Incorporating shading losses in solar photovoltaic potential assessment at the municipal scale
► We developed a solar irradiation model with terrain & near surface shadowing effects. ► It utilizes free and open source GRASS and the module r.sun in modeling irradiation. ► The workflow is validated on LiDAR data for 100 buildings. ► The trade off of each computation options has been quantif...
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| Published in | Solar energy Vol. 86; no. 5; pp. 1245 - 1260 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Kidlington
Elsevier Ltd
01.05.2012
Elsevier Pergamon Press Inc |
| Subjects | |
| Online Access | Get full text |
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| Abstract | ► We developed a solar irradiation model with terrain & near surface shadowing effects. ► It utilizes free and open source GRASS and the module r.sun in modeling irradiation. ► The workflow is validated on LiDAR data for 100 buildings. ► The trade off of each computation options has been quantified at the meso scale.
Recently several algorithms have been developed to calculate the solar photovoltaic (PV) potential on the basis of 2.5D raster data that can capture urban morphology. This study provides a new algorithm that (i) incorporates both terrain and near surface shadowing effects on the beam component; (ii) scales down the diffuse components of global irradiation; and (iii) utilizes free and open source GRASS and the module r.sun in modeling irradiation. This algorithm is semi-automatic and easy to upgrade or correct (no hand drawn areas), open source, detailed and provides rules of thumb for PV system design at the municipal level. The workflow is pilot tested on LiDAR data for 100 buildings in downtown Kingston, Ontario. Shading behavior was considered and suitable roof sections for solar PV installations selected using a multi-criteria objective. At sub-meter resolution and small time steps the effect of occlusion from near object was determined. Annual daily horizontal irradiation values were refined at 0.55m resolution and were shown to be lower than those obtained at 90m by 30%. The robustness of r.sun as capable of working with different levels of surface complexity has been confirmed. Finally, the trade off of each computation option (spatial resolution, time step and shading effect) has been quantified at the meso scale, to assist planners in developing the appropriate computation protocols for their regions. |
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| AbstractList | Recently several algorithms have been developed to calculate the solar photovoltaic (PV) potential on the basis of 2.5D raster data that can capture urban morphology. This study provides a new algorithm that (i) incorporates both terrain and near surface shadowing effects on the beam component; (ii) scales down the diffuse components of global irradiation; and (iii) utilizes free and open source GRASS and the module r.sun in modeling irradiation. This algorithm is semi-automatic and easy to upgrade or correct (no hand drawn areas), open source, detailed and provides rules of thumb for PV system design at the municipal level. The workflow is pilot tested on LiDAR data for 100 buildings in downtown Kingston, Ontario. Shading behavior was considered and suitable roof sections for solar PV installations selected using a multi-criteria objective. At sub-meter resolution and small time steps the effect of occlusion from near object was determined. Annual daily horizontal irradiation values were refined at 0.55m resolution and were shown to be lower than those obtained at 90 m by 30%. The robustness of r.sun as capable of working with different levels of surface complexity has been confirmed. Finally, the trade off of each computation option (spatial resolution, time step and shading effect) has been quantified at the meso scale, to assist planners in developing the appropriate computation protocols for their regions. ► We developed a solar irradiation model with terrain & near surface shadowing effects. ► It utilizes free and open source GRASS and the module r.sun in modeling irradiation. ► The workflow is validated on LiDAR data for 100 buildings. ► The trade off of each computation options has been quantified at the meso scale. Recently several algorithms have been developed to calculate the solar photovoltaic (PV) potential on the basis of 2.5D raster data that can capture urban morphology. This study provides a new algorithm that (i) incorporates both terrain and near surface shadowing effects on the beam component; (ii) scales down the diffuse components of global irradiation; and (iii) utilizes free and open source GRASS and the module r.sun in modeling irradiation. This algorithm is semi-automatic and easy to upgrade or correct (no hand drawn areas), open source, detailed and provides rules of thumb for PV system design at the municipal level. The workflow is pilot tested on LiDAR data for 100 buildings in downtown Kingston, Ontario. Shading behavior was considered and suitable roof sections for solar PV installations selected using a multi-criteria objective. At sub-meter resolution and small time steps the effect of occlusion from near object was determined. Annual daily horizontal irradiation values were refined at 