Hybrid DC–AC Microgrid Energy Management System Using an Artificial Gorilla Troops Optimizer Optimized Neural Network

Murugan, Sathesh; Jaishankar, Mohana; Premkumar, K.

doi:10.3390/en15218187

Cited by 12 publications

(2 citation statements)

References 28 publications

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“…While it has been demonstrated in this study that the artificial gorilla troops algorithm (GTO) is a competitive algorithm by testing it through the CEC2019 benchmark functions, the same results have been achieved with different functions in previous studies [7]. Real-world problem such as renewable energy source [8,9], computer science [10], engineering optimization problems [11], power system stabilizer [12], industrial product design [13], and neural networks optimized [14] was solved with GTO algorithm and improved or hybrid variants of GTO at the used previous works. In this paper, three bar truss design problem will be discussed.…”

Section: Introductionmentioning

confidence: 58%

Assessment of GTO: Performance evaluation via constrained benchmark function, and Optimized of Three Bar Truss Design Problem

Eker

2023

DÜMF MD

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The aim of this paper is to show that the artificial gorilla troops optimization (GTO) algorithm, as an optimizer, can cope with test functions such as CEC2019, and also to best optimize the three bar truss design problem as a constrained optimization problem. As a method, two statistical measures such as the best values provided by the algorithms and the standard deviation showing the distance between the values were studied. At the same time, the convergence rate of the algorithms compared by the convergence curves were examined. For this purpose, it has been competed against two other swarm-based algorithms, sine-cosine algorithm (SCA) and golden eagle optimization (GEO). The optimization of the three bar truss design problem, which is another side of the study, has been made. The GTO algorithm reached the best values in the optimization of the parameters of the problem. In addition to the convergence curve, statistical results have examined, and the advantages of GTO are revealed through box-plot figures that evaluate the relationship between median and quartiles and the distribution among all results.

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Section: Introductionmentioning

confidence: 58%

Assessment of GTO: Performance evaluation via constrained benchmark function, and Optimized of Three Bar Truss Design Problem

Eker

2023

DÜMF MD

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“…The grasshopper-optimization-algorithm-based multistage PDF+(1+PI) structure for frequency control was proposed in [18]. The effect of different energy storage devices with a cascade controller structure on the frequency stability was studied in [19].…”

Section: Introductionmentioning

confidence: 99%

Improved Gorilla Troops Optimizer-Based Fuzzy PD-(1+PI) Controller for Frequency Regulation of Smart Grid under Symmetry and Cyber Attacks

Pachaiyappan,

Arasan,

Chandrasekaran

2023

Symmetry

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In a smart grid (SG) system with load uncertainties and the integration of variable solar and wind energies, an effective frequency control strategy is necessary for generation and load balancing. Cyberattacks are emerging threats, and SG systems are typical cyber-attack targets. This work suggests an improved gorilla troops optimizer (iGTO)-based fuzzy PD-(1+PI) (FPD-(1+PI)) structure for the frequency control of an SG system. The SG contains a diesel engine generator (DEG), renewable sources like wind turbine generators(WTGs), solar photovoltaic (PV), and storage elements such as flywheel energy storage systems (FESSs) and battery energy storage systems (BESSs) in conjunction with electric vehicles (EVs). Initially, the dominance of the projected iGTO over the gorilla troops optimizer (GTO) and some recently suggested optimization algorithms are demonstrated by considering benchmark test functions. In the next step, a traditional PID controller is used, and the efficacy of the GTO method is compared with that of the GTO, particle swarm optimization (PSO), and genetic algorithm (GA) methods. In the next stage, the superiority of the proposed FPD-(1+PI) structure over fuzzy PID (FPID) and PID structures is demonstrated under various symmetry operating conditions as well as under different cyberattacks, leading to a denial of service (DoS) and delay in signal transmission.

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A comprehensive review of hybrid AC/DC networks: insights into system planning, energy management, control, and protection

Abdelwanis,

Elmezain

2024

Neural Comput & Applic

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The introduction of hybrid alternating current (AC)/direct current (DC) distribution networks led to several developments in smart grid and decentralized power system technology. The paper concentrates on several topics related to the operation of hybrid AC/DC networks. Such as optimization methods, control strategies, energy management, protection issues, and proposed solutions. The implementation of neural network optimization methods has great importance for the successful integration of multiple energy sources, dynamic energy management, establishment of system stability and reliability, power distribution optimization, management of energy storage, and online fault detection and diagnosis in hybrid networks like the hybrid AC–DC microgrids (MG). Taking advantage of renewable energy generation and cost-cutting through the neural network optimization technique holds the key to these progressions. Besides identifying the challenges in the operation of a hybrid system, the paper also compares this system to conventional MGs and shows the benefits of this type of system over different MG structures. This review compares the different topologies, particularly looking at the AC–DC coupled hybrid MGs, and shows the important role of the interlinking of converters that are used for efficient transmission between AC and DC MGs and generally used to implement the different control and optimization techniques. Overall, this review paper can be regarded as a reference, pointing out the pros and cons of integrating hybrid AC/DC distribution networks for future study and improvement paths in this developing area.

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Hybrid DC–AC Microgrid Energy Management System Using an Artificial Gorilla Troops Optimizer Optimized Neural Network

Cited by 12 publications

References 28 publications

Assessment of GTO: Performance evaluation via constrained benchmark function, and Optimized of Three Bar Truss Design Problem

Assessment of GTO: Performance evaluation via constrained benchmark function, and Optimized of Three Bar Truss Design Problem

Improved Gorilla Troops Optimizer-Based Fuzzy PD-(1+PI) Controller for Frequency Regulation of Smart Grid under Symmetry and Cyber Attacks

A comprehensive review of hybrid AC/DC networks: insights into system planning, energy management, control, and protection

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