多区域输电阻塞管理的拉格朗日松弛分解算法

LAGRANGIAN RELAXATION BASED MULTI-REGION TRANSMISSION CONGESTION MANAGEMENT

提出一种新的基于增广拉格朗日松弛的区域分解最优潮流算法 ,将一个大的最优潮流问题分解成多个区域子问题 ,并用此算法求解多区域电力市场输电阻塞管理问题。与现有的其他方法相比 ,该算法的主要优点在于无需在原始网络模型的基础上增加任何虚拟发电机或负荷。通过将该算法与电力市场实时平衡机制相结合 ,多区域有功阻塞管理问题可以分解为单区域二次规划子问题。这些子问题可以顺序求解也可以并行求解。采用这一方法 ,所有的区域市场独立调度员在得不到其他区域网络信息的情况下仍然可以相互协作消除网络阻塞。在这一过程中 ,惟一需要进行区域间交换的信息是与区域间“耦合”约束相对应的拉格朗日乘子。最后 ,通过分析 3区域的 IEEE RTS— 96标准测试系统说明了该方法的有效性。

In this paper an augmented Lagrangian Relaxation based algorithm for regional decomposition optimal power flow (OPF) is presented to address congestion management across interconnected regions. An OPF problem is decomposed into regional sub-problems through Lagrangian relaxation. Unlike other existing methods, no dummy generators or loads are added into the original network model. Applying this algorithm with the Real-time Balancing Mechanism, the problem of active power congestion management across interconnected regions is separated into quadratic regional sub-problems, which can be solved either sequentially or in parallel. With this approach, regional ISOs can relieve network congestion coordinatedly without knowing any other regions' network information but the correspondent Lagrangian multipliers of coupling constraints between regions. The IEEE RTS-96 with three interconnected regions is studied to illustrate the effectness of the proposed approach.