以在栅格环境下有效的应用于给定的基于规则的路径策略和贪婪路径策略的性能改进。

Research on path optimization of intelligent substation inspection robot based on simulation

Intelligent substation inspection robot is of great significance for ensuring the safe, stable and reliable operation of power system, as well as improving the inspection quality and energy efficiency. In practice, the path planning algorithms of inspection robot are usually based on static map, which cannot effectively deal with the unknown substation information and the random factors of system. This paper proposes a simulation-based optimization method to improve the path strategy of inspection robot. First, through the real-time observation in patrol, random sampling method is used to generate running samples for simulation optimization. Then, based on the given planning strategy, the simulation samples are used to improve the path strategy to ensure the path strategy performance while reducing the computational burden of the robot. The simulation results show that the proposed method can effectively improve the rule-based strategy and greedy strategy in grid environment.