Investigating the suitability of GIS and remotely-sensed datasets for photovoltaic modelling on building rooftops

Gawley, David; McKenzie, Paul

doi:10.1016/j.enbuild.2022.112083

Cited by 12 publications

(10 citation statements)

References 51 publications

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“…The value to be set as the threshold is not shared: another study [47] takes 5 m 2 as the reference value, one [50] requires an even smaller surface-2 m 2 -and a third one [46] requires at least 40 m 2 . For this purpose, it is interesting to note that Gawley et al [38] set not only a minimum requirement but also a maximum, according to the values included in the British Energy Saving Trust sizing guide [97]. These return a producible output from 1 kWp-generally used in European studies-to 4 kWp-representing an average UK configuration.…”

Section: Pre-filteringmentioning

confidence: 99%

“…Another aspect directly affecting the producibility is the radiation striking the surface. In five cases, this was used as a limiting element, with different thresholds, ranging from 700 kWh/m 2 [38] to 1355 kWh/m 2 [40]. This depends on the case study, with some places receiving less solar energy compared to others, e.g., 700 kWh/m 2 is set for Northern Ireland, while 1355 kWh/m 2 for Pakistan.…”

Section: Pre-filteringmentioning

confidence: 99%

“…This depends on the author and-as for solar radiation-on the geographical position of the case study. Two studies exclude only 45 • from their calculations, namely [38,39]. The former aims to avoid the panels oriented from 315 • to 0 • , while the latter tends to exclude northfacing panels-oriented from 337.5 • to 22.5 • .…”

Section: Pre-filteringmentioning

confidence: 99%

“…A similar distribution can be observed for the thresholds defined for the slope. All authors except for Gawley and McKenzie [38] define only an upper threshold. Gawley and McKenzie [38] include a range of permissible slopes from 30 • to 60 • , defining as optimal inclination the one between 39 • and 40 • .…”

Section: Pre-filteringmentioning

confidence: 99%

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Trends and Evolution of the GIS-Based Photovoltaic Potential Calculation

Anselmo,

Ferrara

2023

Energies

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In the current framework of energy transition, renewable energy production has gained a renewed relevance. A set of 75 papers was selected from the existing literature and critically analyzed to understand the main inputs and tools used to calculate solar energy and derive theoretical photovoltaic production based on geographic information systems (GISs). A heterogeneous scenario for solar energy estimation emerged from the analysis, with a prevalence of 2.5D tools—mainly ArcGIS and QGIS—whose calculation is refined chiefly by inputting weather data from databases. On the other hand, despite some minor changes, the formula for calculating the photovoltaic potential is widely acknowledged and includes solar energy, exploitable surface, performance ratio, and panel efficiency. While sectorial studies—targeting a specific component of the calculation—are sound, the comprehensive ones are generally problematic due to excessive simplification of some parts. Moreover, validation is often lacking or, when present, only partial. The research on the topic is in constant evolution, increasingly moving towards purely 3D models and refining the estimation to include the time component—both in terms of life cycle and variations between days and seasons.

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Section: Pre-filteringmentioning

confidence: 99%

Section: Pre-filteringmentioning

confidence: 99%

Section: Pre-filteringmentioning

confidence: 99%

Section: Pre-filteringmentioning

confidence: 99%

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Trends and Evolution of the GIS-Based Photovoltaic Potential Calculation

Anselmo,

Ferrara

2023

Energies

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“…Por lo tanto, algunos estudios han utilizado los datos meteorológicos y/o datos de teledetección para estimar la energía solar radiante en lugares donde no hay medidores (Zhao et al 2022;Gueymard 2022). Otra alternativa son los módulos diseñados para la obtención del potencial teórico en sistemas de información geográfica (SIG), los cuales resultan viables para la estimación del potencial tanto para pequeñas y grandes escalas, desde techos de edificios hasta países enteros (Lan et al 2021;Kausica y van Sark, 2021,(Gawley andMcKenzie 2022).…”

Section: Introductionunclassified

Modelado espacial del potencial de energía solar en México a partir de Modelo Digital de Elevaciones ASTGTM V3

Martínez¹,

Ferrari²

2022

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Presentamos un modelo de alta resolución de la irradiación total del territorio nacional obtenido por medio del módulo "Solar Radiation toolset" de ArcGIS aplicado a un modelo digital de elevación (MDE) de alta resolución (30 x 30 m) obtenido a partir del Modelo de Elevación Digital Global, Versión 3, del Radiómetro de Reflexión y Emisión Térmica Espacial Avanzado de Terra (ASTGTM V3), cuyos datos se procesaron para eliminar valores erróneos. La alta resolución del MDE mejora significativamente los resultados particularmente en las zonas de cambios de relieve abrupto, que tienden a homogenizarse en modelos de baja resolución. Por cada celda se obtuvo la Radiación Solar Directa y la Radiación Solar Difusa con la finalidad de obtener la Radiación Solar Global en kilovatios hora por metro cuadrado (kWh/m$^2$). El resultado se presenta en 12 mapas mensuales y uno anual de la Radiación Solar Global del territorio nacional. Los meses que presentan mayor potencial de radiación solar corresponden a los meses de primavera y verano, con un máximo absoluto para el mes de julio. Los resultados teóricos de este trabajo se compararon con los valores de radiación de los modelos publicados por el National Renewable Energy Laboratory (NREL), y el Banco Mundial. Estos últimos muestran una sobreestimación del potencial solar debido a su menor resolución, particularmente en zonas con topografía abrupta.

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Rooftop segmentation and optimization of photovoltaic panel layouts in digital surface models

Aslani,

Seipel

2023

Computers, Environment and Urban Systems

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Investigating the suitability of GIS and remotely-sensed datasets for photovoltaic modelling on building rooftops

Cited by 12 publications

References 51 publications

Trends and Evolution of the GIS-Based Photovoltaic Potential Calculation

Trends and Evolution of the GIS-Based Photovoltaic Potential Calculation

Modelado espacial del potencial de energía solar en México a partir de Modelo Digital de Elevaciones ASTGTM V3

Rooftop segmentation and optimization of photovoltaic panel layouts in digital surface models

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