EVALUACION Y PREDICCION DE LA RADIACION SOLAR TRANSMITIDA ENTRE EL HELIOSTATO Y EL RECEPTOR DE UN PLANTA TERMOSOLAR DE TORRE MEDIANTE TECNICAS DE INTELIGENCIA ARTIFICIAL
ENE2014-59454-C3-2-R
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Nombre agencia financiadora Ministerio de Economía y Competitividad
Acrónimo agencia financiadora MINECO
Programa Programa Estatal de I+D+I Orientada a los Retos de la Sociedad
Subprograma Todos los retos
Convocatoria Retos Investigación: Proyectos de I+D+I (2014)
Año convocatoria 2014
Unidad de gestión Dirección General de Investigación Científica y Técnica
Centro beneficiario UNIVERSIDAD DE HUELVA (UHU)
Centro realización ESCUELA TECNICA SUPERIOR DE INGENIERIA
Identificador persistente http://dx.doi.org/10.13039/501100003329
Publicaciones
Found(s) 1 result(s)
Found(s) 1 page(s)
Found(s) 1 page(s)
Worst expected ramp rates from cloud speed measurements
Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
- Wang, Guang Chao
- Bosch, Juan Luis
- Kurtz, Ben
- Parra Laita, Íñigo de la
- Wu, Elynn
Large PV power ramp rates are of concern and sometimes even explicitly restricted by grid operators. Battery energy storage systems can smooth the power output and maintain ramp rates within permissible limits. To enable PV plant and energy storage systems design and planning, a method to estimate the largest expected ramps for a given location is proposed. Because clouds are the dominant source of PV power output variability, an analytical relationship between the worst expected ramp rates, cloud motion vectors, and the geometrical layout of the PV plant is developed. The ability of the proposed method to bracket actual ramp rates is assessed over 8 months under different meteorological conditions, demonstrating an average compliance rate of 96.9% for a 2 min evaluation time window., Juan Luis Bosch has been financed in part by Projects ENE2017-83790-C3-3-R and ENE2014-59454-C3-2-R which were funded by the Ministerio de Ciencia, Innovación y Universidades and Ministerio de Economía y Competitividad, respectively, and co-financed by the European Regional Development Fund. In addition, Iñigo de la Parra has been partially supported by the Spanish State Research Agency (AEI) and FEDER-UE under grants DPI2016-80641-R and DPI2016-80642-R.