计及灵活性的检修—运行协同优化模型及算法

为提升风电并网条件下电力系统的运行灵活性,提出一种结合场景分析和协同优化的检修—运行决策方法。采用K-medoids聚类方法获得风电出力典型场景集,同时根据典型性评估指标确定目标场景集规模。以经济性和灵活性为目标,建立融合多场景经济调度的"检修—运行"分层协同优化模型。为提高模型求解效率,引入对潮流安全违约"轻容忍"的改进Benders分解法,降低运行优化主问题的约束矩阵维数。通过拉格朗日松弛技术及乘子更新机制,实现检修和运行的协同寻优。算例测试验证了所述模型及算法能有效实现经济性及灵活性更优的检修—运行决策。

Collaborative Optimization Model and Algorithm of Maintenance and Operation Considering Flexibility

To improve the operation flexibility of power system with integrated wind power, a method of maintenance and operation decision based on scenario analysis and collaborative optimization is proposed. The typical scenario set of wind power output is obtained via K-medoids clustering method, and the target scenario set size is determined according to the typicality evaluation indices. With economy and flexibility as the goal, a maintenance-operation bilevel collaborative optimization model combined with multi-scenario economic dispatch is formulated. To improve the solving efficiency, an improved Benders decomposition method with light tolerance of power flow limit violation is introduced to reduce the dimension of the constraint matrix in the main problem of operation optimization. Lagrangian relaxation technique and multiplier update mechanism help to coordinate the maintenance schedule and operation optimization. The case study shows that the proposed method can effectively optimize the economy and flexibility of maintenance and operation decision.