Soft Computing Methods for Attaining the Protective Device Coordination Including Renewable Energies: Review and Prospective

Draz, Abdelmonem; Elkholy, Mahmoud M.; El‐Fergany, Attia A.

doi:10.1007/s11831-021-09534-5

Cited by 17 publications

(8 citation statements)

References 148 publications

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“…Amongst the various AI-based optimization techniques, MHAs have proven their accuracy and higher computation efficiency when compared with the other conventional optimization techniques [7]. Therefore, MHAs have been adopted to get the optimum solutions for several engineering problems such as power systems problems, as presented in [95][96][97][98][99][100][101][102][103][104]. Besides, depending on the no freelunch theory [105], many researchers have utilized various algorithms for accurate and effective investigation of the polarization characteristics of the PEMFC, as reported in [5,7,16,57].…”

Section: Mhas For Pemfc's Model Parameters Identificationmentioning

confidence: 99%

Computational Techniques Based on Artificial Intelligence for Extracting Optimal Parameters of PEMFCs: Survey and Insights

Ashraf

Abdellatif

Elkholy

et al. 2022

Arch Computat Methods Eng

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For the sake of precise simulation, and proper controlling of the performance of the proton exchange membrane fuel cells (PEMFCs) generating systems, robust and neat mathematical modelling is crucially needed. Principally, the robustness and precision of modelling strategy depend on the accurate identification of PEMFC’s uncertain parameters. Hence, in the last decade, with the noteworthy computational development, plenty of meta-heuristic algorithms (MHAs) are applied to tackle such problem, which have attained very positive results. Thus, this review paper aims at announcing novel inclusive survey of the most up-to-date MHAs that are utilized for PEMFCs stack’s parameter identifications. More specifically, these MHAs are categorized into swarm-based, nature-based, physics-based and evolutionary-based. In which, more than 350 articles are allocated to attain the same goal and among them only 167 papers are addressed in this effort. Definitely, 15 swarm-based, 7 nature-based, 6 physics-based, 2 evolutionary-based and 4 others-based approaches are touched with comprehensive illustrations. Wherein, an overall summary is undertaken to methodically guide the reader to comprehend the main features of these algorithms. Therefore, the reader can systematically utilize these techniques to investigate PEMFCs’ parameter estimation. In addition, various categories of PEMFC’s models, several assessment criteria and many PEMFC commercial types are also thoroughly covered. In addition to that, 27 models are gathered and summarized in an attractive manner. Eventually, some insights and suggestions are presented in the conclusion for future research and for further room of improvements and investigations.

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Section: Mhas For Pemfc's Model Parameters Identificationmentioning

confidence: 99%

Computational Techniques Based on Artificial Intelligence for Extracting Optimal Parameters of PEMFCs: Survey and Insights

Ashraf

Abdellatif

Elkholy

et al. 2022

Arch Computat Methods Eng

Self Cite

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“…In [48,49], the authors discuss the effect of increasing RESs on power system reliability. The authors in [50,51], shed light on the effect of renewable distributed generators on the settings of protective devices. The effect of increased penetration of RESs on power system frequency stability is illustrated in [52][53][54][55].…”

Section: Power System Inertia and Frequency Stabilitymentioning

confidence: 99%

“…Metaheuristic optimization algorithms differ from each other according to their constraints [50]. A summarization of some studies that have been conducted to enhance power system frequency based on various optimization algorithms for different frequency regulation techniques is given in Table 9.…”

Section: Application Of Metaheuristic Optimization On Frequency Controlmentioning

confidence: 99%

Computational Methods to Mitigate the Effect of High Penetration of Renewable Energy Sources on Power System Frequency Regulation: A Comprehensive Review

El-Bahay

Lotfy

El‐Hameed

2022

Arch Computat Methods Eng

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Depletion of fossil fuel, global warming, and their environmental pollution clarify the importance of renewable energy sources (RESs). However, high penetration of RESs decreases power systems inertia, hence, the system becomes more sensitive to disturbances. This results in problems with frequency control because it increases the rate of change of frequency and may lead to load shedding or tripping of generating units. This paper aims at introducing a comprehensive survey of the effects of the increase in RESs on power system inertia and frequency. Different models of wind-driven and photovoltaic systems used for frequency control studies have been introduced. The up-to-date effective frequency regulation methods which can be used with highly RESs penetrated power systems have been revised and compared. These methods include virtual inertia-based methods depending on energy storage devices, de-loading of renewable energy sources, various inertial response techniques and demand response at load section including under frequency load shedding and electric vehicles. Extensive comparisons among these methods have been carried to guide power system designers, operators, researchers and grid codes taskforces in proper incorporation of RESs for frequency regulation of power systems.

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“…These primary hardware ranges and ratings change depending on the loads connected to the network. The protection mechanisms built into the electrical system also differ depending on the linked equipment's location and nature [9]. The control components include the synchronization model and operational modules for transmitting the required signal to the digital modules used for the operation.…”

Section: Introductionmentioning

confidence: 99%

Cyber Security in Power Systems Using Meta-Heuristic and Deep Learning Algorithms

2023

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Supervisory Control and Data Acquisition system linked to Intelligent Electronic Devices over a communication network keeps an eye on smart grids' performance and safety. The lack of algorithms protecting the power system communication protocols makes them vulnerable to cyberattacks, which can result in a hacker introducing false data into the operational network. This can result in delayed attack detection, which might harm the infrastructure, cause financial loss, or even result in fatalities. Similarly, attackers may be able to feed the system with fake information to hoax the operator and the algorithm into making bad decisions at crucial moments. This paper attempts to identify and classify such cyber-attacks by using numerous deep learning algorithms and optimizing the data features with a metaheuristic algorithm. We proposed a Restricted Boltzmann Machine-based nature-inspired artificial root foraging optimization algorithm. Using a publicly available dataset produced in Mississippi State University's Oak Ridge National Laboratory, simulations are run on the Jupiter Notebook. Traditional supervised machine learning algorithms like Artificial Neural Networks, Convolutional Neural Networks, and Support Vector Machines are measured with the proposed algorithm to demonstrate the effectiveness of the algorithms. Simulations show that the proposed algorithm produced superior results, with an accuracy of 97.8% for binary classification, 95.6% for three-class classification, and 94.3% for multi-class classification. Thereby outperforming its counterpart algorithms in terms of accuracy, precision, recall, and f1 score.

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Soft Computing Methods for Attaining the Protective Device Coordination Including Renewable Energies: Review and Prospective

Cited by 17 publications

References 148 publications

Computational Techniques Based on Artificial Intelligence for Extracting Optimal Parameters of PEMFCs: Survey and Insights

Computational Techniques Based on Artificial Intelligence for Extracting Optimal Parameters of PEMFCs: Survey and Insights

Computational Methods to Mitigate the Effect of High Penetration of Renewable Energy Sources on Power System Frequency Regulation: A Comprehensive Review

Cyber Security in Power Systems Using Meta-Heuristic and Deep Learning Algorithms

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