Comparative Study of Evolutionary Computing Methods for Parameter Estimation of Power Quality Signals

2010 ◽  
Vol 1 (2) ◽  
pp. 28-59 ◽  
Author(s):  
V. Ravikumar Pandi ◽  
B. K. Panigrahi
Keyword(s):  
Particle Swarm Optimization ◽  
Power Quality ◽  
Harmonic Distortion ◽  
Particle Swarm ◽  
Computing Methods ◽  
Optimization Techniques ◽  
Swarm Optimization ◽  
Adaptive Particle Swarm Optimization ◽  
Quality Signal ◽  
Voltage Flicker

Recently utilities and end users become more concerned about power quality issues because the load equipments are more sensitive to various power quality disturbances, such as harmonics and voltage fluctuation. Harmonic distortion and voltage flicker are the major causes in growing concern about electric power quality. Power quality disturbance monitoring plays an important role in the deregulated power market scenario due to competitiveness among the utilities. This paper presents an evolutionary algorithm approach based on Adaptive Particle Swarm Optimization (APSO) to determine the amplitude, phase and frequency of a power quality signal. In this APSO algorithm the time varying inertia weight is modified as rank based, and re-initialization is used to increase the diversity. In this paper, to the authors highlight the efficacy of different evolutionary optimization techniques like classical PSO, Constriction based PSO, Clonal Algorithm (CLONALOG), Adaptive Bacterial Foraging (ABF) and the proposed Adaptive Particle Swarm Optimization (APSO) to extract different parameters like amplitude, phase and frequency of harmonic distorted power quality signal and voltage flicker.

Comparative Study of Evolutionary Computing Methods for Parameter Estimation of Power Quality Signals

2012 ◽  
pp. 99-129
Author(s):  
V. Ravikumar Pandi ◽  
B. K. Panigrahi
Keyword(s):  
Particle Swarm Optimization ◽  
Power Quality ◽  
Harmonic Distortion ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Adaptive Particle Swarm Optimization ◽  
Quality Signal ◽  
Power Quality Disturbance ◽  
Voltage Flicker ◽  
Evolutionary Optimization Techniques

Recently utilities and end users become more concerned about power quality issues because the load equipments are more sensitive to various power quality disturbances, such as harmonics and voltage fluctuation. Harmonic distortion and voltage flicker are the major causes in growing concern about electric power quality. Power quality disturbance monitoring plays an important role in the deregulated power market scenario due to competitiveness among the utilities. This paper presents an evolutionary algorithm approach based on Adaptive Particle Swarm Optimization (APSO) to determine the amplitude, phase and frequency of a power quality signal. In this APSO algorithm the time varying inertia weight is modified as rank based, and re-initialization is used to increase the diversity. In this paper, to the authors highlight the efficacy of different evolutionary optimization techniques like classical PSO, Constriction based PSO, Clonal Algorithm (CLONALOG), Adaptive Bacterial Foraging (ABF) and the proposed Adaptive Particle Swarm Optimization (APSO) to extract different parameters like amplitude, phase and frequency of harmonic distorted power quality signal and voltage flicker.

Fault Diagnosis of Grounding Grid Based on Self-Adaptive Particle Swarm Optimization

2013 ◽  
Vol 448-453 ◽  
pp. 1937-1940
Author(s):  
Wen Hao Lan ◽  
Yi Hui Zheng ◽  
Li Xue Li ◽  
Xin Wang ◽  
Gang Yao ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Fault Diagnosis ◽  
Minimum Energy ◽  
Particle Swarm ◽  
Optimization Techniques ◽  
New Method ◽  
Swarm Optimization ◽  
Adaptive Particle Swarm Optimization ◽  
Grounding Grid ◽  
Self Adaptive

To make effective fault diagnosis of grounding grid , a new method using Self-Adaptive Particle Swarm Optimization (SAPSO) is proposed. Firstly, the grounding grid can be handled as a resistive network to establish fault diagnosis equations. Then the objective function based on minimum energy principle is added to lower the ill-condition of diagnostic equation. Next, according to optimization techniques, a new method of SAPSO is proposed to solve the corrosion diagnosis equations. The method takes advantage of the high global searching ability of SAPSO to obtain the optimal solution to the diagnosis model. By means of the analysis of the simulation, the correctness and reliability of the method have been verified.

scholarly journals A Novel Multiobjective Control of DVR to Enhance Power Quality of Sensitive Load

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Sathish Babu Pandu ◽  
Kamaraj Nagappan
Keyword(s):  
Particle Swarm Optimization ◽  
Power Quality ◽  
Power Distribution ◽  
Distribution Systems ◽  
Harmonic Distortion ◽  
Particle Swarm ◽  
Quality Indices ◽  
Nonlinear Load ◽  
Swarm Optimization ◽  
Proportional Integral

The Dynamic Voltage Restorer (DVR) is one of the fast, flexible, and cost effective solutions available in compensating the voltage-related power quality problems in power distribution systems. In this paper is discussed how power quality enhancement of sensitive load is achieved by applying three versions of Autonomous Group Particle Swarm Optimization like AGPSO1, AGPSO2, and AGPSO3 for tuning the Proportional-Integral DVR controller under balanced and nonlinear load conditions. A novel multiobjective function is formulated to express the control performance of the system, which is quantified using three power quality indices such as Total Harmonic Distortion (THD), voltage sag index, and RMS voltage variation. The obtained results are compared with the Proportional-Integral (PI) controller tuned by Ziegler-Nichols (ZN) method and also by Simple Particle Swarm Optimization based PI controlled DVR. The proposed methodology has improved the performance in terms of the considered power quality indices and the simulation has been carried out in MATLAB/Simulink environment.

