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Multi-area economic dispatch problem: Methods, uncertainties, and future directions.

Authors :
Sharifian, Yeganeh
Abdi, Hamdi
Source :
Renewable & Sustainable Energy Reviews. Mar2024, Vol. 191, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

The problem of economic dispatch is one of the significant topics in modern power system control, monitoring, and operation studies due to economic and environmental issues. The multi-area economic dispatch problem (MAED) is the extended version of the economic dispatch problem in modern, and interconnected power systems, especially in competitive environments, which leads to the improvement of power networks economically and technically. The main goal of the MAED problem is to find the optimal amounts of generation and power interchange between adjacent areas by minimizing the generation, and transmission costs, satisfying different operational, and physical constraints governing the problem. This study endeavors to present a comprehensive classification of different techniques, and methods applied to the multi-area economic dispatch problem while reviewing the most prominent studies in this field. Also, it covers comprehensive formulations of the problem and some important issues in the field of probabilistic MAED. Furthermore, some concepts, such as used test systems, and hardware specification are addressed. Finally, suggestions and future directions are highlighted. [Display omitted] • Presenting the formulation of MASED, MADED, RCMAED, RCMAEED, MAEED, and MANCEED. • Classify the methods based on problem-solving, and mechanism handling techniques. • Describing the mathematical-based optimization, and meta-heuristic methods. • Addressing the single-objective, and multi-objective proposed algorithms. • Detailing the probabilistic MAED techniques, and some data of the proposed methods. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13640321
Volume :
191
Database :
Academic Search Index
Journal :
Renewable & Sustainable Energy Reviews
Publication Type :
Academic Journal
Accession number :
174419251
Full Text :
https://doi.org/10.1016/j.rser.2023.114093