Transmission Network Expansion Planning under Uncertainty using the Conditional Value at Risk and Genetic Algorithms

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2013

Autores

Hugo R. Sardinha (Autor) Outra; João M. C. Sousa (Autor) Outra; Carlos A. Silva (Autor) Outra; Daniel Delgado (Autor) FEUP; João Claro (Autor) FEUP

Ata de Conferência Internacional

Título: INTELLI 2013, The Second International Conference on Intelligent Systems and Applications

Páginas: 135-140

INTELLI 2013, The Second International Conference on Intelligent Systems and Applications

Venice, Italy, April 21-26, 2013

Classificação Científica

FOS: Ciências da engenharia e tecnologias

CORDIS: Ciências Físicas > Matemática > Matemática aplicada > Investigação operacional

Outras Informações

Abstract (EN): The aim of this work is to study the Transmission Network Expansion Planning (TNEP) problem considering uncertainty on the demand side. Such problem consists of deciding how should an electrical network be expanded so that the future demand is ensured. We expanded the power transport problem formulation so that power losses are included in the objective function. Uncertainty is included through stochastic programming based on scenario analysis; different degrees of uncertainty are considered. Further, an explicit risk measure is added to mathematical model using the Conditional Value at Risk (CVaR). Weighting the relative importance of minimizing expansion and operational costs against the value of the CVaR simulates the attitude of the investor towards risk and shows to be of significant importance when planning the future. The problem was optimized using Genetic Algorithms. This work provided insight on how investment decisions change when considering several levels of uncertainty and risk aversion, in an extended formulation of the TNEP problem.

Idioma: Inglês

Tipo (Avaliação Docente): Científica