Improving power system damping using a combination of optimal control theory and differential evolution algorithm.

This paper presents a novel control strategy to improve the damping capability of sub-synchronous oscillations by tuning of Linear Quadratic Regulator (LQR) optimally in order to reduce the fluctuations in the power system. The proposed model includes the coordination of Power System Stabilizer (PSS) and Thyristor-Controlled Series Capacitors (TCSC) in combination with LQR controllers which is formulated as an optimal control problem. The problem is formulated as a linear regulator problem and then the Differential Evolution (DE) algorithm is utilized to optimize the proposed controlling parameters. Several cases have been studied to show the efficiency of the proposed strategy. Obtained results from a case study on a typical generator demonstrated that the proposed method has the best response and quickest function among conventional controller systems. Moreover, the coordination of the LQR with the other control systems, as an optimal linear regulator problem in order to damp system oscillations provides robust stability for optimizing system performance index. Besides, the flexibility and usability of the LQR controller guarantee the stability of the system to cope with the oscillations.

[1]  Mohammad Hasan Raouf,et al.  Power System Damping Using Hierarchical Fuzzy Multi- Input PSS and Communication Lines Active Power Deviations Input and SVC , 2014 .

[2]  Daniela Zaharie,et al.  Influence of crossover on the behavior of Differential Evolution Algorithms , 2009, Appl. Soft Comput..

[3]  E.V. Larsen,et al.  Applying Power System Stabilizers Part III: Practical Considerations , 1981, IEEE Transactions on Power Apparatus and Systems.

[4]  I. Kamwa,et al.  Joint improvement of system loadability and stability through a multi-stage planning of a UPFC with a PMU-based supplementary damping control , 2013, 2013 IEEE Power & Energy Society General Meeting.

[5]  A. Feliachi,et al.  Online Learning Neural Network based PSS with Adaptive Training Parameters , 2007, 2007 IEEE Power Engineering Society General Meeting.

[6]  Amin Safari,et al.  A robust PSSs design using PSO in a multi-machine environment , 2010 .

[7]  Gayadhar Panda,et al.  Robust nested loop control scheme for LCL-filtered inverter-based DG unit in grid-connected and islanded modes , 2018 .

[8]  Mohamed E. El-Hawary,et al.  Linear quadratic regulator design for power system stabilizer using biogeography based optimization method , 2016, 2016 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE).

[9]  Masahiko Amano,et al.  Experimental verification of multi-input PSS with reactive power input for damping low frequency power swing , 1999 .

[10]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[11]  Reza Noroozian,et al.  PSS and STATCOM controller design for damping power system oscillations using fuzzy control strategies , 2010, 2010 18th Iranian Conference on Electrical Engineering.

[12]  K. Vaisakh,et al.  Design of a decentralized non-linear controller for transient stability improvement under symmetrical and unsymmetrical fault condition: A comparative analysis with SSSC , 2009, 2009 IEEE/PES Power Systems Conference and Exposition.

[13]  H. H. Happ,et al.  Power System Control and Stability , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[14]  Jie Jia,et al.  Optimal Feedback Stabilization of Input-Saturated Systems Subject to Structural Uncertainty and Disturbance for Lower Limb Exoskeleton's Motion Control , 2018 .

[15]  E. L. Miotto,et al.  Analysis of impacts of PSS controllers and TCSC FACTS devices at dynamic stability of a multimachine system power , 2010, 2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America (T&D-LA).

[16]  Yong He,et al.  Optimal control in microgrid using multi-agent reinforcement learning. , 2012, ISA transactions.

[17]  Jing Lei,et al.  Performance recovery of regional input-to-state stabilization by sampled-data output feedback control for nonlinear systems in the presence of disturbance , 2017, Eur. J. Control.

[18]  Jih-Gau Juang,et al.  A hybrid intelligent controller for a twin rotor MIMO system and its hardware implementation. , 2011, ISA transactions.

[19]  A. Al-Hinai.  Dynamic stability enhancement using Genetic Algorithm Power System Stabilizer , 2010, 2010 International Conference on Power System Technology.

[20]  Donald E. Kirk,et al.  Optimal control theory : an introduction , 1970 .

[21]  Mukhtar Fatihu Hamza,et al.  COMPARISON OF GA AND LQR TUNING OF STATIC VAR COMPENSATOR FOR DAMPING OSCILLATIONS , 2012 .

[22]  Laszlo Gyugyi,et al.  Understanding FACTS: Concepts and Technology of Flexible AC Transmission Systems , 1999 .