43 research outputs found
Assessment and forecasting of solar resource: applications to the solar energy industry
En la presente tesis doctoral se lleva a cabo un estudio de la evaluación y de la predicción del recurso solar para su aplicación en el campo de la industria solar. El objetivo principal es mejorar el conocimiento sobre varios aspectos de la radiación solar como fuente primaria de energía. Sin embargo, a pesar del incesante desarrollo tecnológico y el considerable abaratamiento de costes, su grado de introducción dentro de los sistemas eléctricos a gran escala está todavía lejos de su potencial real. Esto es debido en gran parte a que, a pesar de que la radiación solar es la fuente primaria de energía más abundante del planeta, presenta de forma natural una gran variabilidad espacio-temporal. Esta característica constituye la mayor fuente de incertidumbre en el desarrollo de los proyectos solares, tanto en la fase inicial de estudio de viabilidad como durante la fase de operación. Con el fin de contribuir a la reducción de dicha incertidumbre, en el trabajo de investigación llevado a cabo en esta tesis doctoral se han desarrollado y evaluado métodos para la caracterización y la estimación de la irradiancia solar en superficie, tanto para la componente global (GHI) como para la directa (DNI).In this thesis a study of the assessment and forecasting of the solar resource for its application in the solar industry is carried out. The main objective is to improve the knowledge about various aspects of solar radiation as primary energy source. . However, despite the relentless technological development and the considerable cost reductions, its degree of introduction at large-scale into power systems is still far from its real potential. This is due mainly to the fact that, although solar radiation is the most abundant primary energy source in the planet, it naturally presents a great spatial and temporal variability. This characteristic constitutes the major source of uncertainty in the development of solar projects, both in the initial phase of feasibility study and during the phase of operation. In order to contribute to the reduction of this uncertainty, the research work carried out in this thesis has developed and evaluated methods for the characterization and estimation of surface solar irradiance, both components: global (GHI) and direct (DNI).Tesis Univ. Jaén. Departamento de Física. Leída el 24 de julio de 2017
Benchmarking of different approaches to forecast solar irradiance
Ponencia presentada en: 24th European Photovoltaic Solar Energy Conference and Exhibition celebrada del 21-25 de septiembre de 2009 en Hamburgo.Power generation from photovoltaic systems is highly variable due to its dependence on
meteorological conditions. An efficient use of this fluctuating energy source requires reliable forecast information for
management and operation strategies. Due to the strong increase of solar power generation the prediction of solar
yields becomes more and more important. As a consequence, in the last years various research organisations and
companies have developed different methods to forecast irradiance as a basis for respective power forecasts. For the
end-users of these forecasts it is important that standardized methodology is used when presenting results on the
accuracy of a prediction model in order to get a clear idea on the advantages of a specific approach.
In this paper we introduce a benchmarking procedure to asses the accuracy of irradiance forecasts and compare
different approaches of forecasting. The evaluation shows a strong dependence of the forecast accuracy on the
climatic conditions. For Central European stations the relative rmse ranges from 40 % to 60 %, for Spanish stations
relative rmse values are in the range of 20 % to 35 %
A methodology for probabilistic assessment of solar thermal power plants yield
AIP Conference Proceedings 1850, 140006-1–140006-7A detailed knowledge of the solar resource is a critical point to perform an economic feasibility analysis of
Concentrating Solar Power (CSP) plants. This knowledge must include its magnitude (how much solar energy is
available at an area of interest over a long time period), and its variability over time. In particular, DNI inter-annual
variations may be large, increasing the return of investment risk in CSP plant projects. This risk is typically evaluated by
means of the simulation of the energy delivered by the CSP plant during years with low solar irradiation, which are
typically characterized by annual solar radiation datasets with high probability of exceedance of their annual DNI values.
In this context, this paper proposes the use meteorological years representative of a given probability of exceedance of
annual DNI in order to realistically assess the inter-annual variability of energy yields. The performance of this approach
is evaluated in the location of Burns station (University of Oregon Solar Radiation Monitoring Laboratory), where a 34-
year (from 1980 to 2013) measured data set of solar irradiance and temperature is available