七种最优潮流分解协调算法的性能比较

目前应用于最优潮流领域的诸多分解协调算法缺乏统一的比较基础,为此,将7种最优潮流分解协调算法用于求解同一系统,力求获得更为客观公正的结论。文中首先采用区域划分的方式将以现代内点理论为基础的7种最优潮流分解协调算法分成4类,即母线撕裂类、边界重叠类、边界分区类和节点解耦类,并简要阐述各算法的模型和计算过程。然后以IEEE 300节点系统为基础,分别构造了2区域600节点和4区域1 200节点系统,比较了各最优潮流算法的收敛性、计算速度和通信量等性能,探讨了参数变化对算法稳定性的影响。最后,以MATLAB并行实验室为平台,进一步测试了各算法的并行性能。测试结果表明,在7种分解协调算法中,近似牛顿方向法在计算速度和通信量方面表现最佳,分解协调内点法的收敛性和稳定性最好。

Comparative Analysis of Seven Decomposition and Coordination Algorithms for Optimal Power Flow

Currently, the decomposition-coordination algorithms used in optimal power flow(OPF)lack a unified basis for comparison. For this reason, the seven kinds of decomposition-coordination algorithm are used for solving the same power system so as to get more objective and fair conclusions. The decomposition-coordination optimal power flow algorithms based on the modern interior point theory are divided into 4 categories by using the area partition method, with the model and calculation process of each algorithm briefly described. The 4 categories are the bus splitting method, the overlap boundary method, the boundary-area partition method and the node decomposition method. In order to fully compare and analyze the performance of the 7 algorithms, 2-region 600-bus and 4-region 1 200-bus systems are constructed as test cases based on an IEEE 300-bus system. Calculation results are obtained by means of vector programming, and then a comparison of the convergence, calculation speed, the amount of communication and stability is conducted. Finally, based on the MATLAB parallel laboratory, the parallel performance of each algorithm is tested. Test results show that the approximate Newton direction(AND)method has better performance in terms of calculation speed and amount of communication, while the convergence and stability of the decomposition coordination interior point method(DCIPM)is better than the other algorithms.