Lead-lag Stabilizer Research Articles

Implementation of Modified Multi-Objective Particle Swarm Optimization to multi-machine power system stability

This paper addresses a coordinated wind turbine equipped with a doubly fed induction generator, photovoltaic plant, and a fractional lead-lag stabilizer to enhance the low-frequency oscillation (LFO) in response to their effects on the power system under load conditions. To achieve better stability in the power system, the DFIG wind turbine and PV plant are equipped with a power oscillation damper (POD) in a practical form by single-input signal output. Although power system stabilizers (PSSs) are the first choice offered for multimachine power system stability, they cannot guarantee power system stability with different types of power plants and their interconnections. To get the high-speed response and the least steady-state error, the fractional-order lead-lag stabilizer is suggested. To save the initial price of equipping all generators with the stabilizer, only the best locations are selected using a probabilistic method formulated in the frequency domain. The optimal tuning of FL-L and POD variables is formulated by the optimization problem, and the developed version of particle swarm optimization is used to solve it. Finally, the suggested coordinated controller is implemented in the MATLAB tool. Moreover, the suggested controller is compared to other available controllers by several indices. The simulation results show that the proposed controller can provide acceptable performance in low frequency oscillation in large scale power systems. According to the simulation results, the damping ratio was modified from 0.1343 to 0.5773. It leads to a reduction in the settlement time from 3.65 s to 2.14 s. Also, the proposed modified optimization algorithm makes a faster and better global and local search compared to other optimization algorithms.

Influence of Adaptive Power System Stabilizer on the Transient and Dynamic Performance of a Multimachine System

This paper presents a power system stabilizer (PSS) for improving the performance of a multimachine system when the system is subjected to different types of disturbances. An adaptive proportional-plus-derivative-plus-integral (PID) PSS is proposed in this paper. In this technique, the controller parameters (proportional, integral, and derivative gains) are not fixed but they are varying according to the system operating conditions. The derivative of power angle, error in output power, terminal voltage, and error in power angle are selected to be the input signals to the proposed stabilizer. A weighting factors are assigned to these signals to obtain the best performance characteristics of each machine. The obtained computer results from simulation study are compared with those of a conventional lead-lag stabilizer.

Robust design of static synchronous series compensator-based stabilizer for damping inter-area oscillations using quadratic mathematical programming

This paper presents a procedure for designing a supplementary damping stabilizer for a static synchronous series compensator (SSSC) in multi-machine power systems. The objective is to shift the lightly damped inter-area modes toward the prescribed stability region. A lead-lag stabilizer is used to demonstrate this technique, in which a particular measure of stabilizer gain is considered as an objective function. Constraints of the problem for phase-lead and lag structures are derived. The objective function with the constraints is formed as a quadratic mathematical programming problem. For robust design, the parameters of the stabilizer are calculated under various operating conditions. Two types of SSSC-based stabilizer have been presented and designed. Numerical results including eigenvalue analysis and the nonlinear simulations on the 4- and 50-machine power systems are presented to show the effectiveness of the proposed method.

Application of hybrid system control method for real-time power system stabilization

The electrical energy has become the major form of energy for end use consumption in today's world. There is always a need of making electric energy generation more economic and reliable. For proper operation, this large integrated system requires a stable operating condition. The power system is a dynamic system. It is constantly being subjected to small disturbances, which cause the generators relative angles to change [A.R. Messina, et al., An investigation on the use of power system stabilizers for damping inter-area oscillations in longitudinal power systems, IEEE Trans. Power Systems 13(2) (1997)]. For the interconnected system to be able to supply the load power demand when the transients caused by disturbance die out, a new acceptable steady state operating condition is reached [A. Soos, An optimal adaptive power system stabilizer, Ph.D. Thesis, University of Calgary, October 1997]. It is important that these disturbances do not drive the system to an unstable condition. The small signal stability problem is associated with modes of oscillations affecting either a single machine (local modes) or a small group of relatively closely connected machines or inter-area (global modes). This problem has got a very high attention in the last three decades and many types of controllers depend on classical and modern control theory have been developed by designing supplementary control signals to improve system damping [A.R. Messina, et al., An investigation on the use of power system stabilizers for damping inter-area oscillations in longitudinal power systems, IEEE Trans. Power Systems 13(2) (1997)]. In this research a novel power system stabilizer for damping both local and global modes of an interconnected system based on neuro fuzzy (hybrid) system is developed. NN-MISO (neural network multiple input single output) is proposed for local modes and Takagi–Sugneo's neuro-fuzzy system is proposed for global modes control [A. Soos, An optimal adaptive power system stabilizer, Ph.D. Thesis, University of Calgary, October 1997]. A comparative study between the proposed controller and most of widely used types of controllers (i.e. optimal controller and lead-lag stabilizer) are made towards damping electromechanical modes of oscillations. The results proved the potency of hybrid controller for power system stability control [D. Chakraborty, N.R. Pal, Integrated feature analysis and fuzzy rule-based system identification in a neuro-fuzzy paradigm, IEEE Trans. Systems Man Cybernet. 31(3) (2001) 391–400].

An Optimal Digital Stabilizer for Power System Stabilization

ABSTRACT The paper presents a new technique for the stabilization of power systems. The proposed technique is developed for designing the power system stabilizers, using the theory of optimal linear digital regulators. An advantage of the proposed digital stabilizer is that, in addition to provide damping effect to the system, it also has the capability of incorporating self-checking and diagnostic operation in case of malfunction. Thus higher reliability can be achieved by using a digital stabilizer. The dynamic responses following a step disturbance by digital simulation are obtained by means of two types of stabilizers: the conventional lead-lag power system stabilizer and the optimal digital stabilizer. Simulation results show that the optimal digital stabilizer yields better system dynamic performance than the lead-lag stabilizer in the sense of having greater damping in response to a step disturbance.