a b s t r a c tMathematical modelling of wave energy devices has many uses, including power production assessment, simulation of device motion and as a basis for model-based control design. Apart from computationally heavy approaches, such as those based on computational fluid dynamics (CFD) and smooth particle hydrodynamics (SPH), the vast majority of models employed in the simulation and analysis of wave energy converters (WECs) are based on boundary-element methods (BEMs). While BEM models have been shown to be useful, they have the inherent limitation that they are linearised around the still water level, with validity only on the immediate vicinity of this equilibrium point. In this paper, we develop a new modelling methodology, which combines the fidelity of CFD models with the computational attractiveness of BEM-type models. This flexible methodology can give representative linear models, or be extended into the nonlinear domain, as desired.
We consider the problem in which a fleet of vehicles located at a central depot is to be optimally used to serve a set of customers partitioned into two subsets of linehaul and backhaul customers. Each route starts and ends at the depot and the backhaul customers must be visited after the linehaul customers. A new (0–1) integer programming formulation of this problem is presented. We describe a procedure that computes a valid lower bound to the optimal solution cost by combining different heuristic methods for solving the dual of the LP-relaxation of the exact formulation. An algorithm for the exact solution of the problem is presented. Computational tests on problems proposed in the literature show the effectiveness of the proposed algorithms in solving problems up to 100 customers.
In this paper and its companion [1], the identification of mathematical models describing the behaviour of wave energy devices (WECs) in the ocean is investigated through the use of numerical wave tank (NWT) experiments. This paper deals with the identification tests used to produce the data for the model identification. NWTs, implemented using computational fluid dynamics (CFD), are shown as an effective platform to perform the identification tests. The design of the NWT experiments, to ensure the production of information-rich data for the model identification, is discussed. A case study is presented to illustrate the design and implementation of NWT experiments for the identification of WEC models.
In this paper and its companion [1], the identification of mathematical models describing the behaviour of wave energy devices (WECs) in the ocean is investigated through the use of numerical wave tank experiments. When the wave amplitude and the WEC displacement are not negligible with respect to the WEC dimensions, nonlinear hydrodynamic effects may appear, and the accuracy of linear hydrodynamic models is reduced, leading to the necessity of introducing some nonlinearities in the model structure. This paper proposes, for WEC modelling, the use of discrete-time nonlinear autoregressive with exogenous input (NARX) models, as an alternative to continuous-time models. Techniques of model identification are also explained and applied to a case study. Index Terms-System identification, numerical wave tank, wave energy, discrete-time modelling, NARX model, ARX model, artificial neural network, Kolmogorov-Gabor polynomial model.
The International Energy Agency Technology Collaboration Programme for Ocean Energy Systems (OES) initiated the OES Wave Energy Conversion Modelling Task, which focused on the verification and validation of numerical models for simulating wave energy converters (WECs). The long-term goal is to assess the accuracy of and establish confidence in the use of numerical models used in design as well as power performance assessment of WECs. To establish this confidence, the authors used different existing computational modelling tools to simulate given tasks to identify uncertainties related to simulation methodologies: (i) linear potential flow methods; (ii) weakly nonlinear Froude–Krylov methods; and (iii) fully nonlinear methods (fully nonlinear potential flow and Navier–Stokes models). This article summarizes the code-to-code task and code-to-experiment task that have been performed so far in this project, with a focus on investigating the impact of different levels of nonlinearities in the numerical models. Two different WECs were studied and simulated. The first was a heaving semi-submerged sphere, where free-decay tests and both regular and irregular wave cases were investigated in a code-to-code comparison. The second case was a heaving float corresponding to a physical model tested in a wave tank. We considered radiation, diffraction, and regular wave cases and compared quantities, such as the WEC motion, power output and hydrodynamic loading.
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