Automatic voltage regulator using TLBO algorithm optimized PID controller

Priyambada, Snigdha; Mohanty, Pradeep Kumar; Sahu, Binod Kumar

doi:10.1109/iciinfs.2014.7036595

Cited by 28 publications

(9 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The controller types that have been studied for improving the dynamic response of AVR system are proportional-integral-derivative (PID), fractional order PID (FOPID), gray PID (GPID), and fuzzy logic PID (FLPID). In literature, heuristic optimization-based tuning methods that have been applied to improve performance of the fore mentioned controller types are particle swarm optimization (PSO) (Gaing, 2004), artificial bee colony (ABC) (Gozde and Taplamacioglu, 2011), teaching learning-based optimization (TLBO) (Chatterjee and Mukherjee, 2016; Priyambada et al, 2014), gravitational search algorithm (GSA) (Duman et al, 2016; Kumar and Shankar, 2015), chaotic ant swarm (CAS) optimization (Zhu et al, 2009), chaotic optimization based on Lozi map (COLM) (Coelho, 2009), pattern search algorithm (PSA) (Sahu et al, 2012), anarchic society optimization (ASO) (Shayeghi and Dadashpour, 2012), many optimising liaisons (MOL) (Panda et al, 2012), Taguchi combined genetic algorithm (TCGA) (Hasanien, 2013), local unimodal sampling (LUS) optimization (Mohanty et al, 2014), firefly algorithm (FA) (Bendjeghaba, 2014), bio-geography-based optimization (BBO) (Guvenc et al, 2016), Nelder-Mead algorithm (NMA) (Verma et al, 2015), ant colony optimization (ACO) (Suri babu and Chiranjeevi, 2016), cuckoo search (CS) algorithm (Sikander et al, 2018), grasshopper optimization algorithm (GOA) (Hekimoglu and Ekinci, 2018) and genetic algorithm (GA) tuned neural networks (NN) (Al Gizi et al, 2015). It is worth mentioning that, in literature, the most studied heuristic optimization methods that have either been proposed or used for comparison with other existing methods for AVR system are PSO, GA, ABC and DE.…”

Section: Introductionmentioning

confidence: 99%

Sine-cosine algorithm-based optimization for automatic voltage regulator system

Hekimoğlu

2018

Transactions of the Institute of Measurement and Control

105

View full text Add to dashboard Cite

A novel design method, sine-cosine algorithm (SCA) is presented in this paper to determine optimum proportional-integral-derivative (PID) controller parameters of an automatic voltage regulator (AVR) system. The proposed approach is a simple yet effective algorithm that has balanced exploration and exploitation capabilities to search the solutions space effectively to find the best result. The simplicity of the algorithm provides fast and high-quality tuning of optimum PID controller parameters. The proposed SCA-PID controller is validated by using a time domain performance index. The proposed method was found efficient and robust in improving the transient response of AVR system compared with the PID controllers based on Ziegler-Nichols (ZN), differential evolution (DE), artificial bee colony (ABC) and bio-geography-based optimization (BBO) tuning methods.

show abstract

Section: Introductionmentioning

confidence: 99%

Sine-cosine algorithm-based optimization for automatic voltage regulator system

Hekimoğlu

2018

Transactions of the Institute of Measurement and Control

105

View full text Add to dashboard Cite

show abstract

“…Nowadays different algorithms are used to design the AVRs and improve the performance of these devices, some of these algorithms and a comparison between classic design methods and new design methods are explained in more details in [123][124][125][126][127][128].…”

Section: Automatic Voltage Regulator (Avr)mentioning

confidence: 99%

An overview of power quality enhancement techniques applied to distributed generation in electrical distribution networks

Naderi

Hosseini

Zadeh

et al. 2018

Renewable and Sustainable Energy Reviews

126

View full text Add to dashboard Cite

-It is obvious that power quality is an important characteristic of today's distribution power systems as loadsbecome more sensitive on the other hand nonlinear loads are increasing in the electrical distribution system. Considering the distributed nature of harmonic loads, the need for distributed power quality improvement (PQI) is inevitable. From years ago, researchers have been working on various kinds of filters and devices to enhance the overall power quality of power system, but today the nature of distribution system has been changed and power electronic based DGs play an important role in distribution grids. In this paper, a thorough survey is done on power quality enhancement devices with emphasis on ancillary services of multi-functional DGs. A literature review is also done on microgrids concept, testbeds and related control methods. Although there were some applications of DGs for PQI improvement these applications were not defined multi-functional DGs. Various control methods are studied and categorized regarding different viewpoints in the literature. Finally, a couple of thorough comparisons are done between the available techniques considering the nature, capabilities, advantages and implementation costs.

show abstract

“…Several computational methods have started to be used in AVR settings such as the genetic algorithm (GA) [5,6], teaching-learning-based optimization (TLBO) [7,8], sine cosine algorithm [9,10], world cup optimization [11,12], biogeography-based optimization [14], the Jaya optimization algorithm [15], global neighborhood algorithm [16], simulated annealing optimization algorithm [17], cuckoo search algorithm [18], firefly algorithm [19], whale optimization algorithm [20], and neural network [21,22]. This paper presents an analysis of the AVR performance, set up using a neural network based Fig.…”

Section: Introductionmentioning

confidence: 99%

An Improved Neural Network Based on Parasitism – Predation Algorithm for an Automatic Voltage Regulator

et al. 2021

View full text Add to dashboard Cite

The parasitism – predation algorithm (PPA) is an optimization method that duplicates the interaction of mutualism between predators (cats), parasites (cuckoos), and hosts (crows). The study employs a combination of the PPA methods using the cascade-forward backpropagation neural network. This hybrid method employs an automatic voltage regulator (AVR) on a single machine system, with the performance measurement focusing on speed and the rotor angle. The performance of the proposed method is compared with the feed-forward backpropagation neural network (FFBNN), cascade-forward backpropagation neural network (CFBNN), Elman recurrent neural network (E-RNN), focused time-delay neural network (FTDNN), and distributed time-delay neural network (DTDNN). The results show that the proposed method exhibits the best speed and rotor angle performance. The PPA-CFBNN method has the ability to reduce the overshoot of the speed by 1.569% and the rotor angle by 0.724%.

show abstract

Automatic voltage regulator using TLBO algorithm optimized PID controller

Cited by 28 publications

References 7 publications

Sine-cosine algorithm-based optimization for automatic voltage regulator system

Sine-cosine algorithm-based optimization for automatic voltage regulator system

An overview of power quality enhancement techniques applied to distributed generation in electrical distribution networks

An Improved Neural Network Based on Parasitism – Predation Algorithm for an Automatic Voltage Regulator

Contact Info

Product

Resources

About