计及风电的中长期机组检修计划研究

Research on generation maintenance scheduling considering wind power

为解决大规模风电并网使电力系统出现低谷时段大量弃风的问题,利用主成分分析法和分层聚类技术提取风电各季节出力典型模式,并采用均摊法建立相应的通用生产函数,以及考虑风电出力季节特性的发电机组检修计划优化决策模型。以各时段弃风电量最少和检修成本最小为优化目标,采用粒子群算法对该模型进行求解。实际算例验证,该模型与方法可行、有效,提高了风电消纳能力,在发电机组检修决策时考虑风电出力季节特性能够显著减少弃风。

In order to solve the problem,the wind curtailment problem,which was brought by the grid- connection of large- scale wind power system,this paper combined principal component analysis（ PCA） with hierarchical cluster analysis to obtain the typical models of wind power output in four seasons,established the UGF model for wind power output by apportionment in average and the decision model of generator maintenance scheduling plan optimization considering the seasonal characteristics of wind power. Taking minimum wind curtailment and minimum maintenance cost in all maintenance time intervals as optimization objective,the paper solved the model by particle swarm optimization algorithm. The practical example verifies that the model,which is feasible and effective,succeeds in enhancing the capacity of wind power and in reducing wind curtailment when generation maintenance scheduling decision considering the seasonal characteristics of wind power is made.