A Study of the Prediction Requirements in Real-Time Control of Wave Energy Converters

Fusco, Francesco; Ringwood, John V.

doi:10.1109/tste.2011.2170226

Cited by 101 publications

(81 citation statements)

References 23 publications

(59 reference statements)

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“…The excitation force can be written as sum of the predictiond(k) and the prediction errord(k), d(k) =d(k)+d(k). The prediction of the excitation force is obtained from the convolution of h eη (t) by the short-term wave elevation forecastingη(t), as explained in Fusco and Ringwood (2012). The prediction errord(k) is assumed to be a zero mean Gaussian white noise.…”

Section: Model Predictive Controlmentioning

confidence: 99%

“…Requirements for sea state prediction is widely discussed in Schoen et al (2011). In Fusco and Ringwood (2012) and Fusco and Ringwood (2010), different prediction algorithms for short term wave forecasting are presented. Linear and non-linear MPC for different types of wave energy absorbers are introduced in Cretel et al (2011);Brekken (2011);Hals et al (2010); Richter et al (2013), where it is indicated that the MPC is a promising controller for increasing the power outtake of WECs.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Model Predictive Control of Buoy Type Wave Energy Converter

Soltani

Sichani

Mirzaei

2014

IFAC Proceedings Volumes

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The paper introduces the Wavestar wave energy converter and presents the implementation of model predictive controller that maximizes the power generation. The ocean wave power is extracted using a hydraulic electric generator which is connected to an oscillating buoy. The power generator is an additive device attached to the buoy which may include damping, stiffness or similar terms hence will affect the dynamic motion of the buoy. Therefore such a device can be seen as a closed-loop controller. The objective of the wave energy converter is to harvest as much energy from sea as possible. The straight forward solution to this maximization problem is achieved by maximizing the instantaneous range of motion of the buoy. The buoy as a single degree of freedom oscillator will undergo its maximum movements when it is in resonance with the sea state. Hence the best solution to the problem is achieved by forcing this condition. In the paper the theoretical framework for this principal is shown. The optimal controller requires information of the sea state for infinite horizon which is not applicable. Model Predictive Controllers (MPC) can have finite horizon which crosses out this requirement. This approach is then taken into account and an MPC controller is designed for a model wave energy converter and implemented on a numerical example. Further, the power outtake of this controller is compared to the optimal controller as an indicator of the performance of the designed controller.

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Section: Model Predictive Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Model Predictive Control of Buoy Type Wave Energy Converter

Soltani

Sichani

Mirzaei

2014

IFAC Proceedings Volumes

View full text Add to dashboard Cite

show abstract

“…In the ideal case, assuming the wave excitation is known completely into the future, the optimisation is performed over an infinitely long the time interval, that is for T ! þ1; however, it has been shown [34] that a limited horizon suffices to achieve close to optimal energy absorption. As a consequence, the real-time implementation of the control algorithm can be performed in a receding horizon fashion, as described in [35], where future knowledge of either wave elevation or excitation force, up to time T ahead, is obtained by prediction.…”

Section: Energy Maximising Controlmentioning

confidence: 99%

Constrained control of arrays of wave energy devices

Bacelli

Ringwood

2013

International Journal of Marine Energy

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a b s t r a c tIt is well known in the literature that the total absorbed energy of a farm of wave energy converter depends, within a wide range of variability, on the hydrodynamic interaction between the individual devices. Several studies have addressed the problem of controlling the wave energy converters so as to exploit the positive interaction between the devices in order to increase the total amount of absorbed energy.This paper studies two types of control systems for array of wave energy converters: the first is similar to the classical optimal control which uses the complete (linear) hydrodynamic model of the array and information about the status (velocity) of the other devices, while the second is a suboptimal control systems which calculates the optimal motion while neglecting completely the interaction between the devices. Most importantly the comparison is carried out considering the effects of constraints on the maximum allowed oscillation amplitude and PTO force.

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“…The control strategies are presented in the frequency domain and their implementation in time domain is not trivial, especially in the case of reactive control [37]. This is because the direct translation of the equations from the frequency domain to the time domain leads to non-causal systems where it is necessary to use prediction algorithms [58]. Although the use of purely resistive controls implies lower power extraction, they are worth considering because they are more robust and easier to implement in the time domain (i.e., by using an adaptive control of the type gain scheduling [50]).…”

Section: Parametric Analysis 5: Energy Extraction Control Strategymentioning

confidence: 99%

Design Parameters Analysis of Point Absorber WEC via an evolutionary-algorithm-based Dimensioning Tool

et al. 2015

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Abstract:Wave energy conversion has an essential difference from other renewable energies since the dependence between the devices design and the energy resource is stronger. Dimensioning is therefore considered a key stage when a design project of Wave Energy Converters (WEC) is undertaken. Location, WEC concept, Power Take-Off (PTO) type, control strategy and hydrodynamic resonance considerations are some of the critical aspects to take into account to achieve a good performance. The paper proposes an automatic dimensioning methodology to be accomplished at the initial design project stages and the following elements are described to carry out the study: an optimization design algorithm, its objective functions and restrictions, a PTO model, as well as a procedure to evaluate the WEC energy production. After that, a parametric analysis is included considering different combinations of the key parameters previously introduced. A variety of study cases are analysed from the point of view of energy production for different design-parameters and all of them are compared with a reference case. Finally, a discussion is presented based on the results obtained, and some recommendations to face the WEC design stage are given.

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A Study of the Prediction Requirements in Real-Time Control of Wave Energy Converters

Cited by 101 publications

References 23 publications

Model Predictive Control of Buoy Type Wave Energy Converter

Model Predictive Control of Buoy Type Wave Energy Converter

Constrained control of arrays of wave energy devices

Design Parameters Analysis of Point Absorber WEC via an evolutionary-algorithm-based Dimensioning Tool

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