Comparative study using soft computing techniques for the reactive power compensation of a hybrid power system model

Guchhait, Pabitra Kumar; Banerjee, Abhik; Mukherjee, V.

doi:10.1016/j.asej.2019.07.012

Cited by 17 publications

(8 citation statements)

References 28 publications

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“…Static VAR compensator (SVC), a reactance‐based shunt connected flexible alternate current transmissions (FACTs) device, is used for reactive power compensation in Mahmoudi et al 15 Active and reactive power management simultaneously can be achieved using STATCOM along with battery management system 16 . STATCOM, which is a converter‐based shunt connected FACTs device, has superior time response performance over SVC and so is used for dynamic reactive power compensation for voltage control 17 . To provide cost‐effective solutions, hybrid participation of FC and STATCOM is presented for such studies in Saxena and Kumar 14 .…”

Section: Introductionmentioning

confidence: 99%

Frequency regulation for microgrid using genetic algorithm and particle swarm optimization tuned STATCOM

Saxena¹,

Gao

Sharma

et al. 2022

Circuit Theory & Apps

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This paper presents the genetic algorithm (GA) and particle swarm optimization (PSO) based frequency regulation for a wind‐based microgrid (MG) using reactive power balance loop. MG, operating from squirrel cage induction generator (SCIG), is employed for exporting the electrical power from wind turbines, and it needs reactive power which may be imported from the grid. Additional reactive power is also required from the grid for the load, directly coupled with such a distributed generator (DG) plant. However, guidelines issued by electric authorities encourage MGs to arrange their own reactive power because such reactive power procurement is defined as a local area problem for power system studies. Despite the higher cost of compensation, static synchronous compensator (STATCOM) is a fast‐acting FACTs device for attending to these reactive power mismatches. Reactive power control can be achieved by controlling reactive current through the STATCOM. This can be achieved with modification in current controller scheme of STATCOM. STATCOM current controller is designed with reactive power load balance for the proposed microgrid in this paper. Further, gain values of the PI controller, required in the STATCOM model, are selected first with classical methods. In this classical method, iterative procedures which are based on integral square error (ISE), integral absolute error (IAE), and integral square of time error (ISTE) criteria are developed using MATLAB programs. System performances are further investigated with GA and PSO based control techniques and their acceptability over classical methods is diagnosed. Results in terms of converter frequency deviation show how the frequency remains under the operating boundaries as allowed by IEEE standards 1159:1995 and 1250:2011 for integrating renewable‐based microgrid with grid. Real and reactive power management and load current total harmonic distortions verify the STATCOM performance in MG. The results are further validated with the help of recent papers in which frequency regulation is investigated for almost similar power system models. The compendium for this work is as following: (i) modelling of wind generator‐based microgrid using MATLAB simulink library, (ii) designing of STATCOM current controller with PI controller, (iii) gain constants estimation using classical, GA and PSO algorithm through a developed m codes and their interfacing with proposed simulink model, (v) dynamic frequency responses for proposed grid connected microgrid during starting and load perturbations, (vi) verification of system performance with the help of obtained real and reactive power management between STATCOM and grid, and (vii) validation of results with available literature.

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Section: Introductionmentioning

confidence: 99%

Frequency regulation for microgrid using genetic algorithm and particle swarm optimization tuned STATCOM

Saxena¹,

Gao

Sharma

et al. 2022

Circuit Theory & Apps

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“…In practice, proportional (P)/PI/proportional plus integral plus derivative (PID) controllers are mostly used in the industries and power system. In this perspective, the researchers have proposed numerous controller design approaches and formulations to optimize the gains of the controllers to fit the dynamics of the power system 15 . The intelligent optimization techniques like a genetic algorithm (GA), 16 BFOA, 17 fuzzy‐GWO, 18 fuzzy‐bat algorithm, 9 Jaya algorithm, 19 etc., have been developed and applied to solve different optimization engineering problems such as tune/optimize the system/controller parameters.…”

