DISHONEST GAUSS–NEWTON METHOD‐BASED POWER SYSTEM STATE ESTIMATION ON A GPU

[1]  Ganesh K. Venayagamoorthy,et al.  Convergence of the Fast State Estimation for Power Systems , 2017 .

[2]  Hadis Karimipour,et al.  Parallel relaxation-based joint dynamic state estimation of large-scale power systems , 2016 .

[3]  Venkata Dinavahi,et al.  Extended Kalman filter-based parallel dynamic state estimation , 2015, 2016 IEEE Power and Energy Society General Meeting (PESGM).

[4]  Ganesh K. Venayagamoorthy,et al.  Cellular computational networks - A scalable architecture for learning the dynamics of large networked systems , 2014, Neural Networks.

[5]  Georgios B. Giannakis,et al.  Distributed Robust Power System State Estimation , 2012, IEEE Transactions on Power Systems.

[6]  H. Poor,et al.  Fully Distributed State Estimation for Wide-Area Monitoring Systems , 2012, IEEE Transactions on Smart Grid.

[7]  George N Korres,et al.  A Distributed Multiarea State Estimation , 2011, IEEE Transactions on Power Systems.

[8]  A. G. Expósito,et al.  Power system state estimation : theory and implementation , 2004 .

[9]  A. Semlyen,et al.  Quasi-Newton Power Flow Using Partial Jacobian Updates , 2001, IEEE Power Engineering Review.

[10]  A. Monticelli,et al.  State estimation in electric power systems , 1999 .

[11]  Daniel Tylavsky,et al.  Parallel Newton type methods for power system stability analysis using local and shared memory multiprocessors , 1991 .

[12]  Fred C. Schweppe,et al.  Power System Static-State Estimation, Part I: Exact Model , 1970 .