Estudos de Caso, Perspectivas

Executive Summary – PV Tracker Lifetime Cost Assessment: A Comparative Case Study

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A graph showing the PV trackers OPEX- Variable costs
This PV Tracker Lifetime Cost Model is based on the report named "PV Tracker Lifetime Cost Assessment Methodology_v1" issued by RINA on 1st June 2020.

Photovoltaic (PV) power plant equipment is typically selected almost exclusively on upfront cost, as capital expenditure, or CAPEX. But a more valuable analysis for PV plant design, build, and lifetime management would be to add accurate operational expense, or OPEX, to the initial financial decision-making process and project component selection.

Conducting a comprehensive lifetime cost assessment can provide asset owners with valuable insight into component selection and how this selection can affect PV plant lifetime revenue projections. Choosing components with an accurate estimate of total lifetime cost of ownership would allow stakeholders to improve profitability and minimize the operational risks of a project, particularly in the context of relatively short contractor warranty periods.

 

A Cost Comparison of PV Tracker Architecture: Centralized vs. Decentralized

Array Technologies Inc., one of the leading suppliers of PV tracking technologies, retained RINA Consulting as an Independent Engineer to perform a lifetime cost comparative assessment of popular single-axis tracker architectures currently available in the solar PV market.

This assessment is structured in three phases:

Phase 1 – PV Tracker Lifetime Cost Methodology
Phase 2 – Model based on the Methodology
Phase 3 – Comparative Case Study utilizing the Model

In Phase 3 of this assessment, an analysis comparing Array Technologies’ centralized tracking system with a market-standard, decentralized, single-axis tracker architecture was performed utilizing the PV tracker analysis model, PVTrax© which RINA developed from the methodology.

This comparative case study has been performed for a specific sample project location, a hypothetical 100 MWp PV plant somewhere in California, to ensure a fair comparison between the two trackers.

This assessment estimates the lifetime OPEX of the two distinct tracking architectures — centralized and decentralized — and compares the impact of tracker failures on the lifetime performance of the PV plant. In order to illustrate the lifetime OPEX, it is assumed that both tracking technologies have the same CAPEX.
The two-primary metrics for lifetime cost analysis are Levelized Cost of Energy (LCOE) and Net Present Value (NPV).

 

A Comparative Case Study on Two Approaches to Utility-Scale PV Solar Tracking

Approach 1: Multi-row tracking system (Tracker A, employing a centralized architecture)

Array’s Tracker A features articulated rotating drivelines with a disconnecting capability. This design introduces a great improvement with respect to traditional centralized architectures and makes it suitable for a variety of land topographies used in utility-scale PV plants as it does not require extensive grading prior to construction.

Approach 2: Single-row tracking system (Tracker B, employing a distributed architecture) Tracker B is a self-powered distributed system driving each row with a single drive motor, a controller, a battery, a battery charger, and a solar module. This system uses up to 32 times as many motors, controllers, and autonomous power supply systems than the centralized tracking system.

 

Comparing Operational Design, Reliability, and Maintenance

Comparing the operational and maintenance requirements for cleaning and mowing, Tracker A drivelines create small incremental operational costs due to the need to disconnect and then reconnect the drivelines.

This case study offers analysis showing that the robust design of the components in Tracker A are less likely to fail even though a motor failure could affect a larger number of rows. The case study goes on to show an additional 13,000 MWh are produced over the PV plant’s lifetime with Array’s centralized architecture.

This case study details that Tracker B, utilizing a distributed architecture, requires a greater number of components that logically increases preventive maintenance, corrective maintenance, or both when compared with a centralized tracker architecture. The use of more components in a distributed architecture creates more potential points of failure and increases risk of plant downtime. Typically, and as in this case study, distributed architectures contain components such as batteries and sensors which have a significantly lower life expectancy which add up to much higher unplanned operational expenses.

 

Case Study Results and Conclusions

This case study highlights that while both tracking solutions initially are quite equal, it becomes evident that Tracker A, or the centralized architecture, is significantly more economically favorable after year 5.

Although Tracker A, the centralized architecture, features slightly higher specific fixed operational costs due to driveline tasks for mowing and cleaning, variable costs are significantly greater in Tracker B, the decentralized tracker architecture. The decentralized architecture incurs higher variable costs due to the contribution of components with a shorter lifetime (e.g. batteries) together with a far greater number of components.

Over the first five years, both tracker architectures have equivalent costs. But after the expiration of the typical 5-year tracker supplier warranty, Tracker B, the decentralized architecture, incurs higher costs from year 6 until the end of the lifetime of the plant.

