Data-based modelling of arrays of wave energy systems:Experimental tests, models, and validation

One of the key steps towards economic feasibility of wave energy conversion technology concerns scaling up to farms of multiple devices, in the attempt to reduce installation costs by sharing infrastructure, and a consequent drop in levelised cost of energy. Moreover, whenever wave energy systems are deployed in proximity (in so-called arrays), the exploitation of the hydrodynamic interactions between single devices is fully enabled, potentially increasing the final energy outcome. To achieve this in real (operational) time, the employed energy-maximising control strategies require control-oriented array models, able to efficiently describe the dynamics of these interconnected systems in a representative fashion. This can be, nonetheless, a difficult task when considering first principles alone, under small motion assumptions, for modelling purposes. Recognising the uncertainty associated to array numerical models obtained from the linearisation of simplified system equations around their equilibria, this paper presents models of several array configurations identified following a frequency domain approach on the basis of experimental data. Tailored tests on laboratory-scale devices have been designed and conducted in the Aalborg University (Denmark) wave tank facility, with the purpose of performing representative system identification of the wave energy systems arrays. The obtained models are validated on different representative sea states configurations, in controlled and uncontrolled motion operational conditions. The validation results are fully discussed and analysed in terms of standard error measures and time lag, while the obtained models are made freely accessible via a linked repository (named OCEAN), in the attempt to openly provide validated models for different array configurations.</p

How future surgery will benefit from SARS-COV-2-related measures: a SPIGC survey conveying the perspective of Italian surgeons

COVID-19 negatively affected surgical activity, but the potential benefits resulting from adopted measures remain unclear. The aim of this study was to evaluate the change in surgical activity and potential benefit from COVID-19 measures in perspective of Italian surgeons on behalf of SPIGC. A nationwide online survey on surgical practice before, during, and after COVID-19 pandemic was conducted in March-April 2022 (NCT:05323851). Effects of COVID-19 hospital-related measures on surgical patients' management and personal professional development across surgical specialties were explored. Data on demographics, pre-operative/peri-operative/post-operative management, and professional development were collected. Outcomes were matched with the corresponding volume. Four hundred and seventy-three respondents were included in final analysis across 14 surgical specialties. Since SARS-CoV-2 pandemic, application of telematic consultations (4.1% vs. 21.6%; p &lt; 0.0001) and diagnostic evaluations (16.4% vs. 42.2%; p &lt; 0.0001) increased. Elective surgical activities significantly reduced and surgeons opted more frequently for conservative management with a possible indication for elective (26.3% vs. 35.7%; p &lt; 0.0001) or urgent (20.4% vs. 38.5%; p &lt; 0.0001) surgery. All new COVID-related measures are perceived to be maintained in the future. Surgeons' personal education online increased from 12.6% (pre-COVID) to 86.6% (post-COVID; p &lt; 0.0001). Online educational activities are considered a beneficial effect from COVID pandemic (56.4%). COVID-19 had a great impact on surgical specialties, with significant reduction of operation volume. However, some forced changes turned out to be benefits. Isolation measures pushed the use of telemedicine and telemetric devices for outpatient practice and favored communication for educational purposes and surgeon-patient/family communication. From the Italian surgeons' perspective, COVID-related measures will continue to influence future surgical clinical practice

An Anti-Windup Mechanism for State Constrained Linear Control of Wave Energy Conversion Systems:Design, Synthesis, and Experimental Assessment

Motivated by the necessity of suitable state constraint mechanisms within linear time-invariant (LTI) energy-maximising control of wave energy converters (WECs), we present, in this article, an anti-windup (AW) scheme for state constraint satisfaction, where the associated unconstrained controller is designed via impedance-matching theory for WEC systems. As in the standard (input) AW scenario, the adopted technique provides a mechanism for 'informing' the (unconstrained) controller when constraints are active, so that appropriate modifications to future control actions can be taken accordingly. The overall adopted AW technique is tested experimentally, on a prototype of the Wavestar WEC system, available at Aalborg University (Denmark). We explicitly demonstrate that the proposed AW scheme is able to consistently respect the defined state constraints, having a mild impact on overall energy absorption performance when compared to its unconstrained counterpart.</p

Mooring Influence on the Productivity of a Pitching Wave Energy Converter

The paper aims at investigate the effect of the mooring system on Wave Energy Converter productivity. In this case a pitch resonant device has been considered for the analysis. The non-linearities of the mooring system require generally a computational effort which cannot be considered in the early design stages of a WEC, and seldom the mooring systems are totally included in WEC models. Driven by those considerations, a nonlinear mooring solvers, MoorDyn, has been used to carry out the effect of the mooring system on energy production. As first step a mooring model has been built to take familiarity with the solver and it has been validated against experimental data, through a static pull-out test and with irregular wave. Then, a semi-taut mooring model has been included in the hydrodynamic model

