Research Article
The Use of Artificial Intelligence in Assessing the Reliability of Electric Power Systems and Networks
Issue:
Volume 13, Issue 1, February 2025
Pages:
15-23
Received:
27 November 2024
Accepted:
12 December 2024
Published:
17 January 2025
DOI:
10.11648/j.jeee.20251301.12
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Abstract: Improving the reliability of power networks is a critical challenge, especially with the rise of renewable energy sources and the continuous growth in electricity demand. This article explores the use of artificial intelligence, specifically dynamic Bayesian networks (DBNs), to evaluate the reliability of electric power systems and networks, focusing on the IEEE 9-bus and IEEE 14-bus networks as case studies. To achieve this, a comprehensive study was conducted by simulating various operating scenarios using these networks as models. These networks were modeled using the simulation and analysis software PyAgrum. Key system variables, including nodes, lines, generators, and transformers, were integrated into the analysis, enabling the construction of conditional probability tables (CPTs) for each component. These tables accounted for both interdependencies and state transitions to reflect real-world dynamics accurately. Simulations performed using MATLAB enabled an in-depth analysis of reliability levels, revealing critical information on the availability rates of nodes, transformers, and generators. The analysis identified specific vulnerabilities within the network, such as node 2 in the IEEE 9-bus network achieving an availability rate of 65%, which indicates robust performance. Conversely, nodes 7 and 9 exhibited significantly lower availability rates of 20% and 40%, respectively, highlighting critical areas requiring immediate attention. Similarly, transformer 1 displayed a relatively high availability rate of 70%, indicating strong performance, whereas transformer 3 showed a notably low availability rate of 30%, suggesting an urgent need for upgrades or replacements. For generators, generator 1 had the lowest availability at 25%, representing a critical vulnerability, while generator 2, with a 55% availability rate, stood out as the most efficient and could serve as a benchmark for performance improvement efforts.
Abstract: Improving the reliability of power networks is a critical challenge, especially with the rise of renewable energy sources and the continuous growth in electricity demand. This article explores the use of artificial intelligence, specifically dynamic Bayesian networks (DBNs), to evaluate the reliability of electric power systems and networks, focusi...
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Research Article
Nested Hexagonal Split Ring Resonator-Based Metamaterial for Performance Enhancement in Multiband Antenna
Issue:
Volume 13, Issue 1, February 2025
Pages:
24-39
Received:
17 December 2024
Accepted:
8 January 2025
Published:
6 February 2025
DOI:
10.11648/j.jeee.20251301.13
Downloads:
Views:
Abstract: In this paper, we present a Nested hexagonal shaped split-ring resonator based negative epsilon metamaterials layered on 11 mm × 10 mm × 1.524 mm Rogers RO4350B dielectric substrate and designed to enhance the performance of multiband satellite antennas. Simulations using CST electromagnetic software show that the NH-SRR metamaterial manifests seven distinct resonance frequencies of S21spectrum at 2.37, 3.92, 5.4, 7.71, 8.58, 9.73 and 10.94 GHz, spanning S, C, and X-bands. The unit cell yields an effective medium ratio (EMR) of 12.66 and an electrical dimension of 0.087λ × 0.079λ when calculated at 2.37 GHz, which implies the effectiveness and compactness of the NH-SRR shaped metamaterial. The simulated outcomes also revealed that negative electric permittivity (є) response is attained within 4.16-5.75 GHz, 10.16-11.58 GHz and 14.46-16 GHz, with Near-Zero permeability property near the resonance frequencies. Our methodology involves using multiple electromagnetic software tools, including CST, HFSS and COMSOL for simulation results and design validation. A detailed numerical analysis was conducted to assess the impact of using this metamaterial as array cover above a Log Periodic Dipole Array (LPDA) Antenna on the performance metrics, demonstrated that the LPDA with metamaterial superstrate surpasses the conventional antenna in term of gain, return in loss and impedance matching, particularly at frequencies where negative permittivity and near-zero permeability properties are observed. These findings suggest that the NH-SRR metamaterial offers compactness, efficiency and scalability for applications in modern wireless communication and network systems.
Abstract: In this paper, we present a Nested hexagonal shaped split-ring resonator based negative epsilon metamaterials layered on 11 mm × 10 mm × 1.524 mm Rogers RO4350B dielectric substrate and designed to enhance the performance of multiband satellite antennas. Simulations using CST electromagnetic software show that the NH-SRR metamaterial manifests seve...
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