PSO-scaled fuzzy logic to load frequency control in hydrothermal power system

Jeyalakshmi, V.; Subburaj, P.

doi:10.1007/s00500-015-1659-8

Cited by 27 publications

(15 citation statements)

References 30 publications

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“…Gas power plants contribute a very little percentage of total power generation, and they are best suited for meeting the fluctuating peaking load demands (Nanda et al 2006). Thus, the natural alternative for AGC study, as also presented here, falls on mix of thermal and hydro units in each area of the system under study (Chandrakala et al 2013;Jeyalakshmi and Subburaj 2015).…”

Section: Literature Reviewmentioning

confidence: 98%

“…In context to fuzzy controller, various intelligent techniques and FLC structures are available in the literature (Chandrakala et al 2013;Saikia et al 2013;Sahu et al 2014;Bhateshvar et al 2015;Jeyalakshmi and Subburaj 2015;Sahu et al 2015a, b, c;Sekhar et al 2016). To the best of the authors' knowledge, till date, no research has been reported in the literature to design BFOA-optimized fuzzy PI/PID structured controller for AGC analysis of traditional and restructured power systems.…”

Section: Literature Reviewmentioning

confidence: 98%

“…Various conventional and intelligent techniques like ISE-based continuous-discrete control (Nanda et al 2006), Ziegler Nichols (ZN) method (Chandrakala et al 2013), variable structure control (Chandrakala et al 2013), neural networks (Chaturvedi et al 1999), genetic algorithm (GA) (Abdel-Magid and Dawoud 1996;Chandrakala et al 2013;Jeyalakshmi and Subburaj 2015), fuzzy control (Indulkar and Raj 1995;Chandrakala et al 2013;Jeyalakshmi and Subburaj 2015), bacterial forazing optimization algorithm (BFOA) (Ali and Abd-Elazim 2011), firefly algorithm (FA) (Padhan et al 2014), hybrid particle swarm optimizationpattern search (PSO-PS)-based fuzzy (Sahu et al 2015a), PSO (Gozde et al 2010;Abdel-Magid and Abido 2003;Panda et al 2013), PSO-based fuzzy (Jeyalakshmi and Subburaj 2015), hybrid BFOA-PSO (Panda et al 2013), artificial bee colony (ABC) (Gozde et al 2012), hybrid FA-PS (Sahu et al 2015b, c), hybrid differential evolution-PS (DE-PS)-based fuzzy ) and BFOA-based fuzzy ) are prevalent in the literature to solve AGC problem in traditionally interconnected power systems.…”

Section: Literature Reviewmentioning

confidence: 99%

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Design and analysis of BFOA-optimized fuzzy PI/PID controller for AGC of multi-area traditional/restructured electrical power systems

Arya

Kumar

2016

Soft Comput

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In this paper, design and performance analysis of bacterial foraging optimization algorithm (BFOA)-optimized fuzzy PI/PID (FPI/FPID) controller for automatic generation control of multi-area interconnected traditional/restructured electrical power systems is presented. Firstly a traditional two-area non-reheat thermal system is considered, and gains of the fuzzy controller are tuned employing BFOA using integral of squared error objective function. The supremacy of this controller is demonstrated by juxtaposing the results with particle swarm optimization (PSO), firefly algorithm (FA), BFOA, hybrid BFOA-PSObased PI and fuzzy PI controllers based upon pattern search (PS) and PSO algorithms for the same power system structure. The approach is then extended to a two-area reheat system, and improved results are found with the purported FPI/FPID controller in comparison with PSO and artificial bee colony optimized PI controller. Further, the approach is implemented on a traditional multi-source multi-area (MSMA) hydrothermal system and its superb performance is observed over genetic algorithm and hybrid FA-PS tuned PI controller. Additionally, to demonstrate the scalability of the designed controller to cope with restructured power system, the study is also protracted to a restructured MSMA

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Section: Literature Reviewmentioning

confidence: 98%

Section: Literature Reviewmentioning

confidence: 98%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Design and analysis of BFOA-optimized fuzzy PI/PID controller for AGC of multi-area traditional/restructured electrical power systems

Arya

Kumar

2016

Soft Comput

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“…The primary control is the regulation of the turbine speed limiter which is the governor by a regulation constant, the subordinate control deals with the ACE which is the summation of the product of the bias frequency with change in frequency and tie-line power deviation [3]. The tie-line power shares the power of the system based on the load changes [4]. Trial and error approach has been deployed to select parameters of the subordinate controllers (PID, MPC) and energy compensator devices (SMES, CES).…”

Section: Introductionmentioning

confidence: 99%

“…The grid frequency is improved with BIA optimal selected gains for a three area inter-connected network using MPC with SMES and considering nonlinearity features [2]. Particle Swarm Optimization Fuzzy Logic Controller (PSO LFC) is used to control a two area multi-unit inter-connected network in the work of [4]. [ how Cuckoo Search (CS) is used to optimize Proportional Integral Derivative (PID) Controller for two area thermal Combined Cycle Gas Turbine (CCGT) with GRC.…”

Section: Introductionmentioning

confidence: 99%

A Three Area Interconnected Power System Network Load Frequency Controller Simulator

Muritala

Mu’azu

Adedokun

2018

KINETIK

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This paper presents a MATLAB simulator of a three area interconnected power system of Thermal-Gas-Hydro. Nonlinearities intrinsic in the interconnected power system of communication delay, Generation Rate Constraint and Generation Dead Band were measured. Bat Inspired Algorithm was exploited to select the favourable parameters of the Model Predictive Controller and the Super Conducting Magnetic Energy Storage. Model Predictive Controller was the subordinate controller employed to minimalize the Area Control Error, Super Conducting Magnetic Energy Storage was the energy buffer to balance the load demand and the power generated. Integral Time Absolute Error was the performance metrics employed to minimize the Area Control Error. Parametric dissimilarity was tested on the inter-connected power system to observe the efficacy of the controller. Step load perturbation of was concurrently applied to the three-area inter-connected network, was introduced to the thermal generating unit, was introduced to the gas and hydro generating unit. Value of the tie-line was introduced to examine its effect on the frequency deviation. The results performed better when compared with Model Predictive Controller joined with Super Conducting Magnetic Energy Storage against the Model Predictive Controller without Super Conducting Magnetic Energy Storage in relations to settling time, overshoot and undershoot.

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New variable structure control based on different meta‐heuristics algorithms for frequency regulation considering nonlinearities effects

Elsisi

2020

Int Trans Electr Energ Syst

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PSO-scaled fuzzy logic to load frequency control in hydrothermal power system

Cited by 27 publications

References 30 publications

Design and analysis of BFOA-optimized fuzzy PI/PID controller for AGC of multi-area traditional/restructured electrical power systems

Design and analysis of BFOA-optimized fuzzy PI/PID controller for AGC of multi-area traditional/restructured electrical power systems

A Three Area Interconnected Power System Network Load Frequency Controller Simulator

New variable structure control based on different meta‐heuristics algorithms for frequency regulation considering nonlinearities effects

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