@inproceedings{1195643168c5408c8b4df43a6a5ec998,
title = "Particle Swarm Optimization and Genetic Algorithms for Optimal Management of Network of Microgrids Based Renewable Energy and Diesel Generators",
abstract = "In this paper, particle swarm optimization and genetic algorithms are applied for the optimization of a network of microgrids based on renewable energy and diesel generators. The problem is formulated based on networked microgrids by developing the equalities, inequalities and bounds constraints using specific design variables and an objective function. These metaheuristic optimizations are applied based on the formulated problem to operate the network of microgrids during a day (24 hours). Simulations are conducted to operate a network of three microgrids by optimizing the diesel generators usage and the power exchange between the microgrid in the network. Results are provided to show optimization outcomes, of the two metaheuristic algorithms, using the formulated problem of the network of microgrids.",
keywords = "diesel generator, genetic algorithms, microgrid, network, particle swarm optimization, renewable energy",
author = "Adel Merabet and Ahmed Al-Durra and Tarek El-Fouly and El-Saadany, \{Ehab F.\}",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 6th International Conference on Smart Power and Internet Energy Systems, SPIES 2024 ; Conference date: 04-12-2024 Through 06-12-2024",
year = "2024",
doi = "10.1109/SPIES63782.2024.10983435",
language = "British English",
series = "2024 6th International Conference on Smart Power and Internet Energy Systems, SPIES 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "344--348",
booktitle = "2024 6th International Conference on Smart Power and Internet Energy Systems, SPIES 2024",
address = "United States",
}
