Abstract

Low frequency oscillations in large power systems may result in system instability under large disturbances. Power system stabilisers (PSS) play an effective role in damping these low frequency oscillations by injecting a modulating signal in the excitation loop of a synchronous machine. A new metaheuristic optimisation algorithm termed the sine cosine algorithm (SCA) was proposed for optimising PSS controller parameters to obtain an optimal solution with the damping ratio as an objective function. The SCA technique was examined on a single machine infinite bus (SMIB) system under distinct loading situations and matched with a moth flame optimisation technique and evolutionary programming to design a robust controller of PSS. The simulation was accomplished using a linearised mathematical model of the SMIB. The performance of a designed lead lag-controller of PSS was demonstrated using eigenvalue analysis with simulations, showing promising results. The dynamic performance was validated with respect to the damping ratio, the eigenvalue’s location in the s-plane and rotor angle deviation response to demonstrate system stability.

Highlights

  • In recent years, significant efforts have been undertaken to improve the dynamic stability of electrical power systems

  • This work presents a metaheuristic optimisation algorithm technique for fine-tuning a lead lag controller of Power system stabilisers (PSS) related to the angle stability of the single machine infinite bus (SMIB) system

  • Five methods based on EP, Moth Flame Optimisation (MFO) and sine cosine algorithm (SCA) computation algorithms for optimising the T1, T2 and Kstb parameters of the controller based on objective function as damping ratio were designed

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Summary

Introduction

Significant efforts have been undertaken to improve the dynamic stability of electrical power systems. The PSS lead lag controller, with the excitation system of the machine, controls the output power by delivering the supplementary synchronising torque, which is in phase with speed eccentricity to damp the required low frequency oscillations and improve power system stability [1,4]. PSS is the preferred method for improving power system stability by damping low frequency oscillations [5,6]; its design for multimachine by using local measurements [7]; and for the tuning of its parameters by combining transfer function–eigenfunction [8]. The use of PSS and FACTS devices with effective coordination amongst controllers is combined to damp both types of low frequency oscillations in an electrical power system: namely, local and inter modes. The proposed algorithm improved the power system stability by damping low frequency oscillations

Modelling of SMIB with AVR and PSS Damping Controllers
TW 1 T2
Objective
Evolutionary Programming Algorithm
Advantages of SCA over MFO and EP
Results and Discussion
Objective function Number of iterations
Conclusions
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