Experimental Validation of a Novel Methodology for Fast an Accurate Analysis of Solar Energy Yields Based on Cluster Analysis

Abstract

The design and optimization of solar power systems requires a detailed knowledge of the dynamic behavior of the meteorology at the site of interest, usually assess by one typical meteorological year (TMY). Even with today’s technology, the computational effort to simulate solar energy system performance with one year of data at high frequency (as 1-min) may become colossal if a multivariable optimization has to be performed. This work evaluates a methodology based on cluster analysis for selecting number of individual days able to represent the long-term performance of a solar energy system. This procedure permits to drastically reduce computational effort related to the calculation of a solar power plant energy yield by simulating a reduced number of days from a TMY, facilitating a fast and optimal design of the plant.