考虑时变故障率的架空输电线路最优巡检策略研究

目前输电线路的巡检周期多为固定性周期,不能根据线路的运行状态和环境状况进行及时调整,影响线路的供电可靠性和经济性运行。针对这一问题,给出了一种考虑时变故障率的架空输电线路最优巡检策略。以包括巡检成本、故障电量损失成本和维持可靠性的成本在内的综合目标效益函数最大作为指标,建立了基于遗传算法的线路巡检策略模型。为了得到更精确的效益函数,建立了非时齐马尔可夫时变停运模型,并结合蒙特卡罗可靠性仿真模型得到了可靠性指标,最后通过遗传算法求解出一个动态、周期可变的输电线路巡检计划。通过中部和东部两个故障率特征不同地区的实例计算,表明算法能根据输电线路的实际故障率大小进行巡检策略制定,并得到一个经济、合理、区域性、分季节性、动态可变的巡检周期计划。这避免了传统巡检过度和巡检不足的问题,能在获得较大经济效益的条件下,保证输电线路以较好的状态运行。

Research on optimal inspection strategy for overhead transmission line considering time-varying failure rate

At present, the inspection cycle of transmission lines is mostly fixed, which can not be adjusted in time according to the operation status and environmental conditions of the lines, which affects the reliability and economic operation of power supply. To solve this problem, an optimal inspection strategy of overhead transmission lines considering time-varying failure rate is proposed. The model of inspection strategy based on genetic algorithm is established with the maximum comprehensive objective benefit function including inspection cost, failure power loss cost and maintenance reliability cost as the index. In order to establish a more accurate benefit function, a non-time homogeneous Markov time-varying outage model is established, and the reliability index is obtained by combining with Monte Carlo reliability simulation model. Finally, a dynamic and periodic variable transmission line inspection plan is solved by genetic algorithm. Through the calculation of the two regions with different fault rate characteristics, it is shown that the algorithm can make the inspection strategy according to the actual fault rate of transmission lines, and get an economic, reasonable, regional, seasonal and dynamic variable inspection cycle plan. It avoids the problem of over inspection and insufficient inspection, and can achieve greater economic efficiency under the favorable condition, the transmission line can operate in a better state. This work is supported by Youth Fund of National Natural Science Foundation of China (No. 51007066).