Session: 06-01: CSP Optical Systems

Paper Number: 155688

155688 - Prediction of Circumsolar Ratio Using Solar Radiation Data and Clear Sky Model 

Abstract: 

This study presents the development of a predictive model for the circumsolar ratio (CSR), which is a key factor that affects the performance of concentrating solar power (CSP) systems. Most existing solar resource assessments tend to underestimate the impact of circumsolar radiation, especially in dusty environments such as Saudi Arabia. High-quality solar irradiance data are critical for developing reliable solar resource assessments. These data are typically gathered from various meteorological stations equipped with advanced instruments that go through regular calibration and maintenance. However, due to their wide aperture, instruments that measure Direct Normal Irradiance (DNI), including pyrheliometers, also capture circumsolar radiation; hence, it can lead to possible inaccuracies.

CSR, defined as the ratio of circumsolar radiation to actual DNI, plays a critical role in evaluating CSP plant performance. The primary objective is to develop a robust correlation for CSR that accurately captures the nonlinear relationship between CSR and the ratio of actual DNI to the ideal DNI obtained from a clear-sky model. While numerous studies have explored various aspects of circumsolar radiation and its influence on CSP systems, this work addresses a critical gap by developing a reliable CSR correlation. It provides a practical tool for designers of CSP installation systems to account for circumsolar radiation in regions with high dust levels.

To achieve this, several regression models, including tools leveraging artificial intelligence (AI) for nonlinear regression, were assessed using data from 11 geographically diverse locations. Among these, the nonlinear exponential model demonstrated the highest reliability and accuracy in predicting CSR, achieving an R² of 0.925, a root mean square error (RMSE) of 0.0478, and a near-zero mean bias error (MBE), making it a valuable tool for enhancing CSP system design and performance optimization. The ASHRAE clear-sky model was applied to generate theoretical DNI values, which were further compared with the actual DNI values to calculate the ratio of actual DNI to the ideal DNI.

From a practical perspective, the developed model can be integrated into solar energy systems simulations to improve the accuracy of resource assessments. It provides CSP plant designers with a more precise method to account for the scattering effect of circumsolar radiation, thereby enhancing overall system efficiency. Furthermore, the model’s applicability across multiple locations, supported by a diverse dataset, makes it a valuable asset for solar energy projects worldwide. The study contributes to the improvement of the CSP system's efficiency and provides practical insights into renewable energy systems, especially in arid regions where dust significantly affects solar irradiance.

Presenting Author: Ahmed Alshehri King Abdullah City for Atomic and Renewable Energy (K.A.CARE)

Presenting Author Biography: Ahmed Alshehri is an Energy Engineer II at King Abdullah City for Atomic and Renewable Energy (K.A.CARE). He holds an MSc degree in Mechanical Engineering from King Saud University, Saudi Arabia. He has seven years of experience in the renewable energy field, focusing on thermal energy systems and energy modeling. Ahmed is passionate about renewable energy, energy efficiency, and innovation in the energy sector, aiming to advance sustainable energy solutions for a cleaner, more efficient future.