Application of BFNN in power flow calculation in smart distribution grid

Neurocomputing

Volumn 125, Issue , 2014, Pages 148-152

  Sun, Qiuye ^a   Yu, Yunxia ^a   Luo, Yanhong ^a   Liu, Xinrui ^a  

^a NORTHEASTERN UNIVERSITY   (China)

Author keywords

BFNN; Breadth first search plan; Power flow

Indexed keywords

APPROXIMATION EFFECTS; BFNN; BREADTH-FIRST SEARCH; DISTRIBUTION SYSTEMS; EXCITATION FUNCTION; POWER FLOW CALCULATIONS; POWER FLOWS; SMART DISTRIBUTION GRIDS;

APPROXIMATION ALGORITHMS; NEURONS;

LEARNING ALGORITHMS;

ACCURACY; ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BACK FORWARD SWEEP NEURAL NETWORK; BREADTH FIRST SEARCH PLAN; CALCULATION; ELECTRIC POTENTIAL; ELECTRICAL PARAMETERS; EXCITATION; MATHEMATICAL MODEL; POWER FLOW CALCULATION; POWER SUPPLY; PRIORITY JOURNAL; VALIDATION STUDY;

EID: 84888027410     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2012.07.044     Document Type: Article

References (13)

1. A. Rathinam, S. Padmini, V. Ravikumar, Application of supervised learning artificial neural networks [CPNN, BPNN] for solving power flow problem, in: ICTES, 2007, pp. 156-160.
2. Bose B.K. Neural network applications in power electronics and motor drives-an introduction and perspective. IEEE Trans. Ind. Electron. 2007, 54(1):14-33.
3. M. Saradarzadeh, S. Farhangi, J.L. Schanen, P.-O. Jeannin, D. Frey, The benefits of looping a radial distribution system with a power flow controller, in: IEEE PECon, 2010, pp. 723-728.
4. A.C. Santos, M. Nanni, M.R. Mansour, A. Delbem, J. London, N.G. Bretas, A power flow method computationally efficient for large-scale distribution systems, in: IEEE TDCELA, 2008, pp. 1-6.
5. Zhang H.G., Huang W., Wang Z.L. Adaptive synchronization between two different chaotic systems with unknown parameters. Phys. Lett. A 2006, 350(5-6):363-366.
6. Zhang H.G., Quan Y.B. Modeling, identification, and control of a class of nonlinear systems. IEEE Trans. Fuzzy Syst. 2001, 9(2):349-354.
7. Zhang H.G., Wang Z.S., Liu D.R. Robust stability analysis for interval Cohen-Grossberg neural networks with unknown time-varying delays. IEEE Trans. Neural Network 2008, 19(11):1942-1955.
8. V.N. Kamalesh, S.K. Srivatsa, Numbering of nodes in a communication network, in: World Congress on Engineering and Computer Science, 2008, pp. 86-93.
9. Zhang H.G., Luo Y.H., Liu D.R. Neural-network-based near-optimal control for a class of discrete-time affine nonlinear systems with control constraints. IEEE Trans. Neural Networks 2009, 20(9):1490-1503.
10. J. Ma, G.Y. Xu, S.H. Wang, X. Lin, Calculation and analysis for line losses in distribution networks, in: IEEE PSTCon, vol. 4, 2002, pp. 2537-2541.
11. D.R. Liu, D. Wang, D.B. Zhao, Adaptive dynamic programming for optimal control of unknown nonlinear discrete-time systems, in: 2011 IEEE ADPRL, 2011, pp. 242-249.
12. Saeedi S., Paull L., Trentini M., Li H. Neural network-based multiple robot simultaneous localization and mapping. IEEE Trans. Neural Networks 2011, 22(12):2376-2387.
13. Zhang H.G., Wang Z.S., Liu D.R. Global asymptotic stability of recurrent neural networks with multiple time-varying delays. IEEE Trans. Neural Networks 2008, 19(5):855-873.