Mobile QR Code QR CODE : The Transactions of the Korean Institute of Electrical Engineers


A. R. Bergen, V. Vittal, 2000, Power System Analysis, 2nd ed., Prentice HallGoogle Search
H. Saadat, 2002, Power System Analysis, 2nd ed., McGraw-HillGoogle Search
G. W. Kim, S. H. Hyun, Feb 2005, Power System Analysis Using MATLAB 1, UUPGoogle Search
J. D. Glover, T. J. Overbye, M.S. Sarma, 2016, Power System Analysis & Design, 6th ed., Cengage LearningGoogle Search
S. R. Nam, J. K. Hong, S. H. Kang, J. K. Park, 2004, Analysis of characteristic frequency along fault distance on a transmission line, KIEE Trans., Vol. 53a, No. 8, pp. 432-437Google Search
D. G. Lee, S. H. Kang, 2010, Distance relaying algorithm using a DFT-based modified phasor estimation method, KIEE Trans., Vol. 59, No. 8, pp. 1360-1365DOI
A. P. Sakis Meliopoulos, G. J. Cokkinides, P. Myrda, Y. Liu, F. Rui, L. Sun, R. Huang, Z. Tan, 2017, Dynamic state estimation-based protection: Status and Promise, IEEE Trans. Power Delivery, Vol. 32, No. 1, pp. 320-330DOI
S. Paudyal, G. Ramakrishna, M. S. Sachdev, 2010, Application of equal area criterion conditions in the time domain for out-of-step protection, IEEE Trans. Power Delivery, Vol. 25, No. 2, pp. 600-609DOI
E. Farantatos, R. Huang, G. J. Cokkinides, Aug 2016, A predictive generator out-of-step protection and transient stability monitoring scheme enabled by a distributed dynamic state estimator, IEEE Trans. Power Del., Vol. 31, No. 4, pp. 1826-1835DOI
Y. Cui, R. G. Kavasseri, S. M. Brahma, 2017, Dynamic state estimation assisted out-of-step detection for generators using angular difference, IEEE Trans. Power Delivery, Vol. 32, No. 3, pp. 1441-1449DOI
A. Levant, 1998, Robust exact differentiation via sliding mode technique, Automatica, Vol. 34, No. 3, pp. 379-384DOI
Y. I. Son, I. H. Kim, May 2010, A robust state observer using multiple integrators for multivariable LTI systems, IEICE Trans. Fundamentals, Vol. E93-A, No. 5, pp. 981-984DOI
W. H. Chen, J. Yang, L. Guo, S. Li, 2016, Disturbance observer-based control and related methods-An overview, IEEE Trans. Ind. Electron., Vol. 63, No. 2, pp. 1083-1095DOI
H. Shim, G. Park, Y. Joo, J. Back, N. H. Jo, 2016, Yet another tutorial of disturbance observer: robust stabilization and recovery of nominal performance, Control Theory and Technology, Vol. 14, No. 3, pp. 237-249DOI
J. Chang, G. N. Taranto, J. H. Chow, 1997, Dynamic state estimation using a nonlinear observer for optimal series- capacitor switching control, Int. J. Electrical Power & Energy Systems, Vol. 19, No. 7, pp. 441-447DOI
R. S. Sutton, Aug 1991, Dyna, an integrated architecture for learning, planning, and reacting, ACM SIGART Bulletin, Vol. 2, No. 4, pp. 160-163DOI
C. J. C. H. Watkins, P. Dayan, May 1992, Q-learning, Machine Learning, Vol. 8, No. 3-4, pp. 279-292DOI
R. S. Sutton, A. G. Barto, 1998, Reinforcement Learning: An Introduction, MIT pressGoogle Search
S. Russel, P. Norvig, Jan 2003, Artificial Intelligence: A Modern Approach, Prentice HallGoogle Search
A. Karami, 2008, Radial basis function neural network for power system transient energy margin estimation, Journal of Electrical Engineering & Technology, Vol. 3, No. 4, pp. 468-475DOI
M. J. Reddy, D. K. Mohanta, 2008, Adaptive-neuro-fuzzy inference system approach for transmission line fault classification and location incorporating effects of powr swings, IET Generation, Transmission & Distribution, Vol. 2, No. 2, pp. 235-244DOI
X. Glorot, Y. Bengio, 2010, Understanding the difficulty of training deep feedforward neural networks, in Proc. of the 13th Int. Conf. Artificial Intelligence and Statistics, Vol. 9, pp. 249-256Google Search
W. Yao, J. Fang, P. zhao, S. Liu, J. Wen, S. Wang, 2013, TCSC nonlinear adaptive damping controller design based on RBF nerual network to enhance power system stability, Journal of Electrical Engineering & Technology, Vol. 8, No. 2, pp. 252-261DOI
D. P. Kingma, J. Ba, 2015, Adam: a method for stochastic optimization, ICLRGoogle Search
V. Mnih, K. Kavukcuoglu, D. Silver, A. A. Rusu, J. Veness, Marc G. Bellemare, A. Graves, M. Riedmiller, Andreas K. Fidjeland, G. Ostrovski, S. Petersen, C. Beattie, A. Sadik, I. Antonoglou, H. King, D. Kumaran, D. Wierstra, S. Legg, D. Hassabis, Feb 2015, Human-level control though deep reinforcement learning, Nature, Vol. 518, No. , pp. 529-533DOI
D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. V. D. Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, D. Hassabis, Jan 2016, Mastering the game of Go with deep neural networks and tree search, Nature, 529, pp. 484-489DOI
S. Das, R. Dubey, B. K. Panigrahi, S. R. Samantaray, 2017, Secured zone-3 protection during power swing and voltage instability: an online approach, IET Generation, Trans- mission & Distribution, Vol. 11, No. 2, pp. 437-446DOI
A. Juliani, 2017, Simple Reinforcement Learning with Tensorflow, Hanbit Publishing NetworkGoogle Search