Time domain model for a two-body heave converter: Model and applications

Andrés, Adrián de; Guanche, Raúl; Armesto, José A.; Vidal, C. R.; Losada, Íñigo J.

doi:10.1016/j.oceaneng.2013.06.019

Cited by 35 publications

(25 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…36 The hydrodynamic properties of the floater are identified once the values of A ∞ , h r and F h are known. Cummins' equation may be expressed in the frequency domain as 37,38 …”

Section: (A) Hydrodynamicsmentioning

confidence: 99%

Met‐ocean conditions influence on floating offshore wind farms power production

et al. 2015

View full text Add to dashboard Cite

Met-ocean conditions may affect the performance of a floating wind turbine, since a harsh climate could lead the system to exceed its operating thresholds and thus to force the machine shutdown.In this paper, it is a proposed methodology to evaluate the effect of met-ocean conditions on the long-term dynamic behaviour, and energy production, of a floating wind farm. For a sample of 500 MW farm located off the coast of Aberdeen (Scotland), 20 years of met-ocean data are generated by means of meteorological reanalysis techniques. A subset of 1000 hourly conditions is selected, by means of a maximum dissimilarity algorithm, and input to a dynamic floating wind turbine model. Numerical results are then interpolated for the whole set of met-ocean data, using radial basis functions. This approach allows to dramatically reduce the global computation time. Tower inclination and hub acceleration are chosen as relevant operating parameters: the former mainly depends on mean wind speed and direction, being largest at rated wind speed. The latter is also affected by significant wave height, and reaches its highest values when wind and waves are aligned. For each simulation, any machine exceeding the selected safety threshold is considered to be shut down. Assuming continuous operation, the average lifespan capacity factor of the farm is 50.2%; more restrictive tolerances result in a nonlinear reduction of the energy production. This approach may help both at the design and the operational stage, in determining the best trade-off between energy production and safe operation.

show abstract

“…36 The hydrodynamic properties of the floater are identified once the values of A ∞ , h r and F h are known. Cummins' equation may be expressed in the frequency domain as 37,38 …”

Section: (A) Hydrodynamicsmentioning

confidence: 99%

Met‐ocean conditions influence on floating offshore wind farms power production

et al. 2015

View full text Add to dashboard Cite

show abstract

“…The frequency range (in rad/s) is from 0.004 to 0.101 in increments of 0.7958, and the data is collected at 3-minute intervals. A bi-variate scatter diagram of significant wave height versus the peak period or energy period is usually used to asses the performance of a wave energy device or array of devices at a specific site [12,20,21]. To create a scatter diagram for the AMETS site, we sort each 3 minute data set according to H m0 and T e .…”

Section: Measured Wave Datamentioning

confidence: 99%

“…The optimal configurations are determined by the highest mean annual production for a specific control scheme and geometry. To produce this number for a WEC in a given wave 6 Copyright © 2014 by ASME climate is usually obtained by multiplying the power matrix for a given set of pairs (T e , H m0 ) by the power matrix of the device [12,20,21]. An example power matrix for a PT-tuned single device of Geometry II is shown in Fig.…”

Section: Yearly Average Power Outputmentioning

confidence: 99%

“…Furthermore, T is long enough for the simulation to reach a steady state where the transient response is no longer significant. Given the likelihood that the largest sea states will cause the device to go into survival mode, we set a criteria to exclude sea states with H m0 greater than the draft, similar to the procedure in [21]. This results in a zero power cut-off at H m0 = 6m and 3m, respectively for Geometries II and III.…”

Section: Yearly Average Power Outputmentioning

confidence: 99%

See 1 more Smart Citation

Control-Influenced Layout Optimization of Arrays of Wave Energy Converters

Balitsky

Bacelli

Ringwood

2014

Volume 9B: Ocean Renewable Energy

View full text Add to dashboard Cite

In this paper we compare the optimal configurations for an array of WECs given two control schemes, a real-time global control and a passive sea-state based tuning scheme. In a particular wave climate and array orientation with its axis normal to the prevailing wave direction, closely-spaced symmetrical arrays of 2, 3, 4, 5, and 6 cylinders of different radiative properties are simulated for varying inter-device separation distances. For each device and control type, we focus on the factors that influence the optimal layout, including number of devices, separating distance and angular spreading. The average annual power output is calculated for each optimal configuration.

show abstract

“…The focus of the present paper is on the control requirements of these intermediate conversion stages, so the wave resource assessment is beyond the scope of the paper. However, several methods for resource assessment have been suggested in the literature [2][3][4][5], which can be incorporated prior to the articulation of the device. Figure 2 illustrates a power take-off (PTO) system with the four conversion stages highlighting the potential control inputs that includes a hydraulic transmission system: The absorption stage comprises the conversion of wave motion into oscillating motion of the WEC.…”

Section: Introductionmentioning

confidence: 99%

A Review of Wave-to-Wire Models for Wave Energy Converters

2016

View full text Add to dashboard Cite

Control of wave energy converters (WECs) has been very often limited to hydrodynamic control to absorb the maximum energy possible from ocean waves. This generally ignores or significantly simplifies the performance of real power take-off (PTO) systems. However, including all the required dynamics and constraints in the control problem may considerably vary the control strategy and the power output. Therefore, this paper considers the incorporation into the model of all the conversion stages from ocean waves to the electricity network, referred to as wave-to-wire (W2W) models, and identifies the necessary components and their dynamics and constraints, including grid constraints. In addition, the paper identifies different control inputs for the different components of the PTO system and how these inputs are articulated to the dynamics of the system. Examples of pneumatic, hydraulic, mechanical or magnetic transmission systems driving a rotary electrical generator, and linear electric generators are provided.

show abstract

Time domain model for a two-body heave converter: Model and applications

Cited by 35 publications

References 11 publications

Met‐ocean conditions influence on floating offshore wind farms power production

Met‐ocean conditions influence on floating offshore wind farms power production

Control-Influenced Layout Optimization of Arrays of Wave Energy Converters

A Review of Wave-to-Wire Models for Wave Energy Converters

Contact Info

Product

Resources

About