INTELLIGENT CONTROLLER BASED IMPROVED FAULT RIDE-THROUGH CAPABILITY OF HVDC SYSTEM CONNECTED TO WEAK AC GRID

In the paper, a novel HVDC transmission system operating with weak ac system has been modeled with speed and precision & analyses the control strategy & performance of system, which is controlled using fuzzy. The system can feed a weak or even dead network under fluctuations and big variations of the input power. The fuzzy logic-based control of the system helps to optimize the efficiency of the link under various disturbances. This model provides the basic building blocks found in a typical HVDC system that can be used to build models for individual users own models. The specific contributions, in this paper are that a DQ- type of phase-locked-loop for synchronizing the firing pulses to the HVDC converter has been presented. This gate-firing unit is capable of a providing a clean sinusoidal synchronizing voltage from a polluted and harmonic distorted commutation voltage. The simulations based on PSCAD/EMTDC show that proposed fuzzy logic based HVDC system can operate steadily, has the capability to restore steadily when short circuit fault occurs, and obvious in advantages.

[1]  Bimal K. Bose,et al.  Modern Power Electronics and AC Drives , 2001 .

[2]  A. Roli.  Artificial Neural Networks , 2012, Lecture Notes in Computer Science.

[3]  Francesco Profumo,et al.  Self-Tuning Position/Speed Fuzzy Logic Controllers for Torque Controlled Drives , 1995 .

[4]  Marcelo Simoes.  Introduction to Fuzzy Control , 2003 .

[5]  V. Dinavahi,et al.  Detailed modeling of CIGRE HVDC benchmark system using PSCAD/EMTDC and PSB/SIMULINK , 2006, IEEE Transactions on Power Delivery.

[6]  R. W. Menzies,et al.  Effect of DC capacitance of a STATCON on the dynamic performance at a weak HVDC terminal , 1995, IEEE WESCANEX 95. Communications, Power, and Computing. Conference Proceedings.

[7]  T. F. Garrity,et al.  Measurement of harmonic currents and evaluation of the DC filter performance of the New England-Hydro-Quebec Phase I HVDC project , 1989 .

[8]  T. K. Bandopadhyaya,et al.  Journal of Theoretical and Applied Information Technology , 2022 .

[9]  Dr. R. C. Bansal,et al.  Some Issues Related to Power Generation Using Wind Energy Conversion Systems: An Overview , 2005 .

[10]  Bimal K. Bose,et al.  Expert system, fuzzy logic, and neural network applications in power electronics and motion control , 1994, Proc. IEEE.

[11]  M. Sublich,et al.  Impact of stray capacitance on HVDC harmonics , 1989 .

[12]  Herbert Werner,et al.  Robust control of a VSC HVDC terminal attached to a weak AC system , 2003, Proceedings of 2003 IEEE Conference on Control Applications, 2003. CCA 2003..

[13]  Vinod Kumar.  Hybrid Controller based Intelligent Speed Control of Induction Motor , 2007 .

[14]  Bimal K. Bose,et al.  Applications of fuzzy logic in the estimation of power electronic waveforms , 1993, Conference Record of the 1993 IEEE Industry Applications Conference Twenty-Eighth IAS Annual Meeting.

[15]  B.K. Bose,et al.  Neural network based estimation of feedback signals for a vector controlled induction motor drive , 1994, Proceedings of 1994 IEEE Industry Applications Society Annual Meeting.

[16]  Ramesh C. Bansal,et al.  Bibliography on the fuzzy set theory applications in power systems (1994-2001) , 2003 .

[17]  H. A. Othman,et al.  Analytical modeling of thyristor-controlled series capacitors for SSR studies , 1996 .

[18]  Jerry Avorn.  Technology , 1929, Nature.

[19]  Kumpati S. Narendra,et al.  Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.

[20]  B. Yegnanarayana,et al.  Artificial Neural Networks , 2004 .

[21]  Vinod Kumar,et al.  FUZZY LOGIC BASED LIGHT LOAD EFFICIENCY IMPROVEMENT OF MATRIX CONVERTER BASED WIND GENERATION SYSTEM , 2007 .

[22]  Richard D. Braatz,et al.  On the "Identification and control of dynamical systems using neural networks" , 1997, IEEE Trans. Neural Networks.

[23]  L.E. Borges da Silva,et al.  Adaptive fuzzy techniques for slip-recovery drive control , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.