Pi Power System Controller: Eigenstructure – Based Design and Sensitivities

Significant advances in power system control design techniques that can take into consideration plants linearized around a number of operating conditions. Most of these techniques are based on eigenspectrum analysis which has numerous advantages. A wealth of applications of eigenstructure assignment are available in the literature and showed that new applications have been found and parametric solution of eigenspectrum assignment can be used successfully to design feedback controllers. The use of supplementary controller added to the automatic voltage regulator (AVR) is a practical effective way to supply additional positive damping to system oscillations via power system stabilizers. The present paper utilizes eigenspectrum analysis in the practical design of proportional integral (PI) type power system stabilizers, in order to achieve good steady state as well as transient response characteristics. Eigenspectrum analysis is attractive since it takes into account freedom in determining feedback gains and provides the frequencies and the damping at each frequency for the entire system in a single calculation. Moreover sensitivity of eigenvalues and eigenvectors with respect to parameter variations are assessed so as to provide information to improve setting parameters for power system damping and stability, without ignoring the operating conditions. The results of eigenvalue/eigenvector sensitivity are tangible for analysis with a wide range of parameter variations and is presented through the right and left eigenvectors of the system matrix and also through Taylor series analysis.

Robust Design of Power System Stabilizers Using Improved Harris Hawk Optimizer for Interconnected Power System

In this present work, a new metaheuristic method called a Harris hawk optimizer (HHO) is applied to achieve the optimal design of a power system stabilizer (PSS) in a multimachine power system. Several well-known chaos maps are incorporated into the HHO to form a chaotic HHO (CHHO) with the aim of improving static operators and enhancing global searching. To assess the CHHO performance, exhaustive comparison studies are made between anticipated chaotic maps in handling unconstrained mathematical problems. At this moment, The PSS design problem over a wide permutation of loading conditions is formulated as a non-linear optimization problem. The adopted objective function defines the damping ratio of lightly damped electromechanical modes subject to a set of constraints. The best PSS parameters are generated by the proposed CHHO. The applicability of the proposed CHHO based on PSS is examined and demonstrated on a 10-generator and 39-bus multimachine power system model. The performance assessments of the CHHO results are realized by a comparative study with HHO through extensive simulations along with further eigenvalue analysis to prove its efficacy. The simulation results convincingly demonstrate the high performance of the proposed CHHO-PSS under various operating scenarios.

Optimal Coordination of PSS and SSSC Controllers in Power System Using Ant Colony Optimization Algorithm

Volatility leads to disruption in synchronism between generators of a continuous system. The frequency of the volatility is usually between a few tenths of Hz to several Hz. This volatility is sometimes divided into two types, local and interregional. Local volatility is the low-frequency volatility of a power plant unit or units of a power plant relative to the grid whereas interregional volatility is the volatility of the units of one area relative to the units of another area. The worst kind of low-frequency volatility occurs when the power system in a region has a short three-phase connection to the earth, creating a complete instability of the grid and operating protective systems. One of the ways to improve the dynamic stability and steady-state of the power system is to use power system stabilizers and FACTS devices in the system. In this paper, the stabilization of the power system stabilizers (PSSs) and SSSC is done using the ant colony algorithm. Studies on a four-machine system with the three-phase error were performed in two scenarios and finally compared with the PSO method. The simulation results show that the proposed method produced more accurate performance.

Local Search-based Non-dominated Sorting Genetic Algorithm for Optimal Design of Multimachine Power System Stabilizers

This study presents a metaheuristic method for the optimum design of multimachine Power System Stabilizers (PSSs). In the proposed method, referred to as Local Search-based Non-dominated Sorting Genetic Algorithm (LSNSGA), a local search mechanism is incorporated at the end of the second version of the non-dominated sorting genetic algorithm in order to improve its convergence rate and avoid the convergence to local optima. The parameters of PSSs are tuned using LSNSGA over a wide range of operating conditions, in order to provide the best damping of critical electromechanical oscillations. Eigenvalue-based objective functions are employed in the PSS design process. Simulation results based on eigenvalue analysis and nonlinear time-domain simulation proved that the proposed controller provided competitive results compared to other metaheuristic techniques.