Applicability of offshore mooring and foundation technologies for marine renewable energy (MRE) device arrays

Published onlineThe marine renewable energy (MRE) sector is progressing from single device units to device arrays. Currently, the mooring/foundation technologies used in MRE are based on offshore oil/gas industry practices. For MRE arrays to reach commercialization, several issues need to be addressed including the hy-drodynamic array layout, electrical infrastructure, operations, maintenance, control, moorings, foundations, installation and logistics. The DTOcean (The Optimal Design Tools for Ocean Energy Arrays) project is aimed at accelerating the industrial development of ocean energy power generation knowledge, and providing design tools for deploying the first generation of wave and tidal energy converter arrays. In this paper, the ap-plicability of offshore mooring/foundation technologies for marine renewable energy (MRE) device arrays are assessed. The paper introduces the criteria which can be used to appraise technologies and approaches rele-vant to MRE devices. Existing mooring/foundation technologies used in the offshore industry are summarized with examples given of MRE device deployments. The guidance from certification agencies which is used for the design and analysis of mooring/foundation systems is summarized. If not addressed, the failure to opti-mize the design of ocean energy arrays and failure to properly understand economic, environmental, or relia-bility impacts of individual components could have significant consequences for the overall project and sec-tor. The function and type of mooring and/or foundation system are determined by a number of factors including the cost, site characteristics, expected environmental loading and environmental or legislative con-straints and these factors are discussed

Long-term distributions of individual wave and crest heights

This is the final version of the article. Available from Elsevier via the DOI in this record.This paper considers three types of method for calculating return periods of individual wave and crest heights. The methods considered differ in the assumptions made about serial correlation in wave conditions. The long-term distribution of individual waves is formed under the assumption that either (1) individual waves, (2) the maximum wave height in each sea state or (3) the maximum wave height in each storm are independent events. The three types of method are compared using long time series of synthesised storms, where the return periods of individual wave heights are known. The methods which neglect serial correlation in sea states are shown to produce a positive bias in predicted return values of wave heights. The size of the bias is dependent on the shape of the tail of the distribution of storm peak significant wave height, with longer-tailed distributions resulting in larger biases. It is shown that storm-based methods give accurate predictions of return periods of individual wave heights. In particular, a Monte Carlo storm-based method is recommend for calculating return periods of individual wave and crest heights. Of all the models considered, the Monte Carlo method requires the fewest assumptions about the data, the fewest subjective judgements from the user and is simplest to implement.This work was partly funded through EPSRC grant EP/R007519/1

The importance of getting your feet wet: Field measurements from the OPERA project

Conference presentation: 4th PRIMaRE Conference 2017; Southampton 6th July 2017Several fundamental development barriers exist within the wave energy sector associated with uncertainties about technological and economic risk. These factors are symptomatic of the sector; a multitude of device designs that have been proposed to-date and yet performance and reliability data is sparse. This coupled with a general lack of design convergence means that the relevance of published results may not always be applicable. The reluctance to share data is due to perceived or actual risks to commercial competitiveness and intellectual property. The need to prove continued availability, performance efficiency and survivability requires a deep understanding of how the device will operate in a range of expected environmental conditions. At low Technology Readiness Levels (TRL < 4) a mixture of experimental and numerical modelling is typically used to understand the fundamental operational characteristics of the device. Scale prototype testing at sea (TRL 5-6) provides an opportunity not only to ‘shakedown’ the design but also to acquire long-term, device response data, allowing numerical models (i.e. dynamic simulations and fatigue calculations) to be validated in addition to allowing O&M activities to be developed. With the current lack of published field data in mind, the Horizon 2020 funded Open Sea Operating Experience to Reduce Wave Energy Cost (OPERA) project is focused on data collection of offshore and onshore devices. The offshore device; Marmok-A-5 (developed by Oceantec Energias Marinas supported by the Basque government energy agency, EVE), is an oscillating water column comprising a 5m diameter (max) and 41.8m long hollow spar buoy deployed in approximately 85m water depth at the BiMEP test site (Fig. 1). The mooring system features one cell of the shared ‘Karratu’ system proposed in and has been instrumented to record tensions on the two seaward corners of the cell at 20Hz. This, coupled with an onboard IMU and DGPS provides a detailed dataset of device and mooring system response. The dataset along with directional wave buoy measurements recorded nearby and hindcast wind and current fields are currently being used to validate a fully dynamic numerical model of the system . An overview of this process and the challenges associated with offshore data collection will be presented at the PRIMaRE conference.The work is part of the OPERA (Open Sea Operating Experience to Reduce Wave Energy Cost) project which is funded from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 654.444

