Modelling the impact of offshore wind farms on safety radars onboard oil and gas platforms

Laith Danoon; Waleed Al Mashhadani; Anthony Brown

doi:10.1049/iet-map.2016.0835

Modelling the impact of offshore wind farms on safety radars onboard oil and gas platforms

Laith Danoon, Waleed Al Mashhadani, Anthony Brown

Research output: Contribution to journal › Article › peer-review

Abstract

Radar Early Warning Systems (REWS) are an important part of the protection and management infrastructure for offshore Oil and Gas (O&G) platforms and subsea assests. REWS are typically installed onboard the O&G platforms to monitor and track nearby surface traffic and alert operators of potential collision threats. However, wind turbines located near REWS have large and varying radar returns which may interfere with the system by mask nearby targets and increasing the detection threshold over the wind farm causing loss of detection of targets of interest. This paper will introduce a modelling tool and present modelling results for a generic 5MW wind turbines nearfield scattering, generic wind farm returns and illustrate the effects of wind farm returns on the detection threshold. The paper will also propose a theoretical approach to minimise the adverse effects of wind farms on the Constant False Alarm Rate (CFAR) threshold. Finally, field measurements of REWS operating near wind farms are shown and the improvement of using a modified CFAR processing is demonstrated.

Original language	English
Number of pages	8
Journal	IEEE Transactions on Antennas and Propagation
Early online date	12 Sept 2017
DOIs	https://doi.org/10.1049/iet-map.2016.0835
Publication status	E-pub ahead of print - 12 Sept 2017

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10.1049/iet-map.2016.0835Licence: CC BY-NC

Cite this

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title = "Modelling the impact of offshore wind farms on safety radars onboard oil and gas platforms",

abstract = "Radar Early Warning Systems (REWS) are an important part of the protection and management infrastructure for offshore Oil and Gas (O&G) platforms and subsea assests. REWS are typically installed onboard the O&G platforms to monitor and track nearby surface traffic and alert operators of potential collision threats. However, wind turbines located near REWS have large and varying radar returns which may interfere with the system by mask nearby targets and increasing the detection threshold over the wind farm causing loss of detection of targets of interest. This paper will introduce a modelling tool and present modelling results for a generic 5MW wind turbines nearfield scattering, generic wind farm returns and illustrate the effects of wind farm returns on the detection threshold. The paper will also propose a theoretical approach to minimise the adverse effects of wind farms on the Constant False Alarm Rate (CFAR) threshold. Finally, field measurements of REWS operating near wind farms are shown and the improvement of using a modified CFAR processing is demonstrated. ",

author = "Laith Danoon and Mashhadani, {Waleed Al} and Anthony Brown",

year = "2017",

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doi = "10.1049/iet-map.2016.0835",

language = "English",

journal = "IEEE Transactions on Antennas and Propagation ",

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T1 - Modelling the impact of offshore wind farms on safety radars onboard oil and gas platforms

AU - Danoon, Laith

AU - Mashhadani, Waleed Al

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Y1 - 2017/9/12

N2 - Radar Early Warning Systems (REWS) are an important part of the protection and management infrastructure for offshore Oil and Gas (O&G) platforms and subsea assests. REWS are typically installed onboard the O&G platforms to monitor and track nearby surface traffic and alert operators of potential collision threats. However, wind turbines located near REWS have large and varying radar returns which may interfere with the system by mask nearby targets and increasing the detection threshold over the wind farm causing loss of detection of targets of interest. This paper will introduce a modelling tool and present modelling results for a generic 5MW wind turbines nearfield scattering, generic wind farm returns and illustrate the effects of wind farm returns on the detection threshold. The paper will also propose a theoretical approach to minimise the adverse effects of wind farms on the Constant False Alarm Rate (CFAR) threshold. Finally, field measurements of REWS operating near wind farms are shown and the improvement of using a modified CFAR processing is demonstrated.

AB - Radar Early Warning Systems (REWS) are an important part of the protection and management infrastructure for offshore Oil and Gas (O&G) platforms and subsea assests. REWS are typically installed onboard the O&G platforms to monitor and track nearby surface traffic and alert operators of potential collision threats. However, wind turbines located near REWS have large and varying radar returns which may interfere with the system by mask nearby targets and increasing the detection threshold over the wind farm causing loss of detection of targets of interest. This paper will introduce a modelling tool and present modelling results for a generic 5MW wind turbines nearfield scattering, generic wind farm returns and illustrate the effects of wind farm returns on the detection threshold. The paper will also propose a theoretical approach to minimise the adverse effects of wind farms on the Constant False Alarm Rate (CFAR) threshold. Finally, field measurements of REWS operating near wind farms are shown and the improvement of using a modified CFAR processing is demonstrated.

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M3 - Article

JO - IEEE Transactions on Antennas and Propagation

JF - IEEE Transactions on Antennas and Propagation

ER -

Modelling the impact of offshore wind farms on safety radars onboard oil and gas platforms

Abstract

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