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Transmission expansion planning - a multiyear dynamic approach using a discrete evolutionary particle swarm optimization algorithm

Title
Transmission expansion planning - a multiyear dynamic approach using a discrete evolutionary particle swarm optimization algorithm
Type
Article in International Conference Proceedings Book
Year
2012
Authors
M. C. Rocha
(Author)
FEUP
J. T. Saraiva
(Author)
FEUP
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Conference proceedings International
Pages: 1-14
2nd European Energy Conference
Maastricht, 17 a 20 de Abril de 2012
Indexing
Publicação em ISI Proceedings ISI Proceedings
Publicação em ISI Web of Knowledge ISI Web of Knowledge - 0 Citations
Publicação em ISI Web of Science ISI Web of Science
Publicação em Scopus Scopus - 0 Citations
Scientific classification
FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering
CORDIS: Technological sciences > Engineering > Electrical engineering
Other information
Authenticus ID: P-008-DCT
Abstract (EN): The basic objective of Transmission Expansion Planning (TEP) is to schedule a number of transmission projects along an extended planning horizon minimizing the network construction and operational costs while satisfying the requirement of delivering power safely and reliably to load centres along the horizon. This principle is quite simple, but the complexity of the problem and the impact on society transforms TEP on a challenging issue. This paper describes a new approach to solve the dynamic TEP problem, based on an improved discrete integer version of the Evolutionary Particle Swarm Optimization (EPSO) meta-heuristic algorithm. The paper includes sections describing in detail the EPSO enhanced approach, the mathematical formulation of the TEP problem, including the objective function and the constraints, and a section devoted to the application of the developed approach to this problem. Finally, the use of the developed approach is illustrated using a case study based on the IEEE 24 bus 38 branch test system.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 14
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