Ana Bernardos

A methodology for calculating percentile values of annual direct normal solar irradiation series

A detailed knowledge of the solar resource is a critical point in the performance of an economic feasibility analysis of solar thermal electricity plants. In particular, the Direct Normal solar Irradiance (DNI) is the most determining variable in its final energy yield. Inter-annual variations of DNI can be large and seriously compromise the viability of solar energy projects. In this work, a methodology for evaluating the statistical properties of annual DNI series is presented for generating inputs to risk assessments in an economic feasibility analysis of a solar power plant. The methodology relies on the construction of a cumulative distribution function of annual DNI values, which allows for the evaluation of both mean and extreme climate characterization at a particular location in the long term.

Statistical analysis of CSP plants by simulating extensive meteorological series

The feasibility analysis of any power plant project needs the estimation of the amount of energy it will be able to deliver to the grid during its lifetime. To achieve this, its feasibility study requires a precise knowledge of the solar resource over a long term period. In Concentrating Solar Power projects (CSP), financing institutions typically requires several statistical probability of exceedance scenarios of the expected electric energy output. Currently, the industry assumes a correlation between probabilities of exceedance of annual Direct Normal Irradiance (DNI) and energy yield. In this work, this assumption is tested by the simulation of the energy yield of CSP plants using as input a 34-year series of measured meteorological parameters and solar irradiance. The results of this work show that, even if some correspondence between the probabilities of exceedance of annual DNI values and energy yields is found, the intra-annual distribution of DNI may significantly affect this correlation. This re...