Section: Introductionmentioning

confidence: 99%

“…The intelligent optimization techniques like a genetic algorithm (GA), 16 BFOA, 17 fuzzy‐GWO, 18 fuzzy‐bat algorithm, 9 Jaya algorithm, 19 etc., have been developed and applied to solve different optimization engineering problems such as tune/optimize the system/controller parameters. A comparative study of various soft computing techniques for reactive power compensation for the hybrid power systems is reported in Reference 15. In Reference 16, the authors have implemented the GA to adjust the PI controller parameters of the SVC and AVR for reactive power control.…”

Section: Introductionmentioning

confidence: 99%

“…Even though numerous intelligent algorithms have been recommended to accomplish the optimal values of the controller/system parameters, they have their own shortcomings 15 . Hence, with the aim of improving search performance (ie, convergence rate and optimized value of controller), the authors have recommended different hybrid algorithms by integrating two intelligent algorithms for reactive power control 21,22 .…”

Section: Introductionmentioning

confidence: 99%

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Bio‐inspired hybrid BFOA‐PSO algorithm‐based reactive power controller in a standalone wind‐diesel power system

Wagle

Sharma

et al. 2021

Int Trans Electr Energ Syst

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Summary With an increase in the penetration of renewable energy sources such as wind into the power systems, the operation and control of voltage/reactive power have become more complicated and challenging than ever. As a result, the reactive power imbalance between reactive power generation and demand instigates a reduction in system voltage stability. To deal with the aforesaid scenarios, automatic voltage regulator (AVR) and static synchronous compensator (STATCOM) are incorporated to curtail the voltage deviations in a standalone wind‐diesel power system. In this article, a hybrid bacterial foraging optimization algorithm‐particle swarm optimization (hBFOA‐PSO) algorithm is proposed for optimizing the PI controller parameters of AVR and STATCOM to further improve the system voltage/reactive power performance. Additionally, H∞‐loop shaping technique is designed to analyze the performance indexes (ie, robustness and stability) of the presented controller with the aim of handling the unstructured uncertainties from generation and loading situation. In order to present the efficiency of the proposed controllers, the performance of the hBFOA‐PSO controller is compared with the performance of the BFOA, PSO, and modified grey wolf optimization (MGWO)‐based PI controllers for the same wind‐diesel system. The dynamic responses of the wind‐diesel system for different disturbance cases have been investigated in the MATLAB/SIMULINK environment.

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“…So, in this paper, it is proposed to connect a fixed capacitor bank of appropriate value, which will supply a fixed reactive power for the entire operating region and the deficit reactive power is met by battery inverter system (BIS). It is to be noted that Navin Sam et al (2015, 2017b), Venkatraman et al (2016), and Guchhait et al (2020) have shown that the capacitor at the stator side should be varied dynamically so that the net reactive power at the stator terminals will vary accordingly, as per the reactive power requirement of the load, for operating the system with minimum power loss. Instead, for achieving this, an attempt is made in this present paper by employing a distribution static compensator (DSTATCOM) at the stator terminals.…”

Section: Introductionmentioning

confidence: 99%

Operation and control of a stand-alone power system with integrated multiple renewable energy sources

Sekhar

Kumaresan

2021

Wind Engineering

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To overcome the difficulties of extending the main power grid to isolated locations, this paper proposes the local installation of a combination of three renewable energy sources, namely, a wind driven DFIG, a solar PV unit, a biogas driven squirrel-cage induction generator (SCIG), and an energy storage battery system. In this configuration one bi-directional SPWM inverter at the rotor side of the DFIG controls the voltage and frequency, to maintain them constant on its stator side, which feeds the load. The PV-battery also supplies the load, through another inverter and a hysteresis controller. Appropriately adding a capacitor bank and a DSTATCOM has also been considered, to share the reactive power requirement of the system. Performance of various modes of operation of this coordinated scheme has been studied through simulation. All the results and relevant waveforms are presented and discussed to validate the successful working of the proposed system.

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Comparative study using soft computing techniques for the reactive power compensation of a hybrid power system model

Cited by 17 publications

References 28 publications

Frequency regulation for microgrid using genetic algorithm and particle swarm optimization tuned STATCOM

Frequency regulation for microgrid using genetic algorithm and particle swarm optimization tuned STATCOM

Bio‐inspired hybrid BFOA‐PSO algorithm‐based reactive power controller in a standalone wind‐diesel power system

Operation and control of a stand-alone power system with integrated multiple renewable energy sources

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