Weighted Elimination Tree Modeling Method and Its Application in Power Grid Matrix Ordering Performance Evaluation

被引:0
|
作者
Guo J. [1 ]
Zhou J. [1 ]
Li Q. [1 ]
Luo Y. [1 ]
Li J. [1 ]
Zhang Y. [1 ]
Lang Y. [1 ]
机构
[1] Beijing Key Laboratory of Power Dispatching Automation Technology Research and System Evaluation, China Electric Power Research Institute, Haidian District, Beijing
来源
Guo, Jian (guojian_715@126.com) | 2018年 / Power System Technology Press卷 / 42期
关键词
Analytic hierarchy process; Ordering methods; Performance evaluation; Weighted elimination tree;
D O I
10.13335/j.1000-3673.pst.2016.3045
中图分类号
学科分类号
摘要
Parallelization is the main technique to improve computing performance in power system computation. Different from computing speed ratio and efficiency as main evaluation method, the weighted elimination tree (WET) corresponding to ordering methods was modeled and analyzed in this paper. Its height, filling ratio, factorization complexity, forward-backward sweep complexity and balance properties were defined and their formation and calculation process were described. Through comparing values and distribution of different modeled elimination tree’s attributes formed from Tinney 1, Tinney 2 and Approximate Minimum Degree (AMD) ordering methods, a good choice suitable for fine-grained parallelization was selected. Finally, analytic hierarchy process (AHP) was used to calculate the weight of each attribute, and effectiveness of AHP values in different weighted elimination trees was verified, providing a reference for evaluation of ordering methods. © 2018, Power System Technology Press. All right reserved.
引用
收藏
页码:1316 / 1321
页数:5
相关论文
共 15 条
  • [1] Tinney W.F., Brandwajn V., Chan S.M., Sparse vector methods, IEEE Transactions on Power Apparatus and Systems, 104, 2, pp. 295-301, (1985)
  • [2] Zhang B., Sparse vector method with application to power system calculation, Proceedings of the CSEE, 7, 5, pp. 48-55, (1987)
  • [3] Xu D., Li Y., Wu Z., Application of sparse techniques in power system state estimation, Power System Technology, 31, 8, pp. 32-36, (2007)
  • [4] Jun Q.W., Anjan B., Parallel solution of large sparse matrix equations and parallel power flow, IEEE Transactions on Power System, 10, 3, pp. 1343-1349, (1995)
  • [5] Ji X., Wang C., A comparative study on parallel processing applied in power system, Power System Technology, 27, 4, pp. 21-26, (2003)
  • [6] Xu D., Li Y., Guo J., Et al., Elimination tree theory and its application in power flow calculation, Power System Technology, 31, 22, pp. 12-16, (2007)
  • [7] Zhao L., Donde V.D., Tourniel J.C., Et al., On limitation of traditional multi-core and potential of many-core processing architectures for sparse linear solvers used in large-scale power system applications, IEEE Power and Energy Society General Meeting., pp. 1-8, (2011)
  • [8] Zhou T., Yan Z., Tang C., Et al., A parallel algorithm for transient stability computing based on multi-processor technology, Automation of Electric Power Systems, 37, 8, pp. 70-75, (2013)
  • [9] Xia J., Yang F., Li J., Et al., Implementation of parallel power flow calculation based on GPU, Power System Protection and Control, 38, 18, pp. 100-103, (2010)
  • [10] Chen D., Li Y., Jiang H., Et al., A parallel power flow algorithm for large-scale grid based on stratified path trees and its implementation on GPU, Automation of Electric Power Systems, 38, 24, pp. 63-69, (2014)