Hybrid Genetic Algorithm for Multi-Objective Transmission Expansion Planning

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2016

Autores

Gomes, PV (Autor) Outra; João Tomé Saraiva (Autor) FEUP

Ata de Conferência Internacional

Título: 2016 IEEE INTERNATIONAL ENERGY CONFERENCE (ENERGYCON)

IEEE International Energy Conference (ENERGYCON)

Leuven, BELGIUM, APR 04-08, 2016

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 5 Citações

Outras Informações

ID Authenticus: P-00M-NY7

DOI: 10.1109/energycon.2016.7514131

Abstract (EN): This paper aims to describe a new tool to solve the Transmission Expansion Planning problem (TEP). The Non-Dominative CHA-Climbing Genetic Algorithm uses the standard blocks of Genetic Algorithms (GA) associated with an improvement of the population building block using Constructive Heuristic Algorithms (CHA) and Hill Climbing Method. TEP is a hard optimization problem because it has a non convex search space and integer and nonlinear nature, besides, the difficulty degree can be further increased if it includes more than one objective. In this work, a multi-objective TEP approach is detailed using an AC Optimal Power Flow to generate the set of Pareto solutions using the investment cost and the level of CO2 emissions, i.e. two conflicting objectives.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6