基于主从问题的电力系统最优主动解列

The Optimal Controlled Partitioning Strategy for Power Systems Based on the Master-slave Problem

系统主动解列的完整模型为大规模非线性混合整数规划问题,大多采取完全分解方法,因而只能求得近似解,针对此问题提出了基于主从问题交替求解电力系统最优主动解列断面的新策略,从而求得更优解。该策略基于图背包理论(connected graph constrained knapsack problem,CGKP)将完整主动解列模型转化为主从问题;主问题为图的最优平衡分割问题,采用CGKP技术进行求解;从问题为基于直流最优潮流(optimal power flow,OPF)的调度问题,采用OPF技术进行求解;主从问题之间通过节点负荷的调节量实现耦合。通过主从问题之间的交替迭代获得更优的解列方案,同时也使得解列方案更接近于完整模型的最优解。算例分析表明,该算法相对于其他近似求解策略,所获得的解列方案可使系统总切机切负荷量更少,从而证明了该方法的有效性和可行性。

Complete splitting model of the controlled partitioning strategy is a large-scale nonlinear mixed integer programming problem and mostly solved by approximate decomposition algorithms. Only the approximate solution can be gained. To solve this problem, a new alternate optimization method based on master-slave problem is proposed to search for optimal splitting strategy. The complete model was converted into master-slave problems based on connected graph constrained knapsack problem （CGKP）. The master problem is graph partitioning problem, which is solved by CGKP algorithm, and the slave problem is direct current optimal power flow （OPF）. The coupling between master problem and slave problem is achieved through load adjustment. A better splitting strategy, which is closer to the optimal solution of the complete model, can be obtained through the alternating iteration between the master problem and the salve problem. The results of the examples show that the proposed method can obtain better splitting strategy with less shed load than other approximate algorithms, which verifies the feasibility and effectiveness of the proposed method.