Abstract
Determination of solar irradiance is a critical asset to ensure efficient working conditions for a photovoltaic (PV) system. This work analyze the feasibility of assessing solar irradiance on a PV device assuming the knowledge of the device temperature and the voltage/current operating point. This work proposes an approach based on a manipulation of the analytic expressions found in the reduced form of the “single diode” circuit model for a silicon PV device. The approach was validated through different practical experiments, and the results obtained are comparable to the ones of a commercial instrument for irradiance sensing. The ease of construction and the reduced costs involved make a device based on the proposed approach suitable for large-scale integration in a PV plant.
Highlights
Assessment of solar irradiance (G) is critical to ensure the correct and efficient operation of a system based on photovoltaic technology (PV)
Since the solar irradiance is correlated to the Maximum Power Point (MPP), the neural approach was used to determine the optimal voltage vmpp using a simple feed-forward artificial neural network (ANN) on low-end microcontroller unit (MCU) [9] and high-end Advanced Reduced Instruction Set Computer Machine (ARM) devices [10,11]
This work analyzed the feasibility of solar irradiance assesment on a PV device assuming the knowledge of the device temperature, the voltage/current work point and the identified five parameters model of the device
Summary
Assessment of solar irradiance (G) is critical to ensure the correct and efficient operation of a system based on photovoltaic technology (PV). Since the solar irradiance is correlated to the Maximum Power Point (MPP), the neural approach was used to determine the optimal voltage vmpp using a simple feed-forward ANN on low-end MCUs [9] and high-end Advanced Reduced Instruction Set Computer Machine (ARM) devices [10,11]. Addressing this problem through an ANN is effective and among the best solutions in terms of accuracy and low-cost strategies.
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