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.

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.

scholarly journals Penurunan Total Harmonic Distortion Pada Penguat Audio Kelas D Menggunakan Metode MQPSO

2019 ◽  
Vol 4 (3) ◽  
pp. 103
Author(s):  
Moh Uhida Subhan ◽  
Ponco Siwindarto ◽  
Bambang Siswojo
Keyword(s):  
Particle Swarm Optimization ◽  
Harmonic Distortion ◽  
Particle Swarm ◽  
Total Harmonic Distortion ◽  
Swarm Optimization ◽  
Proportional Integral ◽  
Modified Particle Swarm Optimization

Penguat audio kelas D merupakan penguat audio switching yang mempunyai efisiensi tinggi dibanding penguat audio konvensional (analog). Dalam kondisi ideal, penguat ini mempunyai efisiensi lebih dari 90%. Permasalahan umum yang terjadi pada penguat ini adalah distorsi karena bekerja secara non linier. Sebuah kompensator Proportional Integral (PI) digunakan sebagai filter analog pada umpan balik negatif dibandingkan antara metode trial dan error dengan metode Modified Particle Swarm Optimization (MQPSO) untuk mengurangi Total harmonic Distortion (THD) pada sebuah sistem. Metode MQPSO memiliki keunggulan dalam kinerja yaitu proses sederhana, implementasikan ke sistem sangat mudah dan didalam perhitungan sangat efisien. Hasilnya menunjukkan bahwa nilai THD tanpa optimasi 13.53% sedangkan dengan tambahan metode MQPSO sebesar 13.46% dengan FFT Tool Simulink Matlab V17 dengan selisih THD optimal sebesar 0.07%. Sedangkan pengujian waktu kestabilan yang terdiri dari parameter C2, R2, dan R1 didapatkan THD 0.116% pada 0.174s tanpa optimasi dan 0.113s menggunakan optimasi dengan selisih waktu sebesar 0.063s untuk mencapai kestabilan. 

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.

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 An Enhanced Multi-Objective Particle Swarm Optimization in Water Distribution Systems Design

Water ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1334
Author(s):  
Mohamed R. Torkomany ◽  
Hassan Shokry Hassan ◽  
Amin Shoukry ◽  
Ahmed M. Abdelrazek ◽  
Mohamed Elkholy
Keyword(s):  
Particle Swarm Optimization ◽  
Local Search ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution Systems ◽  
Particle Swarm ◽  
Large Network ◽  
Swarm Optimization ◽  
Original Algorithm ◽  
Multi Objective

The scarcity of water resources nowadays lays stress on researchers to develop strategies aiming at making the best benefit of the currently available resources. One of these strategies is ensuring that reliable and near-optimum designs of water distribution systems (WDSs) are achieved. Designing WDSs is a discrete combinatorial NP-hard optimization problem, and its complexity increases when more objectives are added. Among the many existing evolutionary algorithms, a new hybrid fast-convergent multi-objective particle swarm optimization (MOPSO) algorithm is developed to increase the convergence and diversity rates of the resulted non-dominated solutions in terms of network capital cost and reliability using a minimized computational budget. Several strategies are introduced to the developed algorithm, which are self-adaptive PSO parameters, regeneration-on-collision, adaptive population size, and using hypervolume quality for selecting repository members. A local search method is also coupled to both the original MOPSO algorithm and the newly developed one. Both algorithms are applied to medium and large benchmark problems. The results of the new algorithm coupled with the local search are superior to that of the original algorithm in terms of different performance metrics in the medium-sized network. In contrast, the new algorithm without the local search performed better in the large network.

scholarly journals Proportional-Integral Controllers Performance of a Grid-Connected Solar PV System with Particle Swarm Optimization and Ziegler–Nichols Tuning Method

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2516
Author(s):  
Klemen Deželak ◽  
Peter Bracinik ◽  
Klemen Sredenšek ◽  
Sebastijan Seme
Keyword(s):  
Particle Swarm Optimization ◽  
Distribution Network ◽  
Particle Swarm ◽  
Open Loop ◽  
Limited Area ◽  
Solar Pv ◽  
Pv System ◽  
Swarm Optimization ◽  
Proportional Integral ◽  
Tuning Method

This paper deals with photovoltaic (PV) power plant modeling and its integration into the medium-voltage distribution network. Apart from solar cells, a simulation model includes a boost converter, voltage-oriented controller and LCL filter. The main emphasis is given to the comparison of two optimization methods—particle swarm optimization (PSO) and the Ziegler–Nichols (ZN) tuning method, approaches that are used for the parameters of Proportional-Integral (PI) controllers determination. A PI controller is commonly used because of its performance, but it is limited in its effectiveness if there is a change in the parameters of the system. In our case, the aforementioned change is caused by switching the feeders of the distribution network from an open-loop to a closed-loop arrangement. The simulation results have claimed the superiority of the PSO algorithm, while the classical ZN tuning method is acceptable in a limited area of operation.

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