Run-time detection and correction of heliostat tracking errors

Scarselli, Eleonora Franchi; Guerrieri, R.

doi:10.1016/j.renene.2016.12.093

Cited by 12 publications

(4 citation statements)

References 22 publications

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“…Entre los factores más importantes que generan estas incertidumbres se pueden citar los siguientes (Berenguel et al, 2004), (Carballo et al, 2019) (Chiesi et al, 2017), (Rubio et al, 2007): errores de verticalidad y de orientación, por ejemplo en el poste principal, que además pueden ir evolucionando con el tiempo en función del terreno donde este ubicada la instalación y cómo se haya hecho la cimentación de la estructura; errores o imprecisiones en el montaje de los paneles, lo cual implica que el ángulo de aceptancia global de la instalación se reduce respeto al de un módulo en solitario; las estructuras no son perfectamente rígidas; y por último existen holguras en los mecanismos de movimiento.…”

Section: Idealunclassified

Evaluación del desempeño por apuntamiento de estrategias de control para seguidores solares fotovoltaicos de alta concentración

Satué

Castaño

Linares

et al. 2022

Rev. iberoam. autom. inform. ind.

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En este artículo se evalua el desempeño por apuntamiento de una serie de estrategias de control para seguidores solares de alta concentracion. Dado el alto grado de precisión que se necesita en el apuntamiento real, por debajo del semi ángulo de aceptancia global del sistema de captacion de energía, en el artículo se revisan las incertidumbres mas características del montaje de un seguidor solar, y se establece un marco teorico que permite representar imperfecciones de montaje en forma de relaciones de rotación de marcos de referencias asociados a los elementos del seguidor. Se expone un proceso de calibracion del sistema en dos etapas, que permite estimar incertidumbres parametricas de las rotaciones. Finalmente, se analizan cinco estrategias de control y los resultados experimentales obtenidos con ellas al implementarlas sobre un seguidor solar HCPV industrial de altas prestaciones. Los resultados muestran que con el sistema bien calibrado, todas las estrategias proporcionan un desempeno similar. Sin embargo, solo la basada en realimentacion en potencia es suficientemente robusta como para proporcionar buen desempeño cuando el sistema de descalibra.

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Section: Idealunclassified

Evaluación del desempeño por apuntamiento de estrategias de control para seguidores solares fotovoltaicos de alta concentración

Satué

Castaño

Linares

et al. 2022

Rev. iberoam. autom. inform. ind.

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show abstract

“…Among all the errors that can affect a solar energy collector [13], aiming errors, tracking offset and optical errors are those directly related to the STS. The first one is related to constant aberrations such as, pedestal tilt due to displacement of the center of gravity, bad reference or structure deformations due to wind loads.…”

Section: Sun Trackingmentioning

confidence: 99%

New approach for solar tracking systems based on computer vision, low cost hardware and deep learning

et al. 2019

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In this work, a new approach for Sun tracking systems is presented. Due to the current system limitations regarding costs and operational problems, a new approach based on low cost, computer vision open hardware and deep learning has been developed. The preliminary tests carried out successfully in Plataforma solar de Almería (PSA), reveal the great potential and show the new approach as a good alternative to traditional systems. The proposed approach can provide key variables for the Sun tracking system control like cloud movements prediction, block and shadow detection, atmospheric attenuation or measures of concentrated solar radiation, which can improve the control strategies of the system and therefore the system performance.

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“…Sun sensors are widely used in space applications [3,4] but are not limited to them. Applications, such as alternative power generation relying on solar panels [5] and heliostats [6] on earth, also require accurate solar tracking to provide maximum throughput.…”

Section: Introductionmentioning

confidence: 99%

Accurate and Cost-Effective Micro Sun Sensor based on CMOS Black Sun Effect

Saleem

Lee

2019

Sensors

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An accurate and cost-effective micro sun sensor based on the extraction of the sun vector using a phenomenon called the “black sun” is presented. Unlike conventional image-based sun sensors where there is difficulty in accurately detecting the sun center, the black sun effect allows the sun center to be accurately extracted even with the sun image appearing irregular and noisy due to glare. This allows the proposed micro sun sensor to achieve high accuracy even when a 1 mm × 1 mm CMOS image sensor with a resolution of 250 × 250 pixels is used. The proposed micro sun sensor is implemented in two application modes: (1) a stationary mode targeted at tracking the sun for heliostats or solar panels with a fixed pose of single image sensor of 1 mm × 1 mm × 1.74 mm in size and (2) a non-stationary mode targeted at determining the orientation of moving platforms with six sensors on the platform, which is configured in an icosahedron geometry of 23 mm × 23 mm × 12 mm in size. For the stationary mode, we obtained an accuracy of 0.013° by applying Kalman filter to the sun sensor measurement for a particular sensor orientation. For the non-stationary mode, we obtained an improved accuracy of 0.05° by fusing the measurements from three sun sensors available at any instant of time. Furthermore, experiments indicate that the black sun effect makes the precision of sun vector extraction independent of the sun location captured on the image plane.

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Run-time detection and correction of heliostat tracking errors

Cited by 12 publications

References 22 publications

Evaluación del desempeño por apuntamiento de estrategias de control para seguidores solares fotovoltaicos de alta concentración

Evaluación del desempeño por apuntamiento de estrategias de control para seguidores solares fotovoltaicos de alta concentración

New approach for solar tracking systems based on computer vision, low cost hardware and deep learning

Accurate and Cost-Effective Micro Sun Sensor based on CMOS Black Sun Effect

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