海上风电机群维修排程在线多目标决策模型

On-line Multi-objective Decision Model for the Maintenance Scheduling of Offshore Wind Turbine Group

结合海上风电机群特点,介绍风电机群维修决策系统框架和决策流程,分析风电机组维修作业流程和成本构成。以风电机群整体维修成本、作业工作量均衡性为目标函数,以维修中心物料和人力资源配置为约束条件,建立海上风电机群日间维修作业排程多目标决策模型。采用地理信息系统中的Kruskal空间分析算法寻找每组维修作业的往返路径最小生成树。应用带精英保留策略的离散粒子群算法求解模型,计算出全部待检修机组组合及其具体作业时段的非劣解集。仿真算例分析结果表明,模型可以降低维修总成本,验证了所提模型的可行性以及求解算法的有效性。

Based on the discussion of the offshore wind turbine characters different than thermal power generator, the framework and decision process of maintenance decision system for wind turbine was introduced, the maintenance operation flow and total maintenance cost of wind turbine was analyzed. On purpose of enhancing the maintenance efficiency and reducing the generation cost of offshore wind turbine group, an on-line multi-objective decision model for the daily maintenance scheduling of offshore wind turbine group was proposed in this paper, which minimizes the total maintenance cost and the workload balance with the constraints of budgets and human resources. The Kruskal spatial analysis algorithm of Geographic Information System （GIS） was applied to find the minimum spanning tree of return path of each maintenance operations combination. The Binary Particle Swarm Optimization （BPSO） was employed to solve the model, and obtains all non-dominated solution set of maintenance turbines combination and their exacted maintenance time. The simulation result shows the feasibility of the proposed model, and the effectiveness of the algorithm is verified.