GOA optimised frequency control of solar-thermal/sea-wave/biodiesel generator based interconnected hybrid microgrids with DC link

Bhuyan, Mausri; Barik, Amar Kumar; Das, Dulal Chandra

doi:10.1080/14786451.2020.1741589

Cited by 37 publications

(13 citation statements)

References 20 publications

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“…In paper, 96 GOA is proposed to optimize the transient response and quality power of the grid‐tied MG while allocating the anticipated amount of power with the public mains. In paper, 97 two independent microgrid are interlinked to a DC bus which comprised of variant renewable sources. GOA tuned PID controller is applied by taking some extreme weather scenarios with perturb load variation.…”

Section: Meta‐heuristic Optimization Algorithmsmentioning

confidence: 99%

A comprehensive review of modern trends in optimization techniques applied to hybrid microgrid systems

Arfeen

Sheikh

Azam

et al. 2020

Concurrency and Computation

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Microgrids have drawn substantial consideration due to high quality and reliable mix sources of electricity. This paper articulates the implication of innovative algorithms for cognitive microgrid. It perceived the algorithms that are backed by artificial intelligence (AI) are quite efficient due to the precision, convergence speed, and less computation time as compared to the conventional heuristic methods. Solar PV/Battery grid‐connected MG is modeled to achieve optimum size, supreme power quality, reduced fluctuations in voltage and frequency, reduced settling time, eliminate short transient currents, seamless power, least annual cost and high reliability as an objective function under wavering weather condition and dynamic load changes. Four broad categorizations of metaheuristic algorithms, that is, evolutionary, swarm intelligence, physics, and human intelligence‐based algorithms are well elaborated in this study. The optimal solution to the fitness function by using a hybrid optimization method also directed in the study. This paper gives deep insight to readers working in the area.

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Section: Meta‐heuristic Optimization Algorithmsmentioning

confidence: 99%

A comprehensive review of modern trends in optimization techniques applied to hybrid microgrid systems

Arfeen

Sheikh

Azam

et al. 2020

Concurrency and Computation

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show abstract

“…The RES such as WTG, SPV, and linear Fresnel reflector (LFR) type STP units are integrated with waste-to-energy-based BEGS such as BDEG, BGTG, MHTG, and BCHP units in this microgrid [1]. Some works applied battery energy storage (BES) units for ALFC of isolated [20] and interconnected [21,22] microgrids.…”

Section: Introductionmentioning

confidence: 99%

“…Most of the recent works on ALFC of microgrids claimed the efficacy of classical proportional-integral-derivative (PID) controllers over conventional integral (I), proportionalintegral (PI), proportional-derivative (PD), and integral-derivative (ID) controllers [17][18][19][20][21]. Some modern controllers such as model predictive controller [19], fuzzy controller [22], fractional order controllers, and their blends [23,24] were also applied in similar works, however, they were corroborated with PID controllers.…”

Section: Introductionmentioning

confidence: 99%

Optimal Voltage–Frequency Regulation in Distributed Sustainable Energy-Based Hybrid Microgrids with Integrated Resource Planning

et al. 2021

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This work is the earliest attempt to propose an integrated resource planning for distributed hybrid microgrids considering virtual-inertia support (VIS) and demand-response support (DRS) systems. Initially, three-distributed sustainable energy-based unequal hybrid microgrids are envisioned with the availability of solar/wind/bioenergy resources. In order to overcome the effects of intermittency in renewable resources and low inertia, each microgrid is incorporated with DRS and VIS units for demand- and supply-side management, respectively. The proposed system is simulated in MATLAB considering real-time recorded solar/wind data with realistic loading for 12 months. A novel quasi-oppositional chaotic selfish-herd optimization (QCSHO) algorithm is proposed by hybridizing quasi-opposition-based learning and chaotic linear search techniques into the selfish-herd optimization, for optimal regulation of voltage and frequency in microgrids. Then, the system responses are compared with 7 algorithms and 5 error functions to tune PID controllers’ gains, which confirmed the superiority of QCSHO over others. Then, the study proceeds to investigate the voltage, frequency, and tie-line power coordination in 5 extreme scenarios of source and load variations in the proposed system without retuning the controllers. Finally, the system responses are analyzed for 10 different possible allocation of VIS and DRS units in different microgrids to find the most suitable combinations, and the results are recorded.

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“…In [17], Grasshopper optimisation technique is used for tuning the parameters of controllers in hybrid micro-grid with DC link. Some recent work concerning frequency oscillation studies in [18] considering hybrid micro-grids using demand response support.…”

Section: Introductionmentioning

confidence: 99%

Integrating layered recurrent ANN with robust control strategy for diverse operating conditions of AGC of the power system

Panwar

Arya²,

Kumawat³

2020

IET Generation, Transmission & Distribution

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GOA optimised frequency control of solar-thermal/sea-wave/biodiesel generator based interconnected hybrid microgrids with DC link

Cited by 37 publications

References 20 publications

A comprehensive review of modern trends in optimization techniques applied to hybrid microgrid systems

A comprehensive review of modern trends in optimization techniques applied to hybrid microgrid systems

Optimal Voltage–Frequency Regulation in Distributed Sustainable Energy-Based Hybrid Microgrids with Integrated Resource Planning

Integrating layered recurrent ANN with robust control strategy for diverse operating conditions of AGC of the power system

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