Optimized Distributed Cooperative Control for Islanded Microgrid Based on Dragonfly Algorithm

Al-dulaimi, Falah Noori Saeed; Kurnaz, Sefer

doi:10.3390/en16227675

Cited by 5 publications

(2 citation statements)

References 40 publications

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“…The secondary layer is responsible for ensuring voltage and frequency stability. Therefore, with delayed information to the secondary, the secondary control was out-of-order, hence the voltage stability [32,33].…”

Section: Resultsmentioning

confidence: 99%

Droop Control Optimization for Improved Power Sharing in AC Islanded Microgrids Based on Centripetal Force Gravity Search Algorithm

Taha,

Kurnaz

2023

Energies

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The urgent demand for clean and renewable energy sources has led to the emergence of the microgrid (MG) concept. MGs are small grids connecting various micro-sources, such as diesel, photovoltaic wind, and fuel cells. They operate flexibly, connected to the grid, standalone, and in clusters. In AC MG control, a hierarchical system consists of three levels: primary, secondary, and tertiary. It monitors and ensures MG stability, power quality, and power sharing based on the specifications of governing protocols. Various challenging transient disturbances exist, such as generator tripping, secondary control failure due to communication delay, and drastic load changes. Although several optimal power sharing methods have been invented, they pose complex control requirements and provide limited improvement. Therefore, in this paper, a novel optimized droop control is proposed using a metaheuristic multi-objective evolutionary algorithm called the Centripetal Force-Gravity Search Algorithm (CF-GSA) to improve the droop performance of power sharing, voltage and frequency stability, and power quality. CF-GSA is an improved algorithm designed to address the issue of local solutions commonly encountered in optimization algorithms. The effectiveness and superiority of the proposed method are validated through a series of simulations. The results of these simulations show that the proposed multi-objective optimization droop control method works well to fix problems caused by power sharing errors in isolated AC microgrids that have to deal with high inductive loads and changes in line impedance.

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Section: Resultsmentioning

confidence: 99%

Droop Control Optimization for Improved Power Sharing in AC Islanded Microgrids Based on Centripetal Force Gravity Search Algorithm

Taha,

Kurnaz

2023

Energies

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“…If they encounter a new deep fake or manipulation that was not taught, their performance will suffer. Earlier research [41][42][43] viewed the battle between deep fakers and detectors as a reactive defense mechanism rather than a war. A recent study validated this notion.…”

Section: Challenges With Deepfake Detectionmentioning

confidence: 99%

A Hybrid CNN-LSTM Approach for Precision Deepfake Image Detection Based on Transfer Learning

Al-Dulaimi,

Kurnaz

2024

Electronics

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The detection of deepfake images and videos is a critical concern in social communication due to the widespread utilization of deepfake techniques. The prevalence of these methods poses risks to trust and authenticity across various domains, emphasizing the importance of identifying fake faces for security and preventing socio-political issues. In the digital media era, deep learning outperforms traditional image processing methods in deepfake detection, underscoring its significance. This research introduces an innovative approach for detecting deepfake images by employing transfer learning in a hybrid architecture that combines convolutional neural networks (CNNs) and long short-term memory (LSTM). The hybrid CNN-LSTM model exhibits promise in combating deep fakes by merging the spatial awareness of CNNs with the temporal context understanding of LSTMs. Demonstrating effective performance on open-source datasets like “DFDC” and “Ciplab”, the proposed method achieves an impressive precision of 98.21%, indicating its capability to accurately identify deepfake images with a limited false-positive rate. The model’s error rate is 0.26%, emphasizing the challenges and intricacies inherent in deepfake detection tasks. These findings underscore the potential of hybrid deep learning techniques for addressing the urgent issue of deepfake image detection.

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Gray Wolf Algorithm Optimization of Automatic Generation Control for Deregulated Multi-Area Power System

Taha,

Elhassene,

El Heiba

2024

2024 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)

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Optimized Distributed Cooperative Control for Islanded Microgrid Based on Dragonfly Algorithm

Cited by 5 publications

References 40 publications

Droop Control Optimization for Improved Power Sharing in AC Islanded Microgrids Based on Centripetal Force Gravity Search Algorithm

Droop Control Optimization for Improved Power Sharing in AC Islanded Microgrids Based on Centripetal Force Gravity Search Algorithm

A Hybrid CNN-LSTM Approach for Precision Deepfake Image Detection Based on Transfer Learning

Gray Wolf Algorithm Optimization of Automatic Generation Control for Deregulated Multi-Area Power System

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