Input-Unknown Estimation for Arrays of Wave Energy Conversion Systems via LTI Synthesis

The incoming menace of global overheating and depletion of fossil fuels, highlight the need for alternative, renewable, energy sources. In this context, ocean wave energy has a massive potential to contribute towards global decarbonisation. In optimising wave energy converters (WEC) productivity, state-of-the-art, model-based optimal control techniques are fundamental to enhance energy absorption efficiency. However, the vast majority of these optimal approaches inherently require wave excitation force estimators. In particular, in array configurations, the interaction between WEC devices has to be taken into account to achieve a consistent excitation force estimation. In this paper, a linear time-invariant (LTI) estimation approach for a WEC farm is proposed. The technique proposed is based upon the so-called ‘simple and effective estimator’, recently presented in the WEC literature, which reformulates the wave excitation force estimation problem as a traditional tracking loop. The results show that the proposed approach provides accurate estimates of the exciting force for every device in the array, with almost no design effort, and mild computational requirements

On the influence of mooring systems in optimal predictive control for wave energy converters

Wave energy conversion systems have a massive potential in securing a reliable renewable energy mix. In their development, a crucial role is that of optimal control (OC) algorithms. Such systems are able to maximize the wave energy converter (WEC) power extraction, while respecting the corresponding of technological constraints. State-of-the-art OC techniques, such as Model Predictive Control (MPC), rely on mathematical models of the device to control, in a predictive fashion, the WEC system, thus maximizing the power production. Nonetheless, to date, control algorithms are usually developed and assessed on the basis of free floating WEC models, i.e. which neglect the mooring system influence. As a matter of fact, the anchorage introduces nonlinear dynamics in the device motion. Consequently, to test the idealized potential of a control strategy, such system is commonly neglected. Moorings are a fundamental WEC component, and have the potential to influence significantly the associated system dynamics. Neglecting this element can lead to deceptive results, either in terms of device theoretical productivity, and control strategy effectiveness. This paper proposes a systematic procedure to include, in the model used to synthesized such OC strategies, a linear representative model of the mooring system, presenting its benefits by discussing the consequent MPC loop development and corresponding performance assessment. Such procedure consists in retrieving an estimate of the frequency response of the moored system, using properly designed input conditions, and identifying the associated input–output linear system. A main objective of this study is, hence, to assess the difference between an MPC strategy designed and synthesized, with and without the proposed mooring control-oriented representation, always using as simulation system a high-fidelity numerical model for performance evaluation, which incorporates a full account of the mooring effects

Collaborative strategy for model-free control of arrays of wave energy converters: A genetic algorithm approach

In the field of renewable energy, one of the most promising branches is wave energy conversion. Systems used to extract wave energy are called WECs (Wave Energy Converters). In order to extensively exploit the untapped potential wave energy has, several devices should be adopted together, constituting in this way an array configuration. The development of suitable control strategies for WECs is among the open challenges in wave energy field. Classical approaches rely on models of the considered WECs to compute the optimal control action. In the proposed work, however, a different model-free approach is pursued. Here, the control action is computed only on the basis of past applied control parameters and of absorbed power measurements among the elements of the array. The strategy developed in this work is based on the analogy between devices of the array and the concept of generation in genetic optimization algorithm. Given a sea-state condition, each WEC in the array constitutes an individual of the generation. On each one, a combination of control parameters is applied and the average absorbed power thus obtained is measured. With the considered analogy, this set of control parameters constitutes the chromosome, while the power is the measure of the fitness function to be, in this case, maximized. In this way, merging the data coming from different WECs of the array helps the control strategy to converge in a collaborative way to optimal parameters faster. As a case study, an array of point absorbers deployed in the Mediterranean Sea has been considered, together with its typical values of significant height, energetic period and annual occurrences

Nonlinear Model Reduction by Moment-Matching for a Point Absorber Wave Energy Conversion System

This paper presents a data-driven model reduction by moment-matching approach to construct control-oriented models for a point absorber device. The methodology chosen and developed generates models which are input-to-state linear, with any nonlinear behaviour confined to the output map. Such a map is the result of a data-driven approximation procedure, where the so-called moment of the point absorber system is estimated via a least-squares procedure. The resulting control-oriented model can inherently preserve steady-state properties of the target WEC system for a user-defined class of input signals of interest, with the computation only dependent upon a suitably defined set of input-output data