超大规模电网快速状态估计的实现方法

Implementation Method for Fast State Estimation of Super-large Power Grid

随着一体化互联大电网全局分析决策中心的建设,对实时状态估计计算速度提出了更高要求。采用多线程并行计算技术实现了快速分解状态估计信息矩阵的快速计算,在稀疏矩阵节点优化编号及其因子分解过程中采用标准模板库关联容器存储稀疏矩阵。基于新一代调控系统验证环境和实际电网拼接模型算例进行了验证。结果表明:在超大规模电网状态估计中,采用多线程并行计算信息矩阵及其因子分解具有较高的加速比,结合基于关联容器的稀疏矩阵存储格式,能够有效提升编程效率和程序品质以及状态估计的计算效率。

With the construction of global analysis and decision-making center for integrated interconnected large power grid,higher speed is needed for the calculation of real-time state estimation.The multi-thread parallel computing technology is used to realize the fast calculation of the gain matrix of the fast decoupled state estimation,and the STL associated container storage format is used in the process of sparse matrix bus optimal ordering and its triangular factorization.Based on the verification environment of the new generation control system and the actual grid connection models,case calculations are carried out.The results show that the multithreaded parallel calculation of the gain matrix and its factorization have a higher speedup ratio when used for state estimation of super large power grids,and can effectively improve the programming efficiency and quality and the computation efficiency of the state estimation when combined with the STL associated container based sparse matrix storage format.