0.55m resolution and were shown to be lower than those obtained at 90m by 30%. The robustness of r.sun as capable of working with different levels of surface complexity has been confirmed. Finally, the trade off of each computation option (spatial resolution, time step and shading effect) has been quantified at the meso scale, to assist planners in developing the appropriate computation protocols for their regions. Recently several algorithms have been developed to calculate the solar photovoltaic (PV) potential on the basis of 2.5D raster data that can capture urban morphology. This study provides a new algorithm that (i) incorporates both terrain and near surface shadowing effects on the beam component; (ii) scales down the diffuse components of global irradiation; and (iii) utilizes free and open source GRASS and the module r.sun in modeling irradiation. This algorithm is semi-automatic and easy to upgrade or correct (no hand drawn areas), open source, detailed and provides rules of thumb for PV system design at the municipal level. The workflow is pilot tested on LiDAR data for 100 buildings in downtown Kingston, Ontario. Shading behavior was considered and suitable roof sections for solar PV installations selected using a multi-criteria objective. At sub-meter resolution and small time steps the effect of occlusion from near object was determined. Annual daily horizontal irradiation values were refined at 0.55 m resolution and were shown to be lower than those obtained at 90 m by 30%. The robustness of r.sun as capable of working with different levels of surface complexity has been confirmed. Finally, the trade off of each computation option (spatial resolution, time step and shading effect) has been quantified at the meso scale, to assist planners in developing the appropriate computation protocols for their regions. Recently several algorithms have been developed to calculate the solar photovoltaic (PV) potential on the basis of 2.5D raster data that can capture urban morphology. This study provides a new algorithm that (i) incorporates both terrain and near surface shadowing effects on the beam component; (ii) scales down the diffuse components of global irradiation; and (iii) utilizes free and open source GRASS and the module r.sun in modeling irradiation. This algorithm is semi-automatic and easy to upgrade or correct (no hand drawn areas), open source, detailed and provides rules of thumb for PV system design at the municipal level. The workflow is pilot tested on LiDAR data for 100 buildings in downtown Kingston, Ontario. Shading behavior was considered and suitable roof sections for solar PV installations selected using a multi-criteria objective. At sub-meter resolution and small time steps the effect of occlusion from near object was determined. Annual daily horizontal irradiation values were refined at 0.55 m resolution and were shown to be lower than those obtained at 90 m by 30%. The robustness of r.sun as capable of working with different levels of surface complexity has been confirmed. Finally, the trade off of each computation option (spatial resolution, time step and shading effect) has been quantified at the meso scale, to assist planners in developing the appropriate computation protocols for their regions. [PUBLICATION ABSTRACT] |
| Author | Nguyen, Ha T. Pearce, Joshua M. |
| Author_xml | – sequence: 1 givenname: Ha T. surname: Nguyen fullname: Nguyen, Ha T. organization: Department of Geography and Environment, Boston University, Boston, MA 02215, USA – sequence: 2 givenname: Joshua M. surname: Pearce fullname: Pearce, Joshua M. email: pearce@mtu.edu organization: Department of Materials Science & Engineering, Michigan Technological University, Houghton, MI 49931, USA |
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| Keywords | GIS Solar irradiation modeling Shading Photovoltaic Renewable energy Solar energy Multicriteria analysis Power system economics Multiobjective programming Modeling Surface effect Trade Roof Power markets Robustness Photovoltaic system Gas insulated switchgear System design Algorithm Mesoscale Geographic information system Morphology Irradiation Lidar Shadowing Spatial resolution |
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| Snippet | ► We developed a solar irradiation model with terrain & near surface shadowing effects. ► It utilizes free and open source GRASS and the module r.sun in... Recently several algorithms have been developed to calculate the solar photovoltaic (PV) potential on the basis of 2.5D raster data that can capture urban... |
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| SubjectTerms | Algorithms Applied sciences Connection and protection apparatus Direct energy conversion and energy accumulation Electric power Electrical engineering. Electrical power engineering Electrical power engineering Electronics Energy Engineering Sciences Equipments, installations and applications Exact sciences and technology GIS Natural energy Photoelectric conversion Photovoltaic Photovoltaic cells Photovoltaic conversion Renewable energy Shading Solar energy Solar irradiation modeling Solar radiation Studies |
| Title | Incorporating shading losses in solar photovoltaic potential assessment at the municipal scale |
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