Free-Surface Time-Series Generation for Wave Energy Applications

Mérigaud, Alexis; Ringwood, John V.

doi:10.1109/joe.2017.2691199

Cited by 68 publications

(47 citation statements)

References 9 publications

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“…The ACVF can be obtained directly from the spectral density function (SDF), since SDF and ACVF are a Fourier transform pair, according to the Wiener-Khintchine theorem. Therefore, the statistical properties of a stationary Gaussian sea are fully characterized by its ACVF or, equivalently, by its SDF [19]. As an example, Fig.…”

Section: A Theoretically Optimal Predictormentioning

confidence: 99%

Short-Term Forecasting of Sea Surface Elevation for Wave Energy Applications: The Autoregressive Model Revisited

Peña-Sanchez

Mérigaud

Ringwood

2020

IEEE J. Oceanic Eng.

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For wave energy converter control applications, autoregressive (AR) models have been proposed as a simple wave forecasting method, solely based on measured or estimated values of the past wave elevation (or excitation force) signal. Using offlinefiltered wave time series, AR models can achieve accurate forecasts several wave periods into the future. In this paper, the AR method is examined from the broader perspective of linear, Gaussian processes. In particular, assuming Gaussian waves and perfect knowledge of the wave spectrum, it is possible to derive a theoreticallyoptimal wave elevation predictor. It is shown that, in realistic situations, AR models can achieve a performance comparable to the theoretically optimal, spectrum-based predictor, both in simulated wave time series and using actual wave elevation records.

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Section: A Theoretically Optimal Predictormentioning

confidence: 99%

Short-Term Forecasting of Sea Surface Elevation for Wave Energy Applications: The Autoregressive Model Revisited

Peña-Sanchez

Mérigaud

Ringwood

2020

IEEE J. Oceanic Eng.

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“…One usual assumption for the numerical generation of the wave excitation force  ( ) in many ocean engineering applications is that it can be expressed as the sum of harmonics of the fundamental frequency 0 (Mérigaud & Ringwood, 2017). The following proposition allows the computation of the average power as a simple vector product, by further exploiting the properties of the moment-based characterisation.…”

Section: Moment-based Wec Control Formulationmentioning

confidence: 99%

Energy-maximising control of wave energy converters using a moment-domain representation

Faedo

Scarciotti

Astolfi

et al. 2018

Control Engineering Practice

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A B S T R A C TWave Energy Converters (WECs) have to be controlled to ensure maximum energy extraction from waves while considering, at the same time, physical constraints on the motion of the real device and actuator characteristics. Since the control objective for WECs deviates significantly from the traditional reference ''tracking'' problem in classical control, the specification of an optimal control law, that optimises energy absorption under different sea-states, is non-trivial. Different approaches based on optimal control methodologies have been proposed for this energy-maximising objective, with considerable diversity on the optimisation formulation. Recently, a novel mathematical tool to compute the steady-state response of a system has been proposed: the moment-based phasor transform. This mathematical framework is inspired by the theory of model reduction by moment-matching and considers both continuous and discontinuous inputs, depicting an efficient and closed-form method to compute such a steady-state behaviour. This study approaches the design of an energy-maximising optimal controller for a single WEC device by employing the moment-based phasor transform, describing a pioneering application of this novel moment-matching mathematical scheme to an optimal control problem. Under this framework, the energy-maximising optimal control formulation is shown to be a strictly concave quadratic program, allowing the application of well-known efficient real-time algorithms. (N. Faedo). minimise the risk of damage, such an optimisation strategy must take into account the physical limitations of the whole conversion chain. Such an optimisation procedure can be achieved by designing an optimal controller that accomplishes such objectives.A considerable number of optimal control formulations and methods have been studied and developed to maximise the energy extraction process from WECs, with extensive reviews available, for example in Ringwood, Bacelli, and Fusco (2014). One particular popular wave energy control strategy is Model Predictive Control (MPC). The success of MPC on the energy-maximising control is mainly due to its ability to handle physical constraints systematically and within a finite horizon optimisation process. While MPC applied to WECs also involves a mathematical model, a typical receding horizon strategy, and can deal with system constraints, the objective function contrasts significantly with the one related to the usual set-point tracking objective. Rather, a converted energy-maximising objective, consistent with the definition https://doi.

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“…where V i denotes the moment-domain equivalent of the velocity of the i-th device. Remark 4: The selection of the set F = {pω 0 } f p=1 is a standard assumption for the numerical generation of ocean waves [13]. Proposition 3 shows that, under our moment-based strategy, the objective function of (8) can be computed as the sum of N inner-product operations in R 1×N ν .…”

Section: Moment-based Wec Array Formulationmentioning

confidence: 99%

“…This refers to the objective function(13) under the assumption that the constraints in the motion of the device defined in(12) are not considered in the formulation 7. Note that the moment-domain equivalent of the position x i (t) can be expressed[14] as V i (I N ⊗ S −1 ).…”

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confidence: 99%

Moment-based constrained optimal control of an array of wave energy converters

Faedo

Scarciotti

Astolfi

et al. 2019

2019 American Control Conference (ACC)

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The roadmap to a successful commercialisation of wave energy inherently incorporates the concept of an array or farm of Wave Energy Converters (WECs). These interacting hydrodynamic structures require an optimised process that can ensure the maximum extraction of time-averaged energy from ocean waves, while respecting the physical limitations of each device and actuator characteristics. Recently, a novel optimal control framework based on the concept of moment, for a single WEC device, has been introduced in [1]. Such a strategy offers an energy-maximising computationally efficient solution that can systematically incorporate state and input constraints. This paper presents the mathematical extension of the optimal control framework of [1] to the case where an array of WECs is considered, providing an efficient solution that exploits the hydrodynamic interaction between devices to maximise the total absorbed energy.

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Free-Surface Time-Series Generation for Wave Energy Applications

Cited by 68 publications

References 9 publications

Short-Term Forecasting of Sea Surface Elevation for Wave Energy Applications: The Autoregressive Model Revisited

Short-Term Forecasting of Sea Surface Elevation for Wave Energy Applications: The Autoregressive Model Revisited

Energy-maximising control of wave energy converters using a moment-domain representation

Moment-based constrained optimal control of an array of wave energy converters

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