Compensation of temporal averaging bias in solar irradiance data

Keith Gibson,Ian R Cole,Brian Goss,Thomas R Betts,Ralph Gottschalg

doi:10.1049/iet-rpg.2016.0903

Abstract

Solar irradiance data is used for the prediction of solar energy system performance but is presently a significant source of uncertainty in energy yield estimation. This also directly affects the expected revenue, so the irradiance uncertainty contributes to project risk and therefore the cost of finance. In this paper, the combined impact of temporal averaging, component deconstruction and plane translation mechanisms on uncertainty is analysed. A new method to redistribute (industry standard) hourly averaged data is proposed. This clearness index redistribution method is based on the statistical redistribution of clearness index values and largely corrects the bias error introduced by temporal averaging. Parameters for the redistribution model were derived using irradiance data measured at high temporal resolution by CREST, Loughborough University, over a 5 year period. The root mean square error (RMSE) of example net annual (2014) diffuse, beam and global yield of hourly averaged data were reduced from approximately 15% to 1%, 14% to 3% and 4% to 1%, respectively.

Highlights

High-quality datasets containing beam and diffuse irradiance are used in many fields of engineering and research, including solar energy, climate modelling, building performance, thermodynamics, material science and the study of transmittance and reflectance
The bias introduced by the averaging of solar irradiance data has been analysed over an extended dataset
Diffuse and beam components each have a significant bias error when calculated from hourly averaged global irradiance measurements, with beam irradiance underestimated and diffuse irradiance overestimated

Summary

Introduction

High-quality datasets containing beam and diffuse irradiance are used in many fields of engineering and research, including solar energy, climate modelling, building performance, thermodynamics, material science and the study of transmittance and reflectance. A minimum of 10, but ideally 20, years of irradiance data are aggregated into a typical meteorological year (TMY). 52.7616, −1.2406 altitude, m measurement global horizontal irradiance (Gh) reference years. The meteorological standard measurement for solar energy is termed ‘global horizontal irradiance’. This quantifies the power density received by a horizontal plane from the whole sky. In order to assess irradiance available to a given plane, translation algorithms are applied to the horizontal irradiance data. The outputs of these translation algorithms are typically non-linear to input irradiance, so the use of average values can lead to errors with a bias element. This paper assesses the consequences of the averaging of irradiance measurements and investigates a proposed solution to correct the bias introduced by averaging

Data used for analysis and validation

Overview of horizontal to in-plane irradiance translation

Impact of temporal averaging on uncertainty

CREST method of temporal bias compensation

Conclusion