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RSS FeedsEnergies, Vol. 12, Pages 1141: Performance and Design Optimization of a One-Axis Multiple Positions Sun-Tracked V-trough for Photovoltaic Applications (Energies)

 
 

23 march 2019 16:00:28

 
Energies, Vol. 12, Pages 1141: Performance and Design Optimization of a One-Axis Multiple Positions Sun-Tracked V-trough for Photovoltaic Applications (Energies)
 


In this article, the performance of an inclined north-south axis (INSA) multiple positions sun-tracked V-trough with restricted reflections for photovoltaic applications (MP-VPVs) is investigated theoretically based on the imaging principle of mirrors, solar geometry, vector algebra and three-dimensional radiation transfer. For such a V-trough photovoltaic module, all incident radiation within the angle θ a arrives on solar cells after less than k reflections, and the azimuth angle of V-trough is daily adjusted M times about INSA to ensure incident solar rays always within θ a in a day. Calculations and analysis show that two-dimensional sky diffuse radiation can’t reasonably estimate sky diffuse radiation collected by fixed inclined north-south V-trough, but can for MP-VPVs. Results indicate that, the annual power output (Pa) of MP-VPVs in a site is sensitive to the geometry of V-trough and wall reflectivity (ρ), hence given M, k and ρ, a set of optimal θ a and φ , the opening angle of V-trough, for maximizing Pa can be found. Calculation results show that the optimal θ a is about 21°, 13.5° and 10° for 3P-, 5P- and 7P-VPV-k/ θ a (k = 1 and 2), respectively, and the optimal φ for maximizing Pa is about 30° for k = 1 and 21° for k = 2when ρ > 0.8. As compared to similar fixed south-facing PV panels, the increase of annual electricity from MP-VPVs is even larger than the geometric concentration of V-trough for ρ > 0.8 in sites with abundant solar resources, thus attractive for water pumping due to stable power output in a day.


 
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Energies, Vol. 12, Pages 1135: An Expeditious Methodology to Assess the Effects of Intermittent Generation on Power Systems (Energies)
Energies, Vol. 12, Pages 1140: Short-Term Electricity Load Forecasting Model Based on EMD-GRU with Feature Selection (Energies)
 
 
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