海上风电机组分阶段预防性维修策略

针对海上恶劣环境所引起维修费用昂贵的问题,结合部件失效率曲线,提出了海上风电机组分阶段预防性维修策略。首先引入容量因子,修正海上风电机组单位时间停机损失。其次,视风电机组为多部件复杂系统,结合维修情况更新部件和机组可靠性。在考虑预防性维修成本和对机组可靠性提高量的影响下,构建费效比(return on investment,ROI),采用离差标准化方法,确定各个部件的维修方式。以单位时间维修成本最低为目标,部件可靠性为约束,采用反向粒子群算法(opposition based learning-particle swarm optimization,OBL-PSO),得到最优维修时间间隔和全寿命周期内预防维修次数。最后,以某海上风电机组为例进行仿真分析。仿真结果表明,分阶段预防性维修策略比传统等时间间隔的维修策略减少了停机维修次数,能够进一步降低维修成本,为海上风电机组维护策略的制定提供指导。

Phasic Preventive Maintenance Strategy of Offshore Wind Turbines

Aiming at the problem of high maintenance cost caused by poor marine environment,combined with bathtub curve,this paper proposes a phasic preventive maintenance strategy for offshore wind turbines.Firstly,we introduce the capacity factorto revise the downtime loss per unit time of offshore wind turbines.Secondly,the wind turbine is regarded as a multi-component system,and the reliability of components and unit is updated according to the maintenance activity.Under the influence of preventive maintenance cost and reliability improvement,we construct the return on investment (ROI),and adopt the standard deviation method to determine the maintenance method of each component.Then,we take the maintenance cost per unit time as the goal,the component reliability as the constraint,and adopt opposition based learning-particle swarm optimization (OBL-PSO) algorithm to obtain the optimal maintenance interval and the number of preventive maintenance times in the whole life cycle.Finally,the simulation results of an offshore wind turbine caseshow that the proposed phasic preventive maintenancestrategy reduces the number of maintenance times and saves maintenance costs compared with the traditional preventive maintenance strategy,which can provide reference for the development of offshore wind turbine maintenance strategy.