Validating nine clear sky radiation models in Australia

There have been many validation studies of clear sky solar radiation models, however, to date, no such analysis has been completed for Australia. Clear sky models are essential for estimating the generation potential of various solar energy technologies, the basic calibration of radiation measuring equipment, quality control of solar radiation datasets, engineering design (e.g. heating and cooling of buildings) and in agricultural and biological sciences (e.g. forestry). All of these areas are of considerable interest to the Australian economy and will benefit from an assessment of clear sky radiation models. With the recent provision of one-minute interval radiation data by the Australian Bureau of Meteorology for 20 sites across Australia, such a study can now be undertaken at a level not previously possible. Using up to ten years of data from each of 14 of these sites, clear sky periods are extracted through an automated detection algorithm. With these clear sky periods identified, nine of the most prominent beam and global clear sky radiation models are assessed using the relative Mean Bias Error, relative Root Mean Square Error and Coefficient of Determination as metrics. Further testing assessed model performance as a function of solar zenith angle and apparent solar time. Results show that for global clear sky simulations, the Solis, Esra and REST2 approaches perform best, while the Iqbal, Esra and REST2 methods are the most proficient clear sky beam models.NAE would like to thank the United States National Science Foundation Graduate Research Fellowship Program and National ICT Australia, which provided partial support for this project

Minute resolution estimates of the diffuse fraction of global irradiance for southeastern Australia

Separating global horizontal irradiance measurements into direct and diffuse components has been vigorously discussed over the past half-century of solar radiation research leading to the creation of many models which attempt to compute these components with varying degrees of success. However, over the course of this discussion, nearly all studies have focused on hourly values, with no studies that have proposed a model for minute-level values of irradiance. As data-logging technologies have become much more prolific and their storage capabilities much larger, solar radiation monitoring sites are more commonly logging data at intervals much less than one hour, but no models exists that are designed to separate these measurements into direct and diffuse components. In Australia, the Australian Bureau of Meteorology and the Australian Solar Institute have compiled a dataset of tens of millions of one-minute global, direct and diffuse solar irradiance observations, comprising data from regions all around Australia. This dataset provides a unique opportunity to investigate the relationships between global irradiance and its direct and diffuse components at higher resolution than has previously been possible. Herein, the largest and most complete diffuse fraction model analysis yet undertaken for Australian solar radiation data, and the first ever to focus on minute resolution data is reported. Nine of the most prominent diffuse fraction, or “separation”, models are tested against minute resolution radiation data from three datasets. The first removed cloud enhancement events in accordance with practices undertaken by the majority of studies in the literature. The second retains these events in order to assess which model would be best suited for operational purposes. The third consisted of only clear sky observations, in order to assess the performance of diffuse fraction models under clear skies. Through the course of this study only the Perez model was found to perform satisfactorily for minute resolution data at sites in southeastern Australia. Three new diffuse models proposed in this study, one trained for each of the three datasets, were found to greatly exceed the performance of existing modeling techniques, with slight improvements over the Perez model

Correlation feature selection and mutual information theory based quantitative research on meteorological impact factors of module temperature for solar photovoltaic systems

The module temperature is the most important parameter influencing the output power of solar photovoltaic (PV) systems, aside from solar irradiance. In this paper, we focus on the interdisciplinary research that combines the correlation analysis, mutual information (MI) and heat transfer theory, which aims to figure out the correlative relations between different meteorological impact factors (MIFs) and PV module temperature from both quality and quantitative aspects. The identification and confirmation of primary MIFs of PV module temperature are investigated as the first step of this research from the perspective of physical meaning and mathematical analysis about electrical performance and thermal characteristic of PV modules based on PV effect and heat transfer theory. Furthermore, the quantitative description of the MIFs influence on PV module temperature is mathematically formulated as several indexes using correlation-based feature selection (CFS) and MI theory to explore the specific impact degrees under four different typical weather statuses named general weather classes (GWCs). Case studies for the proposed methods were conducted using actual measurement data of a 500 kW grid-connected solar PV plant in China. The results not only verified the knowledge about the main MIFs of PV module temperatures, more importantly, but also provide the specific ratio of quantitative impact degrees of these three MIFs respectively through CFS and MI based measures under four different GWCs.This work was supported in part by the National Natural Science Foundation of China (51577067, 51277075); the Natural Science Foundation of Beijing (3162033); the Natural Science Foundation of Hebei Province (E2015502060); the Key Project of the Science and Technology Support Program of Hebei Province (12213913D); the Fundamental Research Funds for the Central Universities (2014ZD29 and 2015XS108); State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (LAPS15009, LAPS16007 and LAPS16015), the China Scholarship Council (CSC) and the Science & Technology Project of State Grid Corporation of China (SGCC)

