Sensitivity of global solar irradiance to transposition models: Assessing risks associated with model discrepancies
Year: 2024
Type: article
Abstract: • Introducing a novel theory named Risk Index (RI), serving as an indicator of a model's deviation from the comparative model. • Assessing TMs' sensitivity to β s of flat-plate solar harvesters, highlighting increased risk as the angle approaches vertical angle. • Recommending a unique TM for a certain β interval for all sites in the northern hemisphere. Estimating solar irradiance is essential for solar energy systems evaluations, energy audit of buildings and. Global and sky-diffuse horizontal irradiances are measured by meteorological stations and satellites. Global horizontal solar irradiance is converted into a global tilted solar irradiance using transposition models (TMs). Despite its importance, many sites—especially isolated rural areas in need of sustainable energy sources—have a conspicuous dearth of information regarding these models. Significant errors can occur when choosing the incorrect TM for feasibility assessments or determining the optimum tilt angles ( β ) for solar collectors. A novel theory (Risky Index theory) for determining the least risky TM is introduced in this work. To evaluate and validate the proposed theory, eight commonly used TMs from literature, database platforms and software were chosen and tested on 133 sites with various climatic and geographical conditions in the Northern Hemisphere. The study concludes that risk index (RI) is <10 % for all models when the collector is facing south with low tilt angles ( β <40°). However, for 40°< β <60° the RI rises above 15 %, and it becomes significant (RI<50 %) as β becomes close to vertical plane. The least risky TM was determined for each site. The results matched satisfactorily with other researchers’ outputs without exceeding 3.5 % of error. A unique TM has been recommended for the entire world corresponding to each interval of β .
Authors: Yasser F. Nassar, Hala J. El-Khozondar, Mohamed M. Khaleel, Abdussalam A. Ahmed, Abdulgader H. Alsharif, Monaem Elmnifi, Mark Amoah Nyasapoh
Institutions: Wadi Alshatti University, Islamic University of Gaza, London Centre for Nanotechnology, Imperial College London, Karabük University, Bani-Waleed University, Sebha University, Belgorod State Technological University, University of Energy and Natural Resources, Ghana Atomic Energy Commission
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,400
OpenAlex ID: W4405884247