This case study shows Tracker A’s centralized design creates appreciable savings and significantly improves asset profitability over the lifetime of the PV solar plant. Key drivers in the lower lifetime costs of the centralized tracker architecture are higher uptime and lower corrective maintenance.

 

Case Study Highlights

  • NPV increases over 1.3 million dollars for asset owners using Array trackers
  • Lower LCOE over the plant’s lifetime with Array’s centralized architecture
  • Total lifetime OPEX is reduced by 42% by using the Array tracker vs. the modeled distributed row architecture
  • Higher energy output versus distributed tracker architecture
  • More than 7% lower tracker lifetime costs with Array trackers

Download our FREE case study to learn more!


For more detailed analysis, including access to tables and charts showing the inputs and results of each portion of the case study, please read the full report, methodology and view the PVTrax© tool

Click here for other articles by this author
Casos de estudio, Perspectivas

Resumen – Evaluación del coste de la vida útil del seguidor fotovoltaico: Un caso de estudio comparativo

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A graph showing the PV trackers OPEX- Variable costs
This PV Tracker Lifetime Cost Model is based on the report named "PV Tracker Lifetime Cost Assessment Methodology_v1" issued by RINA on 1st June 2020.

Los equipos de las plantas fotovoltaicas suelen seleccionarse casi exclusivamente en función del coste inicial, como gasto de capital, o CAPEX. Pero un análisis más valioso para el diseño, la construcción y la gestión de la vida útil de la planta sería añadir un gasto operativo preciso, o OPEX, al proceso inicial de toma de decisiones financieras y a la selección de componentes del proyecto.

La realización de una evaluación exhaustiva de los costes durante la vida útil puede proporcionar a los propietarios de activos una valiosa información sobre la selección de componentes y sobre cómo esta selección puede afectar a las previsiones de ingresos durante la vida útil de la planta fotovoltaica. La elección de componentes con una estimación precisa del coste total de propiedad durante la vida útil permitiría a los interesados mejorar la rentabilidad y minimizar los riesgos operativos de un proyecto, especialmente en el contexto de los periodos de garantía relativamente cortos del contratista.

Comparación de costes de la arquitectura del seguidor fotovoltaico: Centralizado vs. Descentralizado

Array Technologies Inc., uno de los principales proveedores de tecnologías de seguimiento fotovoltaico, contrató a RINA Consulting como ingeniero independiente para realizar una evaluación comparativa del coste de vida de las arquitecturas de seguimiento de un solo eje más populares actualmente disponibles en el mercado solar fotovoltaico.

Esta evaluación está estructurada en tres fases:

Fase 1 – Metodología de costes de vida útil del seguidor fotovoltaico
Fase 2 – Modelo basado en la metodología
Fase 3 – Caso de estudio comparativo utilizando el modelo

En la Fase 3 de esta evaluación, se ha realizado un análisis que compara el sistema de seguimiento centralizado de Array Technologies con una arquitectura de seguidor de un eje descentralizado, estándar en el mercado, utilizando el modelo de análisis de seguidores fotovoltaicos, PVTrax©, que RINA ha desarrollado a partir de la metodología.

Este estudio comparativo se ha realizado para un caso de muestra específico, una hipotética planta fotovoltaica de 100 MWp en algún lugar de California, para garantizar una comparación justa entre los dos seguidores.

Esta evaluación estima el OPEX durante la vida útil de las dos arquitecturas de seguimiento distintas -centralizada y descentralizada- y compara el impacto de los fallos del seguidor en el rendimiento durante la vida útil de la planta fotovoltaica. Para ilustrar el OPEX de por vida, se supone que ambas tecnologías de seguimiento tienen el mismo CAPEX.
Las dos métricas principales para el análisis del coste de la vida útil son el coste nivelado de la energía (LCOE) y el valor actual neto (VAN).

Estudio comparativo de dos enfoques para el seguimiento solar fotovoltaico

Enfoque 1: Sistema de seguimiento de multifila (Seguidor A, empleando una arquitectura centralizada).

El Seguidor A de Array cuenta con líneas motrices giratorias articuladas con capacidad de desconexión. Este diseño introduce una gran mejora con respecto a las arquitecturas centralizadas tradicionales y lo hace adecuado para una variedad de topografías del terreno utilizadas en las plantas fotovoltaicas a gran escala, ya que no requiere una gran nivelación antes de la construcción.

Enfoque 2: Sistema de seguimiento monofila (Seguidor B, que emplea una arquitectura descentralizada). El Seguidor B es un sistema distribuido autoalimentado que acciona cada fila con un único motor de accionamiento, un controlador, una batería, un cargador de batería y un módulo solar. Este sistema utiliza hasta 32 veces más motores, controladores y sistemas de alimentación autónoma que el sistema de seguimiento centralizado.

