Single-Axis Tracker Control Optimization Potential for the Contiguous United States

Anderson, Kevin; Aneja, Saurabh

doi:10.1109/pvsc48317.2022.9938629

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…The improvement that could be obtained by replacing the Astronomical algorithm by another one aimed at maximizing the in-plane irradiance at all times was also quantified for the US, especially for locations with high sky diffuse fraction. [37] Figure 5 shows that in all solar tracking algorithms the irradiance gain value on the POA compared to GHI is higher in the algorithms without BT, but these algorithms present significant irradiance losses due to the self-shading effect, which do not happen when BT is applied. This is because during the time interrow shadings takes place, the unshaded modules of the string in the algorithms without BT are optimally oriented, compensating for the shading irradiance losses on the shaded modules.…”

Section: Resultsmentioning

confidence: 99%

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Evaluation of Horizontal Single‐Axis Solar Tracker Algorithms in Terms of Energy Production and Operational Performance

Muñoz,

Guinda,

Olivares

et al. 2023

Solar RRL

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Horizontal single‐axis solar tracking systems with Astronomical tracking algorithm are commonly used in photovoltaic (PV) installations. However, different algorithms could increase the PV installation’s performance without implementing new equipment or technologies. This paper compares the performance of three tracking algorithms to the Astronomical one. Two algorithms aim at optimizing the received irradiance focusing on the diffuse component. The third one, called Analytical, is presented as a new development in this study, defining the optimal inclination angle depending on all radiation components. The comparison focuses on different parameters like the in‐plane irradiance, DC power output from a monofacial PV system and operational aspects like the performed number of movements. High time resolution (1 minute) simulations have been performed with proprietary software taking into account several effects on the effective irradiance and power output estimation, such as shading effects or PV configuration. Eight locations with different climatic conditions have been analysed. All three algorithms derive in higher in‐plane irradiance and power output values than the Astronomical algorithm, although the gain depends on the climatic conditions. At locations with high diffuse fraction, the power output from the Analytical algorithm, which outperforms the others, could be up to 3% higher than the Astronomical one.This article is protected by copyright. All rights reserved.

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Section: Resultsmentioning

confidence: 99%

“…The improvement that could be obtained by replacing the Astronomical algorithm by another one aimed at maximizing the in‐plane irradiance at all times was also quantified for the US, especially for locations with high sky diffuse fraction. [ 37 ]…”

Section: Resultsmentioning

confidence: 99%

Evaluation of Horizontal Single‐Axis Solar Tracker Algorithms in Terms of Energy Production and Operational Performance

Muñoz,

Guinda,

Olivares

et al. 2023

Solar RRL

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“…In [ 19 ], a study similar to the one developed in [ 17 ] was performed, but considering the geographical context of the United States, evaluating the potential for improvement in irradiance collection based on direct and diffuse irradiance. Similarly, in [ 17 ], a “brute force” strategy was used to calculate the optimal positioning angle of the photovoltaic panels given the position of the sun and the irradiance at the time.…”

Section: Related Workmentioning

confidence: 99%

Solar Tracking Control Algorithm Based on Artificial Intelligence Applied to Large-Scale Bifacial Photovoltaic Power Plants

Santos de Araújo,

de Lucena,

da Silva Netto

et al. 2024

Sensors

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The transition to a low-carbon economy is one of the main challenges of our time. In this context, solar energy, along with many other technologies, has been developed to optimize performance. For example, solar trackers follow the sun’s path to increase the generation capacity of photovoltaic plants. However, several factors need consideration to further optimize this process. Important variables include the distance between panels, surface reflectivity, bifacial panels, and climate variations throughout the day. Thus, this paper proposes an artificial intelligence-based algorithm for solar trackers that takes all these factors into account—mainly weather variations and the distance between solar panels. The methodology can be replicated anywhere in the world, and its effectiveness has been validated in a real solar plant with bifacial panels located in northeastern Brazil. The algorithm achieved gains of up to 7.83% on a cloudy day and obtained an average energy gain of approximately 1.2% when compared to a commercial solar tracker algorithm.

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Simulated Performance Effect of Torque Tube Twisting in Single-Axis Tracking PV Arrays

Anderson,

Hansen

2024

2024 IEEE 52nd Photovoltaic Specialist Conference (PVSC)

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Single-Axis Tracker Control Optimization Potential for the Contiguous United States

Cited by 5 publications

References 15 publications

Evaluation of Horizontal Single‐Axis Solar Tracker Algorithms in Terms of Energy Production and Operational Performance

Evaluation of Horizontal Single‐Axis Solar Tracker Algorithms in Terms of Energy Production and Operational Performance

Solar Tracking Control Algorithm Based on Artificial Intelligence Applied to Large-Scale Bifacial Photovoltaic Power Plants

Simulated Performance Effect of Torque Tube Twisting in Single-Axis Tracking PV Arrays

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