Assessment of local solar resource measurement and predictions in south Louisiana

Background: The accessibility of reliable local solar resource data plays a critical role in the evaluation and development of any concentrating solar power (CSP) or photovoltaic (PV) project, impacting the areas of site selection, predicted output, and operational strategy. Currently available datasets for prediction of the local solar resource in south Louisiana rely exclusively on modeled data by various schemes. There is a significant need, therefore, to produce and report ground measured data to verify the various models under the specific and unique ambient conditions offered by the climate presented in south Louisiana. Methods: The University of Louisiana at Lafayette has been recording onsite high-fidelity solar resource measurements for the implementation into predictive models and for comparison with existing datasets and modeling resources. Industry standard instrumentation has been recording direct normal irradiance (DNI), diffuse horizontal irradiance (DHI), and global horizontal irradiance (GHI), as well as meteorological weather data since 2013. The measured data was then compared statistically to several available solar resource datasets for the geographic area under consideration. Results: Two years of high-fidelity solar resource measurements for a location in south Louisiana that were previously not available are presented. Collected data showed statistically good agreement with several existing datasets including those available from the National Solar Radiation Database (NSRDB). High variability in year-over-year monthly DNI due to cloud cover was prevalent, while a more consistent GHI level was observed. Conclusions: The analysis showed that the datasets presented can be utilized for predictive analysis on a monthly or yearly basis with good statistical correlation. High variability in year-over-year monthly DNI due to cloud cover was prevalent, with as much as a 70 % difference in monthly DNI values observed in the measured data. A more consistent GHI level was observed since the GHI is less susceptible to cloud cover transients. Collected data showed statistically good agreement with several existing datasets including those available from the NSRDB when forecasting was for monthly and yearly intervals.