A Fully Coupled Wave-to-Wire Model of an Array of Wave Energy Converters

Forehand, David; Kiprakis, Aristides; Nambiar, Anup; Wallace, Alfred Russel

doi:10.1109/tste.2015.2476960

Cited by 56 publications

(44 citation statements)

References 38 publications

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“…A number of W2W models have been presented in the literature for different types of WECs: overtopping converters [6], oscillating water columns (OWCs) [7], or wave-activated converters with different PTO strategies, e.g., hydraulic [8][9][10][11][12][13], mechanical [1,14], magnetic [13], or linear generators [15,16].…”

Section: Existing Wave-to-wire Modelsmentioning

confidence: 99%

“…Among the different W2W models found in the literature, only [11,12] include losses or nonlinear forces are included in the hydrodynamic model, incorporating viscous losses and nonlinear restoring force, respectively. Different technologies have been suggested for the transmission stage, with the hydraulic system as the most utilised one.…”

mentioning

confidence: 99%

“…In relation to the generation stage, dynamics of rotary electric generators have been incorporated in [1,10,[12][13][14], although the transient behaviour is ignored in [13]. The other studies utilise constant torque and/or efficiency values to emulate the generator.…”

mentioning

confidence: 99%

“…Garcia Rosa [10] studies voltage and frequency fluctuations of the outgoing power signal, [12] includes a power flow solver for the array of WECs, and [1] studies rapid fluctuations in grid voltage (referred to as flicker), reactive power and harmonic corrections and fault ride-through response.…”

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confidence: 99%

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

2016

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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.

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Section: Existing Wave-to-wire Modelsmentioning

confidence: 99%

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

2016

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“…The radiation torque is calculated using a state space model, with rational approximation to the radiation convolution, implemented in Simulink by Forehand [22]. The viscous drag torque is calculated using the method implemented by Babarit et al [26].…”

Section: Appendix B Owsc Simulationsmentioning

confidence: 99%

Wave Energy Converter Annual Energy Production Uncertainty Using Simulations

Hiles¹,

Beatty²,

Andrés

2016

JMSE

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Critical to evaluating the economic viability of a wave energy project is: (1) a robust estimate of the electricity production throughout the project lifetime and (2) an understanding of the uncertainty associated with said estimate. Standardization efforts have established mean annual energy production (MAEP) as the metric for quantification of wave energy converter (WEC) electricity production and the performance matrix approach as the appropriate method for calculation. General acceptance of a method for calculating the MAEP uncertainty has not yet been achieved. Several authors have proposed methods based on the standard engineering approach to error propagation, however, a lack of available WEC deployment data has restricted testing of these methods. In this work the magnitude and sensitivity of MAEP uncertainty is investigated. The analysis is driven by data from simulated deployments of 2 WECs of different operating principle at 4 different locations. A Monte Carlo simulation approach is proposed for calculating the variability of MAEP estimates and is used to explore the sensitivity of the calculation. The uncertainty of MAEP ranged from 2%-20% of the mean value. Of the contributing uncertainties studied, the variability in the wave climate was found responsible for most of the uncertainty in MAEP. Uncertainty in MAEP differs considerably between WEC types and between deployment locations and is sensitive to the length of the input data-sets. This implies that if a certain maximum level of uncertainty in MAEP is targeted, the minimum required lengths of the input data-sets will be different for every WEC-location combination.

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Advanced Materials and Devices for Hydropower and Ocean Energy

Tong¹

2018

Introduction to Materials for Advanced Energy Systems

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A Fully Coupled Wave-to-Wire Model of an Array of Wave Energy Converters

Cited by 56 publications

References 38 publications

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

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

Wave Energy Converter Annual Energy Production Uncertainty Using Simulations

Advanced Materials and Devices for Hydropower and Ocean Energy

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