Design and experimental investigation on VL-MLI intended for half height (H-H) method to improve power quality using modified particle swarm optimization (MPSO) algorithm

2021 ◽  
pp. 1-18
Author(s):  
Satish Kumar Ramaraju ◽  
Thenmalar Kaliannan ◽  
Sheela Androse Joseph ◽  
Umadevi Kumaravel ◽  
Johny Renoald Albert ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Power Quality ◽  
Harmonic Distortion ◽  
Particle Swarm ◽  
Multilevel Inverter ◽  
Swarm Optimization ◽  
Modified Particle Swarm Optimization ◽  
Half Height ◽  
Field Programmable ◽  
Modulation Methods

A Voltage lift performance is an excellent role to DC/DC conversion topology. The Voltage Lift Multilevel Inverter (VL-MLI) topology is suggested with minimal number of components compared to the conventional multilevel inverter (MLI). In this method, the Modified Particle Swarm Optimization (MPSO) conveys a primary task for the VL-MLI using Half Height (H-H) method, it determine the required optimum switching angles to eliminate desired value of harmonics. The simulation circuit for fifteen level output uses single switch voltage-lift inverter fed with resistive and inductive loads (R & L load). The power quality is developed by voltage-lift multilevel inverter with minimized harmonics under the various Modulation Index (MI) while varied from 0.1 up to 1. The circuit is designed in a Field Programmable Gate Array (FPGA), which includes the MPSO rules for fast convergence to reduce the lower order harmonics and finds the best optimum switching angle values. To report this problem the H-H has implemented with MPSO to reduce minimum Total Harmonic Distortion (THD) for simulation circuit using Proteus 7.7 simulink tool. Due to the absence of multiple switches, filter and inductor element exposes for novelty of the proposed system. The comparative analysis has been carried-out with existing optimization and modulation methods.

scholarly journals Improving DFT-Based Image Watermarking Using Particle Swarm Optimization Algorithm

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1795
Author(s):  
Manuel Cedillo-Hernandez ◽  
Antonio Cedillo-Hernandez ◽  
Francisco J. Garcia-Ugalde
Keyword(s):  
Fourier Transform ◽  
Particle Swarm Optimization ◽  
Discrete Fourier Transform ◽  
Image Watermarking ◽  
Particle Swarm ◽  
Optimization Techniques ◽  
Robust Watermarking ◽  
Swarm Optimization ◽  
General Terms ◽  
Operation Parameters

Robust digital image watermarking is an information security technique that has been widely used to solve several issues related mainly with copyright protection as well as ownership authentication. In general terms, robust watermarking conceals a small signal called a “watermark” in a host image in a form imperceptible to human vision. The efficiency of conventional robust watermarking based on frequency domain depend directly on the results of performance in terms of robustness and imperceptibility. According to the application scenario and the image dataset, it is common practice to adjust the key parameters used by robust watermarking methods in an experimental form; however, this manual adjustment may involve exhaustive tasks and at the same time be a drawback in practical scenarios. In recent years, several optimization techniques have been adopted by robust watermarking to allowing adjusting in an automatic form its key operation parameters, improving thus its performance. In this context, this paper proposes an improved robust watermarking algorithm in discrete Fourier transform via spread spectrum, optimizing the key operation parameters, particularly the amounts of bands and coefficients of frequency as well as the watermark strength factor using particle swarm optimization in conjunction with visual information fidelity and bit correct rate criteria. Experimental results obtained in this research show improved robustness against common signal processing and geometric distortions, preserving a high visual quality in color images. Performance comparison with conventional discrete Fourier transform proposal is provided, as well as with the current state-of-the-art of particle swarm optimization applied to image watermarking.

scholarly journals Asteroid Rendezvous Mission Design Using Multiobjective Particle Swarm Optimization

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Ya-zhong Luo ◽  
Li-ni Zhou
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Optimization Techniques ◽  
Mission Design ◽  
Trajectory Design ◽  
Time Transfer ◽  
Pareto Solution ◽  
Swarm Optimization ◽  
Multiobjective Particle Swarm Optimization ◽  
Asteroid Mission

A new preliminary trajectory design method for asteroid rendezvous mission using multiobjective optimization techniques is proposed. This method can overcome the disadvantages of the widely employed Pork-Chop method. The multiobjective integrated launch window and multi-impulse transfer trajectory design model is formulated, which employes minimum-fuel cost and minimum-time transfer as two objective functions. The multiobjective particle swarm optimization (MOPSO) is employed to locate the Pareto solution. The optimization results of two different asteroid mission designs show that the proposed approach can effectively and efficiently demonstrate the relations among the mission characteristic parameters such as launch time, transfer time, propellant cost, and number of maneuvers, which will provide very useful reference for practical asteroid mission design. Compared with the PCP method, the proposed approach is demonstrated to be able to provide much more easily used results, obtain better propellant-optimal solutions, and have much better efficiency. The MOPSO shows a very competitive performance with respect to the NSGA-II and the SPEA-II; besides a proposed boundary constraint optimization strategy is testified to be able to improve its performance.

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