Coordinated control of an underwater glider fleet in an adaptive ocean sampling field experiment in Monterey Bay

Naomi E. Leonard; Derek A. Paley; Russ E. Davis; David M. Fratantoni; Francois Lekien; Fumin Zhang

doi:10.1002/rob.20366

Underwater Glider Networks for Adaptive Ocean Sampling

10.21236/ada620403 ◽

2003 ◽

Author(s):

Naomi Leonard ◽

Clarence Rowley ◽

Jerrold Marsden

Keyword(s):

Underwater Glider ◽

Ocean Sampling

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Implementation and Analyses of Yaw Based Coordinated Control of Wind Farms

Energies ◽

10.3390/en12071266 ◽

2019 ◽

Vol 12 (7) ◽

pp. 1266 ◽

Cited By ~ 6

Author(s):

Tanvir Ahmad ◽

Abdul Basit ◽

Muneeb Ahsan ◽

Olivier Coupiac ◽

Nicolas Girard ◽

...

Keyword(s):

Power Generation ◽

Field Experiment ◽

Intelligent Control ◽

Wind Farm ◽

Control Strategies ◽

Wind Farms ◽

Coordinated Control ◽

Net Production ◽

Wake Effects ◽

The Impact

This paper presents, with a live field experiment, the potential of increasing wind farm power generation by optimally yawing upstream wind turbine for reducing wake effects as a part of the SmartEOLE project. Two 2MW turbines from the Le Sole de Moulin Vieux (SMV) wind farm are used for this purpose. The upstream turbine (SMV6) is operated with a yaw offset ( α ) in a range of − 12 ° to 8° for analysing the impact on the downstream turbine (SMV5). Simulations are performed with intelligent control strategies for estimating optimum α settings. Simulations show that optimal α can increase net production of the two turbines by more than 5%. The impact of α on SMV6 is quantified using the data obtained during the experiment. A comparison of the data obtained during the experiment is carried out with data obtained during normal operations in similar wind conditions. This comparison show that an optimum or near-optimum α increases net production by more than 5% in wake affected wind conditions, which is in confirmation with the simulated results.

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Forecasting and reanalysis in the Monterey Bay/California Current region for the Autonomous Ocean Sampling Network-II experiment

Deep Sea Research Part II Topical Studies in Oceanography ◽

10.1016/j.dsr2.2008.08.010 ◽

2009 ◽

Vol 56 (3-5) ◽

pp. 127-148 ◽

Cited By ~ 40

Author(s):

P.J. Haley ◽

P.F.J. Lermusiaux ◽

A.R. Robinson ◽

W.G. Leslie ◽

O. Logoutov ◽

...

Keyword(s):

California Current ◽

Monterey Bay ◽

Sampling Network ◽

Current Region ◽

Ocean Sampling

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Multiscale Processes and Nonlinear Dynamics of the Circulation and Upwelling Events off Monterey Bay

Journal of Physical Oceanography ◽

10.1175/2008jpo3950.1 ◽

2009 ◽

Vol 39 (2) ◽

pp. 290-313 ◽

Cited By ~ 14

Author(s):

X. San Liang ◽

Allan R. Robinson

Keyword(s):

Large Scale ◽

Hydrodynamic Instability ◽

Coastal Region ◽

Complex Surface ◽

Finite Amplitude ◽

Monterey Bay ◽

Mesoscale Structures ◽

Multiscale Dynamics ◽

Layer Flow ◽

Ocean Sampling

Abstract The nonlinear multiscale dynamics of the Monterey Bay circulation during the Second Autonomous Ocean Sampling Network (AOSN-II) Experiment (August 2003) is investigated in an attempt to understand the complex processes underlying the highly variable ocean environment of the California coastal region. Using a recently developed methodology, the localized multiscale energy and vorticity analysis (MS-EVA) and the MS-EVA-based finite-amplitude hydrodynamic instability theory, the processes are reconstructed on three mutually exclusive time subspaces: a large-scale window, a mesoscale window, and a submesoscale window. The ocean is found to be most energetic in the upper layers, and the temporal mesoscale structures are mainly trapped above 200 m. Through exploring the nonlinear window–window interactions, it is found that the dynamics underlying the complex surface circulation is characterized by a well-organized, self-sustained bimodal instability structure: a Bay mode and a Point Sur mode, which are located near Monterey Bay and west of Point Sur, respectively. Both modes are of mixed types, but they are distinctly different in dynamics. The former is established when the wind relaxes, while the latter is directly driven by the wind. Either way, the wind instills energy into the ocean, which is stored within the large-scale window and then released to fuel temporal mesoscale processes. Upon wind relaxation, the generated mesoscale structures propagate northward along the coastline, in a form with dispersion properties similar to that of a free thermocline-trapped coastal-trapped wave. Between these two modes, a secondary instability is identified in the surface layer during 15–21 August, transferring energy to the temporal submesoscale window. Also studied is the deep-layer flow, which is unstable all the time throughout the experiment within the Bay and north of the deep canyon. It is observed that the deep temporal mesoscale flow within the Bay may derive its energy from the submesoscale window as well as from the large-scale window. This study provides a real ocean example of how secondary upwelling can be driven by winds through nonlinear instability and how winds may excite the ocean via an avenue distinctly different from the classical paradigms.

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Preparing to predict: The Second Autonomous Ocean Sampling Network (AOSN-II) experiment in the Monterey Bay

Deep Sea Research Part II Topical Studies in Oceanography ◽

10.1016/j.dsr2.2008.08.013 ◽

2009 ◽

Vol 56 (3-5) ◽

pp. 68-86 ◽

Cited By ~ 86

Author(s):

S.R. Ramp ◽

R.E. Davis ◽

N.E. Leonard ◽

I. Shulman ◽

Y. Chao ◽

...

Keyword(s):

Monterey Bay ◽

Sampling Network ◽

Ocean Sampling

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Underwater Glider Reliability and Implications for Survey Design

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-13-00138.1 ◽

2014 ◽

Vol 31 (12) ◽

pp. 2858-2870 ◽

Cited By ~ 21

Author(s):

Mario Brito ◽

David Smeed ◽

Gwyn Griffiths

Keyword(s):

Survey Design ◽

Underwater Glider ◽

Risk Profiles ◽

Underwater Gliders ◽

Sampling Network ◽

Significant Difference ◽

Hard Evidence ◽

Ocean Sampling

Abstract It has been 20 years since the concept of the Autonomous Ocean Sampling Network (AOSN) was first introduced. This vision has been brought closer to reality with the introduction of underwater gliders. While in terms of functionality the underwater glider has shown to be capable of meeting the AOSN vision, in terms of reliability there is no communitywide hard evidence on whether persistent presence is currently being achieved. This paper studies the reliability of underwater gliders in order to assess the feasibility of using these platforms for future AOSN. The data used are taken from nonunderwater glider developers, which consisted of 205 glider deployments by 12 European laboratories between 2008 and 2012. Risk profiles were calculated for two makes of deep underwater gliders; there is no statistically significant difference between them. Regardless of the make, the probability of a deep underwater glider surviving a 90-day mission without a premature mission end is approximately 0.5. The probability of a shallow underwater glider surviving a 30-day mission without a premature mission end is 0.59. This implies that to date factors other than the energy available are preventing underwater gliders from achieving their maximum capability. This reliability information was used to quantify the likelihood of two reported underwater glider surveys meeting the observation needs for a period of 6 months and to quantify the level of redundancy needed in order to increase the likelihood of meeting the observation needs.

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