Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/92982
Author(s): Bruno Gomes
João Tomé Saraiva
Title: Evaluation of transmission reinforcement strategies using risk indices in the presence of uncertainties
Issue Date: 2010
Abstract: This paper describes a hybrid approach in which generation cost and demand uncertainties are represented by fuzzy numbers and the life cycle of system components is modeled by probabilistic models. The Monte Carlo simulation model is used to sample system states according to the failure rates of the system components and a Fuzzy DC OPF model is used to analyse each sampled state. This Fuzzy DC OPF model adopts multi-parametric optimization techniques and admits that loads, generation costs or both of them simultaneously are modeled using fuzzy numbers. At the end of this process, it is possible to compute estimates of the Power Not Supplied and also of the exposure and robustness indices that characterize the ability that the system has to accommodate the specified uncertainties. This information can then be used to characterize the ability each reinforcement has in increasing the robustness of the system. Finally, the paper includes results for two case studies. On of them is based on a 6 bus system and the second uses the IEEE 24 bus/38 branch test system to illustrate the developed approaches. © 2010 IEEE.
Subject: Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
Scientific areas: Ciências da engenharia e tecnologias::Engenharia electrotécnica, electrónica e informática
Engineering and technology::Electrical engineering, Electronic engineering, Information engineering
URI: https://repositorio-aberto.up.pt/handle/10216/92982
Source: 2010 7th International Conference on the European Energy Market, EEM 2010
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: restrictedAccess
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

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