This paper presents a3E(energy, environmental and economic) analysis of the impact of the movement limit on a horizontal single-axis tracker in Spain. Four scenarios have been analysed: (i) Scenario 1 (most favourable scenario), characterised by low wind and snow loads (Miraflores PVplant and Sueca location); (ii) Scenario 2, characterised by low wind and medium snow loads (CanredondoPVplant); (iii) Scenario 3, characterised by high wind and low snow loads (BasirPVplant); and (iv) Scenario 4 (less favourable scenario), characterised by high wind and snow loads (Rubió location). Four evaluation indicators (annual incident energy ratio,CO2emissions ratio,PVmounting system cost ratio,LCOEefficiency) and ten movement limits (βmax), ranging from±50 (o) to±60 (o), were analysed. Scenario 1 was used for comparison with the other scenarios. According to this study, the following conclusions can be drawn: (i) From an energetic point of view, the optimal maximum movement limit depends on each location; (ii) There is a relationship betweenCO2 emissions and the presence of wind and snow loads. The higher the impact of wind and snow loads, the higher theCO2emissions. For example, in Scenario 4, the configurationsβmax=±50 (o),βmax=±55 (o) andβmax=±60 (o) generate1.94(t/tracker),2.07 (t/tracker) and2.11(t/tracker) moreCO2 emissions compared to Scenario 1; (iii)CO2emissions decrease with decreasingβmax. For example, in Scenario 4, the βmax=±60 (o) configuration generates11.42%and4.23%more CO2emissions compared to theβmax=±50 (o) andβmax=±55 (o) configuration, respectively; (iv) There is a relationship between the cost of thePVmodule mounting system and the presence of wind and snow loads. The higher the impact of wind and snow loads, the higher the cost of thePVmodule mounting system. For example, in Scenario 4, the configurationsβmax=±50 (o),βmax=±55 (o) andβmax=±60 (o) the cost is higher by approximately 958 (€), 1034 (€) and 1045 (€) compared to Scenario 1; (v) The cost of the PVmodule mounting system decreases with decreasing βmax. For example, in Scenario 4, theβmax=±60 (o) configuration has a higher cost of8.44%and 3.05%compared to theβmax=±50 (o) andβmax=±55 (o) configuration, respectively; and (vi) In all scenarios analysed, the LCOEefficiency was always lower for movement limits below βmax=±55 (o).
Energy, environmental and economic analysis of the influence of the range of movement limit on horizontal single-axis trackers at photovoltaic power plants
Spagnuolo, G.
2025
Abstract
This paper presents a3E(energy, environmental and economic) analysis of the impact of the movement limit on a horizontal single-axis tracker in Spain. Four scenarios have been analysed: (i) Scenario 1 (most favourable scenario), characterised by low wind and snow loads (Miraflores PVplant and Sueca location); (ii) Scenario 2, characterised by low wind and medium snow loads (CanredondoPVplant); (iii) Scenario 3, characterised by high wind and low snow loads (BasirPVplant); and (iv) Scenario 4 (less favourable scenario), characterised by high wind and snow loads (Rubió location). Four evaluation indicators (annual incident energy ratio,CO2emissions ratio,PVmounting system cost ratio,LCOEefficiency) and ten movement limits (βmax), ranging from±50 (o) to±60 (o), were analysed. Scenario 1 was used for comparison with the other scenarios. According to this study, the following conclusions can be drawn: (i) From an energetic point of view, the optimal maximum movement limit depends on each location; (ii) There is a relationship betweenCO2 emissions and the presence of wind and snow loads. The higher the impact of wind and snow loads, the higher theCO2emissions. For example, in Scenario 4, the configurationsβmax=±50 (o),βmax=±55 (o) andβmax=±60 (o) generate1.94(t/tracker),2.07 (t/tracker) and2.11(t/tracker) moreCO2 emissions compared to Scenario 1; (iii)CO2emissions decrease with decreasingβmax. For example, in Scenario 4, the βmax=±60 (o) configuration generates11.42%and4.23%more CO2emissions compared to theβmax=±50 (o) andβmax=±55 (o) configuration, respectively; (iv) There is a relationship between the cost of thePVmodule mounting system and the presence of wind and snow loads. The higher the impact of wind and snow loads, the higher the cost of thePVmodule mounting system. For example, in Scenario 4, the configurationsβmax=±50 (o),βmax=±55 (o) andβmax=±60 (o) the cost is higher by approximately 958 (€), 1034 (€) and 1045 (€) compared to Scenario 1; (v) The cost of the PVmodule mounting system decreases with decreasing βmax. For example, in Scenario 4, theβmax=±60 (o) configuration has a higher cost of8.44%and 3.05%compared to theβmax=±50 (o) andβmax=±55 (o) configuration, respectively; and (vi) In all scenarios analysed, the LCOEefficiency was always lower for movement limits below βmax=±55 (o).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


