Validating a simulation environment for floating lidar systems

Bischoff, Oliver; Yu, Wei; Gottschall, Julia; Cheng, Po Wen

doi:10.1088/1742-6596/1037/5/052036

Cited by 8 publications

(8 citation statements)

References 1 publication

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“…Towards this purpose, they need to integrate in the same device an energy generating system, a data-logging system, a communications system, and a lidar motional attitude measurement system along with the DWL [7]. These needs were satisfied according to the wind industry requirements, following a roadmap for the commercial acceptance of floating LIDAR technology [8], and guides for the best practices for their application [9].…”

Section: Introductionmentioning

confidence: 99%

Enhanced Dual Filter for Floating Wind Lidar Motion Correction: The Impact of Wind and Initial Scan Phase Models

2022

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An enhanced filter for floating Doppler wind lidar motion correction is presented. The filter relies on an unscented Kalman filter prototype for floating-lidar motion correction without access to the internal line-of-sight measurements of the lidar. In the present work, we implement a new architecture based on two cooperative estimation filters and study the impact of different wind and initial scan phase models on the filter performance in the coastal environment of Barcelona. Two model combinations are considered: (i) a basic random walk model for both the wind turbulence and the initial scan phase and (ii) an auto-regressive model for wind turbulence along with a uniform circular motion model for the scan phase. The filter motion-correction performance using each of the above models was evaluated with reference to a fixed lidar in different wind and motion scenarios (low- and high-frequency turbulence cases) recorded during a 25-day campaign at “Pont del Petroli”, Barcelona, by clustered statistical analysis. The auto-regressive wind model and the uniform circular motion phase model permitted the filter to overcome divergence in all wind and motion scenarios. The statistical indicators comparing both instruments showed overall improvement. The mean deviation increased from 1.62% (without motion correction) to −0.07% (with motion correction), while the root-mean-square error decreased from 1.87% to 0.58%, and the determination coefficient (R2) improved from 0.90 to 0.96.

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Section: Introductionmentioning

confidence: 99%

Enhanced Dual Filter for Floating Wind Lidar Motion Correction: The Impact of Wind and Initial Scan Phase Models

2022

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“…Offshore wind resource assessment based on in situ meteorological wind observations in the Baltic and North seas (see review in Sempreviva et al, 2008), Italy (Casale et al, 2010), and Malta (Farrugia and Sant, 2016) provides local information. Furthermore, the meteorological observations are useful for comparison to model results to select suitable atmospheric model setup and to assess the model performance (Jimenez et al, 2006;Berge et al, 2009;Hahmann et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…There is potential to also compare model results and satellite data to wind profiling lidar (light detection and ranging) data at offshore platforms (Hasager et al, 2013) and floating wind profile lidar systems (OWA, 2018;Bischoff et al, 2018). These are local point data similar to buoy data and meteorological mast data.…”

Section: Introductionmentioning

confidence: 99%

Europe's offshore winds assessed with synthetic aperture radar, ASCAT and WRF

et al. 2020

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Abstract. Europe's offshore wind resource mapping is part of the New European Wind Atlas (NEWA) international consortium effort. This study presents the results of analysis of synthetic aperture radar (SAR) ocean wind maps based on Envisat and Sentinel-1 with a brief description of the wind retrieval process and Advanced Scatterometer (ASCAT) ocean wind maps. The wind statistics at 10 and 100 m above mean sea level (a.m.s.l.) height using an extrapolation procedure involving simulated long-term stability over oceans are presented for both SAR and ASCAT. Furthermore, the Weather Research and Forecasting (WRF) offshore wind atlas of NEWA is presented. This has 3 km grid spacing with data every 30 min for 30 years from 1989 to 2018, while ASCAT has 12.5 km and SAR has 2 km grid spacing. Offshore mean wind speed maps at 100 m a.m.s.l. height from ASCAT, SAR, WRF and ERA5 at a European scale are compared. A case study on offshore winds near Crete compares SAR and WRF for flow from the north, west and all directions. The paper highlights the ability of the WRF model to simulate the overall European wind climatology and the near-coastal winds constrained by the resolution of the coastal topography in the WRF model simulations.

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“…Wind sensors such as Light Detection and Ranging (LiDAR) module mounted on weather buoys play a key role in obtaining reliable measurements of the wind profile and surface wave properties [4,5]. The most practical and commercialized stabilizers used for this purpose are the gyroscopic and gimbal types, which are large, heavy and costly and require frequent maintenance [6,7].…”

Section: Introductionmentioning

confidence: 99%

Design, assessment and evaluation of structural stabilization system for weather buoys using a moving foil

2020

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This paper proposes a novel, simple and high-efficient submerged structural stabilization system for a self-stabilizing buoy that provides a stable platform for oceanographic and meteorological sensors. The proposed stabilization system is a Seesaw-like Tuned Mass Damper (STMD) combined with a foil and is designed in a way to harvest the activation energy from incoming waves. A fixed rudder in the rear underside of the buoy, as well as physical properties of the buoy, help to keep its balance in yaw and roll directions while encountering lateral waves. Therefore, the orientational stabilization of the whole structure is achieved by controlling only the pitch deviation. The proposed model is then simulated in a marine dynamic analysis software. Two different shapes of a thin rod and a foil were proposed for the sliding mass (slider) of the STMD and their performances are investigated and compared to each other in two different modes of passive and active control. In the passive mode, different mass ratios were conducted for the thin rod-shaped slider (i.e., a ratio of the effective mass of the stabilizing system to that of the whole structure) and a mass ratio of 8% could suppress the pitch deviation up to 81.3% in the resonance condition. The same STMD system with a mass ratio of 2% suppresses the pitch deviation by only 7%. In the active mode, the STMD with a thin rod-shaped slider and a mass ratio of 8% exhibits only 49.1% suppression effect in a multiwave condition. However, by changing the shape of the slider to a foil while controlling its angle of attack (AOA) mechanically, the system with the mass ratios of 2% and 8% could suppress the pitch deviation of the buoy up to 69.4% and 79.1%, respectively.

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Validating a simulation environment for floating lidar systems

Cited by 8 publications

References 1 publication

Enhanced Dual Filter for Floating Wind Lidar Motion Correction: The Impact of Wind and Initial Scan Phase Models

Enhanced Dual Filter for Floating Wind Lidar Motion Correction: The Impact of Wind and Initial Scan Phase Models

Europe's offshore winds assessed with synthetic aperture radar, ASCAT and WRF

Design, assessment and evaluation of structural stabilization system for weather buoys using a moving foil

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