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https://doi.org/10.30765/er.2402

Dynamic economic load dispatch problems in microgrid containing renewable energy sources based ontunicate swarm algorithm

Benyekhlef Larouci orcid id orcid.org/0000-0002-9302-9819 ; Department of Electrical Engineering, University Kasdi MerbahOuargla, Algeria *
Houari Boudjella ; Department of Electrical Engineering, University Kasdi MerbahOuargla, Algeria
Abdelkader Si Tayeb ; Applied Research Unit for Renewable Energies “URAER Ghardaia” Renewable Energy Development Center (CDER)
Ahmed Nour El Islamayad orcid id orcid.org/0000-0002-0238-2204 ; Department of Electrical Engineering, University Kasdi MerbahOuargla, Algeria

* Dopisni autor.


Puni tekst: engleski pdf 911 Kb

verzije

str. 37-50

preuzimanja: 95

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Sažetak

Dynamic Economic Load Dispatch (DELD) is a significant problem in microgridincluding renewable energy sources (RESs). The aim of this paper is to minimize the overall cost of the system while ensuring that the power demands of the consumers are met. However, with the added complexity of RESs, conventional optimization techniques may not be able to provide optimal solutions. This is where metaheuristic algorithms come into play, which are optimization techniques inspired by natural phenomena such as biological, nature, and animal behavior. This studycovers a new bio-inspired algorithm called Tunicate Swarm Algorithm (TSA)applied for solving DELD in microgrid with considering the variable power output of RES such as wind and solar energy. The DELD problem should also incorporate various constraints such as power balance and generation limits. Four cases of DELD containing RESs are treated. The obtained resultsare compared to other methods.. The result shows that for the DELD problem, the TSA demonstrate the superiority in term of optimise thegeneration cost compared to other optimization techniques.

Ključne riječi

dynamic economic environmental dispatch; tunicate swarm algorithm; optimal scheduling

Hrčak ID:

320422

URI

https://hrcak.srce.hr/320422

Datum izdavanja:

1.9.2024.

Posjeta: 305 *