Artificial bee colony algorithm for inverter complex wave reduction under line-load variations

Abstract

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.

Application of mixed integer distributed ant colony optimization to the design of undamped single-tuned passive filters based harmonics mitigation

“…In the compensated system, the Thevenin's impedance for Kth harmonic is = + (9) and the load impedance for the Kth harmonic is…”

“…Different approaches optimal filter design for harmonic mitigations have been developed using an Adaptive Carrier Frequency Optimization [7], Non-Dominated Sorting Genetic Algorithm (NSGA-II) [8], Artificial Bee Colony [9], Adaptive Bacterial Foraging Optimization [10], Differential Evolution [11], Cuckoo Search Algorithm [12], Crow Search Algorithm [13] and Bat Algorithm [14].…”

ABC-WOA Optimization Strategy for UPQC Fuzzy PI Tuning

“…The operating principle and control strategy based on the dq0 transform are discussed in [16]. The authors are described different algorithms such as (ABC-DE-WOA), (ACWOA), ABC in [17][18][19]. In [20][21][22][23][24][25][26][27] authors are described different power quality mitigation techniques using conventional and AI based algorithms.…”

Optimal Design of C-Type Filter in Harmonics Polluted Distribution Systems

“…From the viewpoint of optimization methods for filter designing, research works in literature can be categorized into several classes, which include classical linear and nonlinear approaches [30], sequential quadratic programming [31], and metaheuristic methods. Various metaheuristic approaches for optimal filter design were represented using adaptive carrier frequency optimization [10], non-dominant genetic algorithm (NSGA-II) [32], bee colony [33], adaptive bacterial nutrition optimization [34], differential evolution [35], the cuckoo search algorithm [36], the crow search algorithm [37], the bat algorithm [38], and the Harris Hawks optimization algorithm (HHO) [29]. Generally, the complex problems can found by metaheuristic methods that offer solutions in accordance to constraints and non-constraints.…”

“…From the solution approach viewpoint, various techniques were proposed to find solutions, such as minimizing harmonic pollution, cost, or power loss, or power factor maximizing, or efficiency [29][30][31][32][33][34][35][36][37][38][39]. A comprehensive overview of the different objective functions (OFs) and constraints for passive filters design was introduced in [40][41][42].…”