KPV: A clear-sky index for photovoltaics

The rapidly growing installed base of distributed solar photovoltaic (PV) systems is causing increased interest in forecasting their power output. A key step towards this is accurately estimating the output from a PV system based on the known output fro

A Simple Model for Estimating the Diffuse Fraction of Solar Irradiance from Photovoltaic Array Power Output

Given the rapid proliferation of data recording equipment for distributed photovoltaic (PV) arrays globally, there exists a new opportunity to use the power output from these systems for the purpose of surface solar radiation assessment. Direct measurements of the beam and diffuse irradiance represent the best methods for producing such assessments, however the equipment required for these observations are expensive and require routine maintenance, which therefore mean that the measurements are quite sparse globally. Satellite derived solar radiation estimates, meanwhile, have global coverage with increasingly fine resolution, but still require surface measurements of radiation in order to assess the performance of their solar radiation estimation algorithms (e.g. Heliostat). Therefore, it is global horizontal irradiance measurements recorded by a pyranometer, which have become the most common measurement of surface radiation. Pyranometers provide accurate surface radiation observations and are relatively inexpensive. As such, models which separate the diffuse and beam components in a global measurement have been discussed and developed vigorously in recent decades, with many modern models now accepted as the state of the art. This paper posits that the power output from PV systems is not altogether different from that recorded by pyranometers, and could be used in place of, or in supplement to, radiation observation equipment. This would greatly increase the density of the surface radiation measurement network, allowing for the many millions of PV systems reporting power output measurements globally to be applied to this purpose. PV system power output has a first order relationship with incoming solar radiation, but is confounded by additional second order interactions such as losses related to temperature, module efficiency, DC-AC conversion, soiling and shading, etc. Recently, research work by the first author has demonstrated that the individual nuances of PV systems can be accommodated through normalisation of their power output to their simulated clear sky performance. This normalised variable is termed the clear sky index for photovoltaics, KPV . We use this value as the primary input to a logistical regression model in place of the traditional input, the clearness index Kt, and explore the use of additional predictor variables to optimise accuracy. PV power output was collected from 18 sites in two Australian cities (Adelaide and Melbourne) in which Bureau of Meteorology solar radiation measurement stations are deployed. This allowed us to fit and test Kt and KPV based models to the observed diffuse radiation, and directly compare these approaches. Surprisingly, initial results suggest a KPV based model has nearly equivalent performance to that of the traditional, pyranometer based Kt model. This paper will explore this relationship more fully, and provide the first simple model available for this purpos

Validating nine clear sky radiation models in Australia

There have been many validation studies of clear sky solar radiation models, however, to date, no such analysis has been completed for Australia. Clear sky models are essential for estimating the generation potential of various solar energy technologies

Himawari-8 enabled real-time distributed PVsimulations for distribution networks

High resolution, next generation satellites such as Himawari-8 show great promise for the provision of accurate estimations of Behind-the-Meter (BtM) solar PV power production. This paper presents a methodology that produces real-time PV power estimates as derived from Himawari-8 satellite imagery, validating them against seven Australian radiation monitoring sites and 78 small-scale BtM solar PV sites in Canberra, Australia. We report an MBE of -7 W m-2 and RMSE of 55 W m-2 for global horizontal radiation values (Gh) and an MBE of 0.04 W/Wp and RMSE of 0.15 W/Wp for estimated actuals at the PV sites. As a capstone, we apply this satellite based radiation modeling tool to a distribution network level distributed PV simulation in a single case-study using 15,500 PV sites. This work was completed in collaboration with industry partner, Solcast