Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/11531/7811
Título : Multiple criteria decision making and risk analysis as risk management tools for power systems planning
Autor : Linares Llamas, Pedro
Fecha de publicación : 1-ago-2002
Resumen : Uncertainties in power systems planning are getting more important nowadays due to the liberalization of the electricity industry and the increasing concern for the environmental impact of electricity generation. This paper presents an electricity planning model which deals with uncertainty and its associated risk at two levels. At the first level, by minimizing environmental risk through a multiple-criteria model. At the second level, by performing a risk analysis consistent with the multiple criteria model used before, and which applies classical decision rules for selecting the best planning strategy under uncertainty. Results show that the incorporation of additional criteria produce much more flexible and efficient strategies, which greatly reduce environmental risk at a little cost increment, while the risk analysis process selects flexible and robust strategies for the scenarios analyzed.
Uncertainties in power systems planning are getting more important nowadays due to the liberalization of the electricity industry and the increasing concern for the environmental impact of electricity generation. This paper presents an electricity planning model which deals with uncertainty and its associated risk at two levels. At the first level, by minimizing environmental risk through a multiple-criteria model. At the second level, by performing a risk analysis consistent with the multiple criteria model used before, and which applies classical decision rules for selecting the best planning strategy under uncertainty. Results show that the incorporation of additional criteria produce much more flexible and efficient strategies, which greatly reduce environmental risk at a little cost increment, while the risk analysis process selects flexible and robust strategies for the scenarios analyzed.
Descripción : Artículos en revistas
URI : https://doi.org/10.1109/TPWRS.2002.800991
ISSN : 0885-8950
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