中文摘要：

发电机组一旦故障，不仅需要较大费用更新破损元件，而且恶化了系统可靠性，增大了运行成本。当前的检修模型未考虑该因素的影响，或将其故障率简化为一常数，对系统运行带来风险。文中基于机组浴盆曲线的失效模式及其期望更新费用，分析了机组检修及故障停运对系统运行成本的影响，包括系统可靠性成本、发电成本、机组更新成本及检修成本，其中前两者通过等效电量函数进行系统随机生产模拟确定。基于此，以最小化规划期内系统总运行成本确定检修计划，由于其非线性、不可微，因而采用遗传算法进行求解。与常规模型相比，强调了机组变化故障率对系统及其自身运行的影响，21机系统的仿真结果验证了其有效性和实用性。

英文摘要：

This paper proposes a novel unit maintenance scheduling （UMS） model, considering the influence of unexpected unit failures. The Uncertain factor not only leads to costly expenditure for replacing the damaged components, but also lowers the system reliability and increases the operation cost. This is rarely considered or is often simplified as a constant value in the existing approaches. Based on the generator＇s bath-curve failure model and the corresponding renewable costs, the impacts of scheduling outage and unexpected failures on the operational costs are discussed in detail. The reliability costs and generation costs of the system, and the renewable costs and maintenance costs of generating units are included in the operational costs analysed. The former two costs are calculated through the system probabilistic production simulation by equivalent energy function （EEF） method. Subsequently, the UMS model is presented to minimize the total costs over the whole planning horizon, which is solved by a genetic algorithm because of its non-linear and non-differentiable characteristics. Finally, numerical examples based on a 21-unit system are utilized to demonstrate the usefulness of the proposed scheme.