Real-time Forecasting and Control for Oscillating Wave Energy Devices

Ocean wave energy represents a signicant resource of renewable energy and can make an important contribution to the development of a more sustainable solution in support of the contemporary society, which is becoming more and more energy intensive. A perspective is given on the benefits that wave energy can introduce, in terms of variability of the power supply, when combined with oshore wind. Despite its potential, however, the technology for the generation of electricity from ocean waves is not mature yet. In order to raise the economic performance of Wave energy converters (WECs), still far from being competitive, a large scope exists for the improvement of their capacity factor through more intelligent control systems. Most control solutions proposed in the literature, for the enhancement of the power absorption of WECs, are not implemented in practise because they require future knowledge of the wave elevation or wave excitation force. The non-causality of the unconstrained optimal conditions, termed complex-conjugate control, for the maximum wave energy absorption of WECs consisting of oscillating systems, is analysed. A link between fundamental properties of the radiation of the floating body and the prediction horizon required for an effective implementation of complex-conjugate control is identified. An extensive investigation of the problem of wave elevation and wave excitation force forecasting is then presented. The prediction is treated as a purely stochastic problem, where future values of the wave elevation or wave excitation force are estimated from past measurements at the device location only. The correlation of ocean waves, in fact, allows the achievement of accurate predictions for 1 or 2 wave periods into the future, with linear Autoregressive (AR) models. A relationship between predictability of the excitation force and excitation properties of the floating body is also identified. Finally, a controller for an oscillating wave energy device is developed. Based on the assumption that the excitation force is a narrow-banded harmonic process, the controller is effectively tuned through a single parameter of immediate physical meaning, for performance and motion constraint handling. The non-causality is removed by the parametrisation, the only input of the controller being an on-line estimate of the frequency and amplitude of the excitation force. Simulations in (synthetic and real) irregular waves demonstrate that the solution allows the achievement of levels of power capture that are very close to non-causal complex-conjugate control, in the unconstrained case, and Model predictive control (MPC), in the constrained case. In addition, the hierarchical structure of the proposed controller allows the treatment of the issue of robustness to model uncertainties in quite a straightforward and effective way

On state and inertial parameter estimation of free-falling planar rigid bodies subject to unsche dule d frictional impacts

This paper addresses the problem of simultaneous state estimation and inertial and frictional parameter identification for planar rigid-bodies subject to unscheduled frictional impacts. The aim is to evaluate to what level of accuracy, given noisy captured poses of an object free-falling under gravity and impacting the surrounding environment, it is conceivable to reconstruct its states, the sequence of normal and tangential impulses and, concurrently, estimate its inertial properties along with Coulomb’s coefficient of friction at contacts. To this aim we set up a constrained nonlinear optimization problem, where the unscheduled impacts are handled via a complementarity formulation. To assess the validity of the proposed approach we test the identification results both (i) with respect to ground truth values produced with a simulator, and (ii) with respect to real experimental data. In both cases, we are able to provide accurate/realistic estimates of the inertia-to-mass ratio and friction coefficient along with a satisfactory reconstruction of systems states and contact impulses

Quantification of the Prediction Requirements in Reactive Control of Wave Energy Converters

Optimal reactive control for maximum ocean wave power absorption from Wave Energy Converters (WECs) consisting of oscillating systems, is based on the principle of tuning their oscillation so that it is in resonance with the excitation force produced by the incident waves. Reactive control, however, is non-causal and cannot be implemented in real time. This paper analyses the prediction requirements of one possible solution, where predictions of the excitation force are utilised to resolve the non-causality. The study is focused on the analysis of the required forecasting horizon against the achievable prediction. Also, through the aid of numerical simulations of a number of specific systems over several wave conditions, a link is found between some fundamental properties of the system and the prediction requirements

Robust control of wave energy converters

Energy-maximising controllers for wave energy devices are normally based on linear hydrodynamic device models. Such models ignore nonlinear effects which typically manifest themselves for large device motion (typical in this application) and may also include other modelling errors. In this paper, we present a methodology for reducing the sensitivity to modelling errors and nonlinear effects by the use of a hierarchical robust controller, which also allows good energy maximisation to be recovered through a passivity-based control approach

Short-Term Wave Forecasting with AR models in Real-Time Optimal Control of Wave Energy Converters

Time domain control of wave energy converters requires knowledge of future incident wave elevation in order to approach conditions for optimal energy extraction. Autoregressive models revealed to be a promising approach to the prediction of future values of the wave elevation only from its past history. Results on real wave observations from different ocean locations show that AR models allow to achieve very good predictions for more than one wave period in the future if the focus is put on low frequency components, which are the most interesting from a wave energy point of view. For real-time implementation, however, the lowpass filtering introduces an error in the wave time series, as well as a delay, and AR models need to be designed so to be as robust as possible to these errors

A Simple and Effective Real-Time Controller for Wave Energy Converters

A novel strategy for the real-time control of oscillating wave energy converters (WECs) is proposed. The controller tunes the oscillation of the system such that it is always in phase with the wave excitation force and the amplitude of the oscillation is within given constraints. Based on a nonstationary, harmonic approximation of the wave excitation force, the controller is easily tuned in real-time for performance and constraints handling, through one single parameter of direct physical meaning. The effectiveness of the proposed solution is assessed for a heaving system in one degree of freedom, in a variety of irregular (simulated and real) wave conditions. A performance close to reactive control and to model predictive control is achieved. Additional benefits in terms of simplicity and robustness are obtained

Evaluating IP Blacklists Effectiveness

IP blacklists are widely used to increase network security by preventing communications with peers that have been marked as malicious. There are several commercial offerings as well as several free-of-charge blacklists maintained by volunteers on the web. Despite their wide adoption, the effectiveness of the different IP blacklists in real-world scenarios is still not clear. In this paper, we conduct a large-scale network monitoring study which provides insightful findings regarding the effectiveness of blacklists. The results collected over several hundred thousand IP hosts belonging to three distinct large production networks highlight that blacklists are often tuned for precision, with the result that many malicious activities, such as scanning, are completely undetected. The proposed instrumentation approach to detect IP scanning and suspicious activities is implemented with home-grown and open-source software. Our tools enable the creation of blacklists without the security risks posed by the deployment of honeypots