A methodology for probabilistic assessment of solar thermal power plants yield

Abstract

A 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.