Comparación del diseño operativo, la fiabilidad y el mantenimiento

Si se comparan los requisitos operativos y de mantenimiento para la limpieza y la siega, las líneas de transmisión del seguidor A generan pequeños costes operativos adicionales debido a la necesidad de desconectar y volver a conectar las líneas de transmisión.

Este caso de estudio ofrece un análisis que muestra que el diseño robusto de los componentes del seguidor A tiene menos probabilidades de fallar a pesar de que un fallo del motor podría afectar a un mayor número de hileras. El caso de estudio continúa mostrando que se producen 13.000 MWh adicionales durante la vida útil de la planta fotovoltaica con la arquitectura centralizada de Array.

Este caso de estudio detalla que el seguidor B, que utiliza una arquitectura descentralizada, requiere un mayor número de componentes, lo que lógicamente aumenta el mantenimiento preventivo, el mantenimiento correctivo, o ambos, en comparación con una arquitectura de seguidor centralizada. El uso de más componentes en una arquitectura descentralizada crea más puntos potenciales de fallo e incrementa el riesgo de que se produzcan interrupciones en la planta. Normalmente, y como en este caso, las arquitecturas descentralizadas contienen componentes como baterías y sensores que tienen una esperanza de vida significativamente menor, lo que se traduce en unos gastos operativos no planificados mucho mayores.

Resultados y conclusiones del caso de estudio

Este caso de estudio pone de manifiesto que, aunque ambas soluciones de seguimiento son inicialmente bastante similares, resulta evidente que el seguidor A, o la arquitectura centralizada, es significativamente más conveniente desde el punto de vista económico a partir del quinto año.

Aunque el seguidor A, de arquitectura centralizada, presenta unos costes operativos fijos específicos ligeramente superiores debido a las tareas de siega y limpieza, los costes variables son significativamente mayores en el seguidor B, de arquitectura descentralizada. La arquitectura descentralizada incurre en mayores costes variables debido a la utilización de componentes con una vida útil más corta (por ejemplo, las baterías) y a un número mucho mayor de componentes.

Durante los primeros cinco años, ambas arquitecturas de seguidores tienen costes equivalentes. Sin embargo, tras la expiración de la típica garantía de 5 años del proveedor del seguidor, el Seguidor B, de arquitectura descentralizada, incurre en mayores costes desde el año 6 hasta el final de la vida útil de la planta.

Este caso de estudio muestra que el diseño centralizado del seguidor A genera ahorros apreciables y mejora significativamente la rentabilidad de los activos a lo largo de la vida útil de la planta solar fotovoltaica. Los principales factores que contribuyen a reducir los costes de la vida útil de la arquitectura centralizada del seguidor son un mayor tiempo de funcionamiento y un menor mantenimiento correctivo.

Conclusiones

  • El VAN aumenta más de 1,3 millones de dólares para los propietarios de activos que utilizan los seguidores de Array.
  • Menor LCOE durante la vida útil de la planta con la arquitectura centralizada de Array.
  • El OPEX total a lo largo de la vida útil se reduce en un 42% al utilizar el seguidor Array frente a la arquitectura de filas distribuidas modelada.
  • Mayor producción de energía frente a la arquitectura de seguidor descentralizada.
  • Los costes de la vida útil del seguidor son más de un 7% inferiores con los seguidores de Array.

Descargue el caso de estudio completo aquí.


Para un análisis más detallado, incluyendo el acceso a tablas y gráficos que muestran las entradas y los resultados de cada parte del caso de estudio, por favor lea el informe completo, la metodología y vea la herramienta PVTrax©.

Click here for other articles by this author
Case Studies, Perspectives

Executive Summary – PV Tracker Lifetime Cost Assessment: A Comparative Case Study

A graph showing the PV trackers OPEX- Variable costs
This PV Tracker Lifetime Cost Model is based on the report named "PV Tracker Lifetime Cost Assessment Methodology_v1" issued by RINA on 1st June 2020.

Photovoltaic (PV) power plant equipment is typically selected almost exclusively on upfront cost, as capital expenditure, or CAPEX. But a more valuable analysis for PV plant design, build, and lifetime management would be to add accurate operational expense, or OPEX, to the initial financial decision-making process and project component selection.

Conducting a comprehensive lifetime cost assessment can provide asset owners with valuable insight into component selection and how this selection can affect PV plant lifetime revenue projections. Choosing components with an accurate estimate of total lifetime cost of ownership would allow stakeholders to improve profitability and minimize the operational risks of a project, particularly in the context of relatively short contractor warranty periods.

