A Comparative Study Of Novel Symmetric Sparse Matrix Techniques In Various Power Flow Algorithms

Electricity is the basic industry in China,and the security of the power system is very important.In the analysis of power system networks,the importance of power flow calculation is self-evident,and it plays an important role in power system planning and design and quantitative analysis of the power system's operation.For many years,scholars from all over the world have conducted in-depth research on different algorithms.Newton-Raphson power flow algorithm and PQ decomposition method are the most classic representatives.Many people are committed to optimizing different power flow algorithms in different ways,but these two algorithms still have more in-depth research space.In this paper,the application of symmetric sparse matrix technology in different power flow algorithms is introduced in detail,and in each algorithm,we propose an improved method based on symmetric sparse matrix technology,these two improved methods also compared with traditional algorithms seperately.The specific comparative research mainly focuses on the reading of data files,the formation of Jacobi matrix or factor table,and the various iterative processes,for example,the comparison between the storage of Y(n,d)form and the storage of traditional methods,the comparison between the formation of Jacobian matrix and factor table and the traditional method after symmetric sparse matrix technique is applied,the comparison of the efficiency of time and so on.