arXiv subjects

M. A. Abido

Publications and source records attributed to M. A. Abido.

3 recordsLinked to original sources

arXiv2026

Voltage and Frequency Stability Analysis of Transmission Power Grids with EV Charging Stations

The large-scale Electric Vehicle (EV) integration into the electricity grid has initiated significant challenges to grid stability issues due to dynamic loadability events. Although electric vehicle impacts on distribution systems are well studied, transmission-level investigations remain limited. In this research paper, case scenarios of EV load models as charging stations have been considered for stability analysis (Voltage and Frequency Stability) to address EV operation on the transmission grid. It is also noted that the operation of EV stations due to their high loadability causes more stability complexities to the grid compared to other loads in a power network. Simulations have been conducted on two different power networks of the IEEE-9 and IEEE-39 bus test systems, respectively.

eess.SY↗

arXiv2020

High-Level Penetration of Renewable Energy with Grid: Challenges and Opportunities

The utilization of renewable energy sources (RESs) has become significant throughout the world especially over the last two decades. Although high-level RESs penetration reduces negative environmental impact compared to conventional fossil fuel based energy generation, control issues become more complex as well as total inertia to the system is significantly decreased due to removal of conventional synchronous generators. Some other technical issues, high uncertainties, low fault ride through capability, high fault current, low generation reserve, and low power quality, arise due to RESs integration. Renewable energy like solar and wind are highly uncertain due to intermittent nature of wind and sunlight. Cutting edge technologies including different control strategies, optimization techniques, energy storage devices, and fault current limiters are employed to handle those issues. This paper summarizes several challenges in the integration process of high-level RESs to the existing grid. The respective solutions to each challenge are also discussed. A comprehensive list of challenges and opportunities, for both wind and solar energy integration cases, are well documented. Also, the future recommendations are provided to solve the several problems of renewable integration which could be key research areas for the industry personnel and researchers.

eess.SY↗

arXiv2018

Optimal Placement of Relay Nodes in Wireless Sensor Network Using Artificial Bee Colony Algorithm

Deploying sensor nodes randomly most of the time generates initial communication hole even in highly dense networks. These communication holes cannot be totally eliminated even when the deployment is done in a structured manner. In either case, the resulting inter-node distances may degrade the performance of the network. This paper proposes an enhanced deployment algorithm based on Artificial Bees Colony (ABC). The ABC-based deployment is guaranteed to extend the lifetime by optimizing the network parameters and constraining the total number of deployed relays. Simulations validate the effectiveness of the proposed strategy under different cases of problem complexity. Results show that the proposed approach improves the network lifetime considerably when compared to solutions reported in the literature such as Shortest Path 3-D grid Deployment (SP3D) algorithm. Keywords: Artificial Bee Colony, Wiener index, optimization, relay nodes, Laplacian matrix, connected graph, vertex, edge, average distance, Laplacian matrix, Shortest Path 3-D grid Deployment, ABC, SP3D, RNs/CHs, ILDCC, SPRN, O3DwLC, algorithm, approach, single objective, multi objective, eigenvalue, First Phase Relay Nodes, NP-Hard, Deployment, proposed, second phase relay nodes, Ideal Media Access Control, cluster head, Minimum Spanning Tree, non-deterministic polynomial-time hard, two-layer hierarchical structure, Optimized 3-D deployment with Lifetime Constraints, flux, Wireless Sensor Network, size, Lifetime, Network load, number of nodes using packets, Connectivity, two layered, protocols, collision and interference.

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