Increases in the average power output of wave energy converters using quiescent period predictive control

Belmont, M.R.

doi:10.1016/j.renene.2010.05.001

Cited by 21 publications

(12 citation statements)

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“…It is known that for ε/0 (ε > 0) the optimal cost of the above unconstrained (in state) optimal control problem (i.e., the minimum of J ε ) converges to the minimum of the cost eE of the constrained optimal control problem (8), see [56]. Thus, for ε sufficiently small, we get a control input u that produces an amount of energy E as close as desired to the optimal energy E of the original constrained problem (8). To solve the optimization problem for J ε , we use Pontryagin's Minimum Principle (PMP) ([ [48], Ch.…”

Section: Optimal Control Analysismentioning

confidence: 93%

“…The traditional approach to these issues exploits short term statistical properties of the sea [6] but it has been shown [7,8] that doing so severely limits the average power that can be extracted. We address the above two problems by considering schemes designed to achieve optimal control.…”

Section: Introductionmentioning

confidence: 99%

“…The above control strategies do not use prediction of the forces acting on the WEC and thus inevitably lead to sub-optimal energy extraction. Since the early work [5,9,11] there have been a number of authors who have recognized the importance of DSWP in the control of a variety of floating body applications [7,8,17,37,38], but these have, as yet, not been incorporated into actual control schemes.…”

Section: Introductionmentioning

confidence: 99%

“…It has been shown that by using control strategies that incorporate these constraints, considerable increases in the energy output can be obtained without increasing the risk of damage [7,8]. The ability to handle constraints combined with the development of real time wave prediction methods has recently led to an interest in the use of model predictive control (MPC) for wave energy devices [43e45].…”

Section: Introductionmentioning

confidence: 99%

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Wave energy converter control by wave prediction and dynamic programming

et al. 2012

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This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues.Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. b s t r a c tWe demonstrate that deterministic sea wave prediction (DSWP) combined with constrained optimal control can dramatically improve the efficiency of sea wave energy converters (WECs), while maintaining their safe operation. We focus on a point absorber WEC employing a hydraulic/electric power take-off system. Maximizing energy take-off while minimizing the risk of damage is formulated as an optimal control problem with a disturbance input (the sea elevation) and with both state and input constraints. This optimal control problem is non-convex, which prevents us from using quadratic programming algorithms for the optimal solution. We demonstrate that the optimum can be achieved by bangebang control. This paves the way to adopt a dynamic programming (DP) algorithm to resolve the on-line optimization problem efficiently. Simulation results show that this approach is very effective, yielding at least a two-fold increase in energy output as compared with control schemes which do not exploit DSWP. This level of improvement is possible even using relatively low precision DSWP over short time horizons. A key finding is that only about 1 second of prediction horizon is required, however, the technical difficulties involved in obtaining good estimates necessitate a DSWP system capable of prediction over tens of seconds.

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Section: Optimal Control Analysismentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Wave energy converter control by wave prediction and dynamic programming

et al. 2012

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“…Particularly in [18] it is shown, on real wave measurements, how autoregressive (AR) models allow the achievement of accurate forecasts for more than 1 wave period into the future. Alternative deterministic approaches have been also investigated, where the incident wave (or force/motion) is predicted from distant measurements [12], [19]- [22]. The latter solutions can produce more accurate predictions for longer into the future, at the expense of more instrumentation and higher algorithm complexity.…”

Section: Introductionmentioning

confidence: 99%

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

Fusco

Ringwood

2012

IEEE Trans. Sustain. Energy

101

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Abstract-It is widely acknowledged that real-time control of wave energy converters (WECs) can benefit from prediction of the excitation force. The prediction requirements (how far ahead into the future do we need to predict?) and the achievable predictions (how far ahead can we predict?) are quantified when unconstrained reactive control is implemented. The fundamental properties of the floating system that influence the length of the required forecasting horizon, as well as the achievable prediction, are characterized. The possibility of manipulating the control, based on prior knowledge of the wave spectral distribution, is also proposed for the reduction of the prediction requirements, such that they are within the range of predictability offered by simple stochastic predictors. The proposed methodology is validated on real wave data and heaving buoys with different geometries.

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