Dynamic rating management of overhead transmission lines operating under multiple weather conditions

Integration of a large number of renewable systems produces line congestions, resulting in a problem for distribution companies, since the lines are not capable of transporting all the energy that is generated. Both environmental and economic constraints do not allow the building new lines to manage...

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Detalles Bibliográficos
Autores: Martínez Torre, Raquel|||0000-0002-0278-2785, Mañana Canteli, Mario|||0000-0001-6886-8170, Arroyo Gutiérrez, Alberto|||0000-0002-6045-2610, Bustamante Sánchez, Sergio|||0000-0001-7691-6187, Laso Pérez, Alberto|||0000-0003-3751-7305, Castro Alonso, Pablo Bernardo, Mínguez Matorras, Rafael|||0000-0002-2451-8213
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universidad de Cantabria (UC)
Repositorio:UCrea Repositorio Abierto de la Universidad de Cantabria
Idioma:inglés
OAI Identifier:oai:repositorio.unican.es:10902/21902
Acceso en línea:http://hdl.handle.net/10902/21902
Access Level:acceso abierto
Palabra clave:Ampacity
Conductor temperature
Overhead transmission lines
Weather parameters
Real-time monitoring
Descripción
Sumario:Integration of a large number of renewable systems produces line congestions, resulting in a problem for distribution companies, since the lines are not capable of transporting all the energy that is generated. Both environmental and economic constraints do not allow the building new lines to manage the energy from renewable sources, so the efforts have to focus on the existing facilities. Dynamic Rating Management (DRM) of power lines is one of the best options to achieve an increase in the capacity of the lines. The practical application of DRM, based on standards IEEE (Std.738, 2012) and CIGRE TB601 (Technical Brochure 601, 2014) , allows to find several deficiencies related to errors in estimations. These errors encourage the design of a procedure to obtain high accuracy ampacity values. In the case of this paper, two methodologies have been tested to reduce estimation errors. Both methodologies use the variation of the weather inputs. It is demonstrated that a reduction of the conductor temperature calculation error has been achieved and, consequently, a reduction of ampacity error.