 

A Cost Comparison of PV Tracker Architecture: Centralized vs. Decentralized

Array Technologies Inc., one of the leading suppliers of PV tracking technologies, retained RINA Consulting as an Independent Engineer to perform a lifetime cost comparative assessment of popular single-axis tracker architectures currently available in the solar PV market.

This assessment is structured in three phases:

Phase 1 – PV Tracker Lifetime Cost Methodology
Phase 2 – Model based on the Methodology
Phase 3 – Comparative Case Study utilizing the Model

In Phase 3 of this assessment, an analysis comparing Array Technologies’ centralized tracking system with a market-standard, decentralized, single-axis tracker architecture was performed utilizing the PV tracker analysis model, PVTrax© which RINA developed from the methodology.

This comparative case study has been performed for a specific sample project location, a hypothetical 100 MWp PV plant somewhere in California, to ensure a fair comparison between the two trackers.

This assessment estimates the lifetime OPEX of the two distinct tracking architectures — centralized and decentralized — and compares the impact of tracker failures on the lifetime performance of the PV plant. In order to illustrate the lifetime OPEX, it is assumed that both tracking technologies have the same CAPEX.
The two-primary metrics for lifetime cost analysis are Levelized Cost of Energy (LCOE) and Net Present Value (NPV).

 

A Comparative Case Study on Two Approaches to Utility-Scale PV Solar Tracking

Approach 1: Multi-row tracking system (Tracker A, employing a centralized architecture)

Array’s Tracker A features articulated rotating drivelines with a disconnecting capability. This design introduces a great improvement with respect to traditional centralized architectures and makes it suitable for a variety of land topographies used in utility-scale PV plants as it does not require extensive grading prior to construction.

Approach 2: Single-row tracking system (Tracker B, employing a distributed architecture) Tracker B is a self-powered distributed system driving each row with a single drive motor, a controller, a battery, a battery charger, and a solar module. This system uses up to 32 times as many motors, controllers, and autonomous power supply systems than the centralized tracking system.

 

Comparing Operational Design, Reliability, and Maintenance

Comparing the operational and maintenance requirements for cleaning and mowing, Tracker A drivelines create small incremental operational costs due to the need to disconnect and then reconnect the drivelines.

This case study offers analysis showing that the robust design of the components in Tracker A are less likely to fail even though a motor failure could affect a larger number of rows. The case study goes on to show an additional 13,000 MWh are produced over the PV plant’s lifetime with Array’s centralized architecture.

This case study details that Tracker B, utilizing a distributed architecture, requires a greater number of components that logically increases preventive maintenance, corrective maintenance, or both when compared with a centralized tracker architecture. The use of more components in a distributed architecture creates more potential points of failure and increases risk of plant downtime. Typically, and as in this case study, distributed architectures contain components such as batteries and sensors which have a significantly lower life expectancy which add up to much higher unplanned operational expenses.

 

Case Study Results and Conclusions

This case study highlights that while both tracking solutions initially are quite equal, it becomes evident that Tracker A, or the centralized architecture, is significantly more economically favorable after year 5.

Although Tracker A, the centralized architecture, features slightly higher specific fixed operational costs due to driveline tasks for mowing and cleaning, variable costs are significantly greater in Tracker B, the decentralized tracker architecture. The decentralized architecture incurs higher variable costs due to the contribution of components with a shorter lifetime (e.g. batteries) together with a far greater number of components.

Over the first five years, both tracker architectures have equivalent costs. But after the expiration of the typical 5-year tracker supplier warranty, Tracker B, the decentralized architecture, incurs higher costs from year 6 until the end of the lifetime of the plant.

This case study shows Tracker A’s centralized design creates appreciable savings and significantly improves asset profitability over the lifetime of the PV solar plant. Key drivers in the lower lifetime costs of the centralized tracker architecture are higher uptime and lower corrective maintenance.

 

Case Study Highlights

  • NPV increases over 1.3 million dollars for asset owners using Array trackers
  • Lower LCOE over the plant’s lifetime with Array’s centralized architecture
  • Total lifetime OPEX is reduced by 42% by using the Array tracker vs. the modeled distributed row architecture
  • Higher energy output versus distributed tracker architecture
  • More than 7% lower tracker lifetime costs with Array trackers

Download our FREE case study to learn more!


For more detailed analysis, including access to tables and charts showing the inputs and results of each portion of the case study, please read the full report, methodology and view the PVTrax© tool

Click here for other articles by this author