TW
T. Weij
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Co-locating photovoltaic (PV) arrays and wind turbines can improve land-use efficiency, increase utilisation of grid infrastructure, and exploit complementary renewable energy resources. However, rotating wind turbine blades and yawing nacelles cast dynamic shadows on nearby PV modules, producing transient irradiance distributions that are difficult to capture with conventional static shading models.
This thesis presents a dynamic wind turbine shading framework developed within the PVMD Toolbox. The method extends the existing sensitivity-map workflow by introducing time-varying turbine orientations and a lookup-table approach for blade rotation. To reduce computational cost, a Spherical Half-Space Test is introduced, which transforms the shading calculation from a ray–geometry intersection problem into an angular containment problem on a unit sphere. Validation against the original ray-tracing implementation showed an annual energy-yield deviation of 0.09%, while reducing total simulation runtime by approximately 59×.
The framework was applied to a 240-module PV array at the Westermeerdijk PV–wind co-location case study in the Netherlands. Dynamic turbine shading generated rapidly varying irradiance distributions, repeated bypass-diode activation, changing module and string I–V characteristics, and multi-peak P–V curves. Nevertheless, the annual array-level impact remained limited: the total dynamic shading loss was approximately 2.0%.
The results show that dynamic modelling is essential for resolving transient operating conditions and spatial loss patterns, even when annual array-level yield losses are modest. ...
This thesis presents a dynamic wind turbine shading framework developed within the PVMD Toolbox. The method extends the existing sensitivity-map workflow by introducing time-varying turbine orientations and a lookup-table approach for blade rotation. To reduce computational cost, a Spherical Half-Space Test is introduced, which transforms the shading calculation from a ray–geometry intersection problem into an angular containment problem on a unit sphere. Validation against the original ray-tracing implementation showed an annual energy-yield deviation of 0.09%, while reducing total simulation runtime by approximately 59×.
The framework was applied to a 240-module PV array at the Westermeerdijk PV–wind co-location case study in the Netherlands. Dynamic turbine shading generated rapidly varying irradiance distributions, repeated bypass-diode activation, changing module and string I–V characteristics, and multi-peak P–V curves. Nevertheless, the annual array-level impact remained limited: the total dynamic shading loss was approximately 2.0%.
The results show that dynamic modelling is essential for resolving transient operating conditions and spatial loss patterns, even when annual array-level yield losses are modest. ...
Co-locating photovoltaic (PV) arrays and wind turbines can improve land-use efficiency, increase utilisation of grid infrastructure, and exploit complementary renewable energy resources. However, rotating wind turbine blades and yawing nacelles cast dynamic shadows on nearby PV modules, producing transient irradiance distributions that are difficult to capture with conventional static shading models.
This thesis presents a dynamic wind turbine shading framework developed within the PVMD Toolbox. The method extends the existing sensitivity-map workflow by introducing time-varying turbine orientations and a lookup-table approach for blade rotation. To reduce computational cost, a Spherical Half-Space Test is introduced, which transforms the shading calculation from a ray–geometry intersection problem into an angular containment problem on a unit sphere. Validation against the original ray-tracing implementation showed an annual energy-yield deviation of 0.09%, while reducing total simulation runtime by approximately 59×.
The framework was applied to a 240-module PV array at the Westermeerdijk PV–wind co-location case study in the Netherlands. Dynamic turbine shading generated rapidly varying irradiance distributions, repeated bypass-diode activation, changing module and string I–V characteristics, and multi-peak P–V curves. Nevertheless, the annual array-level impact remained limited: the total dynamic shading loss was approximately 2.0%.
The results show that dynamic modelling is essential for resolving transient operating conditions and spatial loss patterns, even when annual array-level yield losses are modest.
This thesis presents a dynamic wind turbine shading framework developed within the PVMD Toolbox. The method extends the existing sensitivity-map workflow by introducing time-varying turbine orientations and a lookup-table approach for blade rotation. To reduce computational cost, a Spherical Half-Space Test is introduced, which transforms the shading calculation from a ray–geometry intersection problem into an angular containment problem on a unit sphere. Validation against the original ray-tracing implementation showed an annual energy-yield deviation of 0.09%, while reducing total simulation runtime by approximately 59×.
The framework was applied to a 240-module PV array at the Westermeerdijk PV–wind co-location case study in the Netherlands. Dynamic turbine shading generated rapidly varying irradiance distributions, repeated bypass-diode activation, changing module and string I–V characteristics, and multi-peak P–V curves. Nevertheless, the annual array-level impact remained limited: the total dynamic shading loss was approximately 2.0%.
The results show that dynamic modelling is essential for resolving transient operating conditions and spatial loss patterns, even when annual array-level yield losses are modest.