A Nonlinear H-Infinity Control Approach to Stabilization of Distributed Synchronous Generators

This paper proposes a new nonlinear H-infinity control method for stabilization and synchronization of distributed interconnected synchronous generators. At first stage, local linearization of the distributed generators’ model is performed round its present operating point. The approximation error that is introduced to the linearized model is due to truncation of higher-order terms in the performed Taylor series expansion and is represented as a disturbance. The control problem is now formulated as a min–max differential game in which the control input tries to minimize the state vector's tracking error while the disturbances affecting the model try to maximize it. Using the linearized description of the distributed generators’ dynamics, an H-infinity feedback controller is designed through the solution of a Riccati equation at each step of the control algorithm. The inherent robustness properties of H-infinity control assure that the disturbance effects will be eliminated and the state variables of the individual power generators will converge to the desirable setpoints. The proposed method, stands for a reliable solution to the problem of nonlinear control and stabilization for interconnected synchronous generators. It is also a novel approach, comparing to control of synchronous generators based on global linearization methods. Its efficiency is further confirmed through simulation experiments.

[1]  P. Siano,et al.  A New Non-linear H-infinity Feedback Control Approach for Three-phase Voltage Source Converters , 2016 .

[2]  Yao Zhang,et al.  A robust decentralized load frequency controller for interconnected power systems. , 2012, ISA transactions.

[3]  Gerasimos Rigatos,et al.  Fuzzy model validation using the local statistical approach , 2009, Fuzzy Sets Syst..

[4]  Magdi S. Mahmoud,et al.  H/sub /spl infin//-controllers for linearised time-delay power systems , 2000 .

[5]  Gerasimos Rigatos,et al.  Nonlinear Control and Filtering Using Differential Flatness Approaches , 2015 .

[6]  Michèle Basseville,et al.  Detection of Abrupt Changes: Theory and Applications. , 1995 .

[7]  Xiaorong Xie,et al.  Simultaneously tuning decentralized nonlinear optimal excitation controllers in multimachine power systems , 2005 .

[8]  Gerasimos Rigatos,et al.  Extended Kalman filtering for fuzzy modelling and multi-sensor fusion , 2007 .

[9]  Gerasimos Rigatos Intelligent Renewable Energy Systems: Modelling and Control , 2016 .

[10]  Gerasimos G. Rigatos,et al.  Modelling and Control for Intelligent Industrial Systems - Adaptive Algorithms in Robotics and Industrial Engineering , 2011, Intelligent Systems Reference Library.

[11]  M. J. Hossain,et al.  Robust nonlinear excitation controller design for multimachine power systems , 2014, 2014 IEEE PES General Meeting | Conference & Exposition.

[12]  Alessandro Astolfi,et al.  Improving transient stability of multi-machine power systems: Synchronization via immersion of a pendular system , 2011, Proceedings of the 2011 American Control Conference.

[13]  Qiang Lu,et al.  Nonlinear decentralized disturbance attenuation excitation control via new recursive design for multi-machine power systems , 2002, 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309).

[14]  P. Siano,et al.  PMSG sensorless control with the use of the derivative-free nonlinear Kalman filter , 2013, 2013 International Conference on Clean Electrical Power (ICCEP).

[15]  Ufuk Topcu,et al.  Design and Stability of Load-Side Primary Frequency Control in Power Systems , 2013, IEEE Transactions on Automatic Control.

[16]  Steven H. Low,et al.  Optimal decentralized primary frequency control in power networks , 2014, 53rd IEEE Conference on Decision and Control.

[17]  Daizhan Cheng,et al.  Nonlinear decentralized controller design for multimachine power systems using Hamiltonian function method , 2002, Autom..

[18]  Narri Yadaiah,et al.  Linearisation of multi-machine power system: Modeling and control – A survey , 2007 .

[19]  Romeo Ortega,et al.  A “Globally” Convergent Controller for Multi-Machine Power Systems Using Structure-Preserving Models , 2009, IEEE Transactions on Automatic Control.

[20]  Josep M. Guerrero,et al.  Advanced Control Architectures for Intelligent Microgrids—Part I: Decentralized and Hierarchical Control , 2013, IEEE Transactions on Industrial Electronics.

[21]  Xiangjie Liu,et al.  Robust distributed MPC for load frequency control of uncertain power systems , 2016 .

[22]  Srdjan S. Stankovic,et al.  DECENTRALIZED H∞ DESIGN OF AUTOMATIC GENERATION CONTROL , 2002 .

[23]  Shahab Mehraeen,et al.  Modeling and Nonlinear Optimal Control of Weak/Islanded Grids Using FACTS Device in a Game Theoretic Approach , 2016, IEEE Transactions on Control Systems Technology.

[24]  P. Siano,et al.  Derivative‐Free Nonlinear Kalman Filtering for PMSG Sensorless Control , 2013 .

[25]  Bo Guo,et al.  Optimal operation of a smart residential microgrid based on model predictive control by considering uncertainties and storage impacts , 2015 .

[26]  Q. Henry Wu,et al.  Decentralized nonlinear adaptive control for multimachine power systems via high-gain perturbation observer , 2004, IEEE Transactions on Circuits and Systems I: Regular Papers.

[27]  Xin Wang,et al.  Robust H∞ control of time delayed power systems , 2015 .

[28]  Patrice Wira,et al.  Nonlinear H-infinity feedback control for asynchronous motors of electric trains , 2015 .

[29]  Pierluigi Siano,et al.  Sensorless Control of Distributed Power Generators With the Derivative-Free Nonlinear Kalman Filter , 2014, IEEE Transactions on Industrial Electronics.

[30]  Yi Guo,et al.  Nonlinear decentralized control of large-scale power systems , 2000, Autom..

[31]  Larry E. Banta,et al.  Real-time management solutions for a smart polygeneration microgrid , 2016 .

[32]  Daizhan Cheng,et al.  Dissipative Hamiltonian realization and energy-based L2-disturbance attenuation control of multimachine power systems , 2003, IEEE Trans. Autom. Control..

[33]  Sebastien Gros,et al.  A distributed algorithm for NMPC-based wind farm control , 2014, 53rd IEEE Conference on Decision and Control.

[34]  J. Mauricio,et al.  Multi-machine power system stability improvement using an observer-based nonlinear controller , 2012 .

[35]  Guang Li,et al.  Model predictive control of sea wave energy converters – Part II: The case of an array of devices , 2014 .

[36]  Jianming Lian,et al.  Decentralized control of multimachine power systems , 2009, 2009 American Control Conference.

[37]  Daizhan Cheng,et al.  Nonlinear decentralized saturated controller design for power systems , 2003, IEEE Trans. Control. Syst. Technol..