A wind farm control strategy for power reserve maximization

Nowadays, in many countries wind energy is responsible for a significant part of the electricity generation. For this reason, Transmission System Operators (TSOs) are now demanding the wind power plants (WPPs) to contribute with ancillary services such as frequency support. To this end, WPPs must be...

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Detalles Bibliográficos
Autores: Siniscalchi Minna, Sara, Bianchi, Fernando Daniel|||0000-0001-7332-6501, Prada Gil, Mikel de|||0000-0001-6491-8601, Ocampo-Martínez, Carlos|||0000-0001-9251-6044
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/125806
Acceso en línea:https://hdl.handle.net/2117/125806
https://dx.doi.org/10.1016/j.renene.2018.06.112
Access Level:acceso abierto
Palabra clave:Wind power plants
Wind turbines
Frequency control
Wind farm power regulation
De-loading operation
Power reserve maximization
Energia eòlica
Àrees temàtiques de la UPC::Energies
Descripción
Sumario:Nowadays, in many countries wind energy is responsible for a significant part of the electricity generation. For this reason, Transmission System Operators (TSOs) are now demanding the wind power plants (WPPs) to contribute with ancillary services such as frequency support. To this end, WPPs must be able to temporally increase the active power delivered into the grid to compensate consume and demand imbalances. This implies that WPPs now work below their maximum capacity to keep some power reserve to be able to inject extra power into the grid when needed. This reserve depends on the available wind power, which is directly connected with the wind speed faced by each turbine within the WPP. However, wind speed is negative affected by the wakes caused by the upstream turbines. This paper proposes a control algorithm to distribute the power contribution of each turbine seeking to minimize the wake effects and thus maximize the power reserve. The proposed algorithm is evaluated by simulations for the case of a WPP of 12 wind turbines.