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This paper describes the minimization of total harmonics in a single-phase sine wave voltage source inverter using a proportional–integral (PI) controller by estimating the optimized values of PI constants using an artificial bee colony (ABC) algorithm under line-load variations. The single-phase inverter is a non-linear load using power electronic components causing distortions in the load voltage and current wave patterns from the sinusoidal waveforms due to harmonics. A state variable analysis for the single-input–single-output (SISO) model of an inverter was developed by considering the switching sequence of a voltage source full bridge sine wave inverter. The ABC algorithm calculates the optimized values of the constants for the PI controller, thereby tuning the controller for reducing the total harmonics of an inverter. The MATLAB/Simulink tool and an experimental set-up were implemented, and their total harmonic distortion (THD) values were estimated. The outcomes of the proposed ABC scheme were compared with the previous results such as the PI algorithm, fuzzy logic controller, neuro-fuzzy controller, particle swarm optimization (PSO) and the bat algorithm. A practical example of the ABC algorithm is considered in the present harmonic reduction problem. From the simulation and experimental results using the ABC algorithm, it was observed that its harmonics levels were reduced considerably compared with IEEE and IEC standards. [ABSTRACT FROM AUTHOR]

A Queen-Bee Evolution-based tuning of a multi-machine power system stabilizer, which aims at enhancing the damping of the system over a wide range of operating conditions, is introduced in this paper. The basic components of this study are modeled by IEEE Model 1.1 and Heffron–Philips constants, considering the external resistance but neglecting the armature resistance. The problem is then formulated as a constrained multi-objective optimization problem. For investigation purposes, two different test systems are considered. The non-linear time domain simulations of the proposed power system stabilizer are compared with that based on the conventional approach power system stabilizer. The overall transfer function and the characteristic equation of the compensated system are derived from the single equivalent block diagram, and the nature of stability is verified by both frequency response analysis and Routh-Hurwitz (RH) criterion. Simulation results show that the proposed method motivates faster damping and leads to minimal overshoots in both speed and power angle deviations. [ABSTRACT FROM AUTHOR]

In this paper, a multi-objective design of the multi-machine Power System Stabilizer (PSS) using Ant Colony Optimization (ACO) is proposed. The fine tuning of PSS parameters problem is converted to an optimization problem that is resolved by an ACO-based dominant metaheuristic technique. The strength of the proposed ACO-based PSS is tested on two different multi-machine power systems under diverse operating conditions. The outcomes of the proposed ACOPSS are compared with the Conventional PSS, Genetic Local Search-based PSS, Chaotic Optimization-based PSS and Particle Swarm Optimization-based PSS (PSOPSS). From the simulation results it can be inferred that the ACOPSS reduces the settling time and maximum overshoot more than the other techniques. [ABSTRACT FROM AUTHOR]