Salp Swarm Optimization Algorithm-Based Fractional Order PID Controller for Dynamic Response and Stability Enhancement of an Automatic Voltage Regulator System

Khan, Ismail Akbar; Alghamdi, Ali S.; Jumani, Touqeer Ahmed; Alamgir, Arbab; Awan, Ahmed Bilal; Khidrani, Attaullah

doi:10.3390/electronics8121472

Cited by 92 publications

(65 citation statements)

References 29 publications

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“…The fitness function tries to achieve a complete symbiosis and harmony between three fundamental terms to maximize the efficiency of the system. The first term of Equation (23) quantifies the error between the current reference and the current measured in the stationary frame, through normalized root-mean-square error (NRMSE), allowing the determination of the optimum parameters of the PR current controller. The remaining terms of Equation (23) search a balance between antagonistic and fundamental terms for the correct design of the output filter, as they quantify the damping effect and power loss.…”

Section: Proposed Methodologymentioning

confidence: 99%

Proportional Resonant Current Control and Output-Filter Design Optimization for Grid-Tied Inverters Using Grey Wolf Optimizer

et al. 2020

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This paper proposes a new method for the simultaneous determination of the optimal control parameters of proportional resonant controllers and the optimal design of the output filter of a grid-tied three-phase inverter. The proposed method, based on the grey wolf optimization (GWO) algorithm, addresses both optimization problems as a single process to achieve a better system frequency response. It optimizes the unknown parameters by using a fitness function to find the best trade-off between the following fundamental terms: the harmonic attenuation rate; the power loss, through the damping resistor; and the current tracking error in the stationary frame, ensuring the system and grid stability. To validate the proposed optimization methodology, two case studies are considered with different output filter topologies with passive damping methods. The results obtained from the proposed optimization procedure were analyzed and discussed according to the fitness function terms.

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Section: Proposed Methodologymentioning

confidence: 99%

Proportional Resonant Current Control and Output-Filter Design Optimization for Grid-Tied Inverters Using Grey Wolf Optimizer

et al. 2020

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“…The ITAE has been reported to be an effective objective function for the AGC system [66], [67]. This is because of its simplicity of use, reliability and improved efficiency in outputs [68]- [70]. The ITAE criterion exceeds IAE and ISE in its ability to minimize the settling time.…”

Section: ) Setpoint Weighted Fractional Order Pid Controllermentioning

confidence: 99%

Application of a New Fusion of Flower Pollinated With Pathfinder Algorithm for AGC of Multi-Source Interconnected Power System

2021

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As the world's population grows and energy demand increases, it is necessary to increase the scale of the electrical system, which is more complicated. Consequently, adopting automatic generation control (AGC) scheme to meet the demand becomes inevitable. In this article, the fusion of flower pollinated algorithm (FPA) and pathfinder algorithm (PFA), named hereafter as ℎFPAPFA, is proposed to achieve maximum control efficiency by combining the exploitation of FPA with the exploration capacity of PFA. The proposed ℎFPAPFA is meant to regulate two unequal multi-area interconnected power system with different generating units such as thermal, hydro, wind power and diesel plants. The proposed control scheme aims to achieve this by using the new algorithm to optimize the fractional-order set-point weighted PID (FOSWPID) parameters under time domain-based fitness functions namely, integral time square error (ITSE) and integral time absolute error (ITAE) while simultaneously minimizing the power losses. Employing the same interconnected power systems, a comparative study with some recent approaches in renowned journals is conducted. The performance of the proposed method is observed under diverse load conditions scenarios. Moreover, three nonlinearities including boiler dynamics, the governor dead band (GDB) and generation rate constraints (GRC) are further integrated into the system from a pragmatic context. Finally, sensitivity tests involving various parameter changes and the introduction of random step load perturbations are carried out. From the results, the proposed approach outperformed other approaches under different load condition scenarios, incorporation of nonlinearities and random load perturbation, demonstrating the proposed technique's efficacy and reliability.INDEX TERMS automatic generation control (AGC), flower pollinated algorithm, pathfinder algorithm integral time absolute error, governor dead band (GDB), generation rate constraints (GRC).

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“…It is important to note that a good SI optimization algorithm should possess the potential of pushing the search agents towards the global optimum continuously in order to find a better solution by exploring and exploiting the defined search space. Some of the very important features of a good optimization algorithm are listed as follows [99].…”

Section: Role Of Si Based Optimization Techniques In Ac Mg Controlmentioning

confidence: 99%

Swarm Intelligence-Based Optimization Techniques for Dynamic Response and Power Quality Enhancement of AC Microgrids: A Comprehensive Review

et al. 2020

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The increasing penetration of Microgrids (MGs) into existing power systems and ''plug and play'' capability of Distributed Generators (DGs) causes large overshoots and settling times along with various power quality issues such as voltage and frequency flickers, current harmonics and short current transients. In this context, over the past few years, considerable research has been undertaken to investigate and address the mentioned issues using different control schemes in conjunction with soft computational techniques. The recent trends and advancements in the field of Artificial Intelligence (AI) have led the development of Swarm Intelligence (SI) based optimized controllers for smooth Renewable Energy Sources (RES) penetration and optimal voltage, frequency, and power-sharing regulation. Moreover, the recent studies have proved that the SI-based controllers provide enhanced dynamic response, optimized power quality and improved the dynamic stability of the MG systems as compared to the conventional control methods. Their importance in modern AC MG architectures can be judged from the growing number of publications in the recent past. However, literature, pertaining to SI applications to AC MG, is scattered with no comprehensive review on this significant development. As such, this study provides an overview of 15 different SI optimization techniques as applied to AC MG controls from 43 research publications including a detailed review of one of the elementary and most widely used SI based metaheuristic optimization algorithms called Particle Swarm Optimization (PSO) algorithm. This comprehensive review provides a valuable one-stop source of knowledge for the researchers and experts working on SI controller's applications for AC MG dynamic response and power quality improvements.

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Salp Swarm Optimization Algorithm-Based Fractional Order PID Controller for Dynamic Response and Stability Enhancement of an Automatic Voltage Regulator System

Cited by 92 publications

References 29 publications

Proportional Resonant Current Control and Output-Filter Design Optimization for Grid-Tied Inverters Using Grey Wolf Optimizer

Proportional Resonant Current Control and Output-Filter Design Optimization for Grid-Tied Inverters Using Grey Wolf Optimizer

Application of a New Fusion of Flower Pollinated With Pathfinder Algorithm for AGC of Multi-Source Interconnected Power System

Swarm Intelligence-Based Optimization Techniques for Dynamic Response and Power Quality Enhancement of AC Microgrids: A Comprehensive Review

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