A generalised equivalent storm model for long-term statistics of ocean waves

This is the final version of the article. Available from Elsevier via the DOI in this record.To calculate the return periods of individual wave or crest heights, the long-term distribution of sea states must be combined with the short-term distribution of individual wave or crest heights conditional on sea state. This is normally achieved using an equivalent storm model to parameterise the distribution of the maximum wave or crest height in a storm. A new equivalent storm model is introduced that generalises the approach of Tromans and Vanderschuren (1995). The generalised equivalent storm (GES) method is significantly simpler than equivalent storm methods that model the temporal evolution of the significant wave height in a storm. The GES method is applied to long time series of wave buoy measurements for deep and shallow water sites and demonstrated to be more accurate than existing methods at representing the statistical characteristics of measured storms. Return periods of crest heights from the GES method are shown to be more robust to uncertainties in the fitted models of the equivalent storm parameters than estimates from temporal evolution methods such as the equivalent triangular storm and equivalent power storm model.This work was partly funded through EPSRC grant EP/R007519/1

Operations and maintenance planning for community-scale, off-grid wave energy devices

Conference paper from RENEW 2016: 2nd International Conference on Renewable Energies Offshore, 2016-10-24, 2016-10-26, Lisbon, Portugal. This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Marine Renewable Energy (MRE) has progressed towards commercialisation over the recent years but signifi-cant barriers still exist. This includes the currently high cost of energy, leaving MRE uncompetitive with re-spect to other more established renewable energy technologies. A significant proportion of this cost comes from Operation and Maintenance (O&M) activities. O&M activity can be reduced through the use of condi-tion-based maintenance scheduling. In offshore environments, the submerged location of most devices enables the use of underwater Acoustic Emission (AE), a new condition-monitoring technique. It combines acoustics (used for environmental monitoring of MRE influence on noise levels) with AE condition monitoring as used in air. This paper assesses the practicality of such an approach in complex ocean environments through detailed sound propagation modelling using the propagation model Bellhop in the Matlab toolbox AcTUP. Results show that acoustic propagation is very sensitive to variations in the shallow water environments considered. When concerning sensor placement, multiple-path interferences mean that the location of the measuring sen-sor(s) needs to be carefully considered, but might not cover all environmental variations over the several months necessary for accurate long-term monitoring. Associated to the shallow depths, these environmental variations also mean that some frequencies cannot be back-propagated easily, generally limiting access to the monitoring of Received Levels. The results presented here are the first steps toward optimizing AE sensor po-sitions and AE measuring strategies for arrays of devices.The lead author would like to thank the academic supervisors of this IDCORE project for their contributions, advice and support. Similar thanks must go to the engineers involved in developing the Squid devices at Albatern Ltd. The author would also like to thank Wave Energy Scotland, the IDCORE programme and their funding bodies, in particular the ETP (Energy Technology Partnership), for their support. IDCORE is funded by the Energy Technology Partnership and the RCUK Energy Programme; Grant number EP/J500847/1

Development of a Multi-Objective Genetic Algorithm for the Design of Offshore Renewable Energy Systems

This is the author accepted manuscript. The final version is available from the publisher via the URL in this record.Optimization algorithms have been deployed for a range of renewable energy problems and can successfully be applied to aid in the design of devices, farms, control strategies, and operations and maintenance strategies. Building on this, the present work makes use of a multi-objective genetic algorithm (GA) in order to develop a framework that can further aid in the design and development of offshore renewable energy systems by explicitly taking into account reliability considerations. Though the reliability-based design optimization approach has previously been used in offshore renewable energy applications and multi-objective optimization applications, it has not previously been applied to multi-objective offshore renewable energy design optimization. As the offshore renewable energy sectors grows it is important for the industry to explore more sophisticated methods of designing devices in order to ensure that the device reliability and lifetime can be maximized while downtime and cost are minimized. This paper describes the development of a framework using a GA in order to aid in the design of a mooring system for offshore renewable energy devices. This framework couples numerical models of the mooring system and structural response to both stress-life cumulative damage models and cost models in order for the GA to effectively operate considering the multiple objectives. The use of this multi-objective optimization approach allows multiple design objectives such as system lifetime and cost to be satisfied simultaneously using an automated mathematical approach. From the outputs of this approach, a designer can then select a solution which appropriately balances the different objectives. The developed framework will be applicable to any offshore technology subsystem allowing multi-objective optimization and reliability to be considered from the design stage in order to improve the design efficiency and aid the industry in using more systematic design approaches.This work is funded by the EPSRC (UK) grant for the SuperGen United Kingdom Centre for Marine Energy Research (UKCMER) [grant number: EP/P008682/1]

A coupled Monte Carlo - Evolutionary Algorithm approach to optimise offshore renewables O&M

This is the author accepted manuscript. The final version is available from EWTEC via the link in this record.Improving the reliability and survivability of wave and tidal energy converters, whilst minimising the perceived risks and reducing the deployment costs, are recognised as key priorities to further develop the marine energy market. Computational decision-making models for offshore renewables have demonstrated to be valuable tools in order to provide support in these strategic areas. In this paper, the authors propose an integrated approach of Monte Carlo simulation and Evolutionary Algorithms to address these challenges. A time-domain method based on the Monte Carlo technique, with specific consideration of marine renewable energy requirements, is used for the assessment of the devices and the characterization of the offshore farms. This permits the obtainment of energy predictions and indications on the reliability, availability, maintainability and profitability of the farm. A multi-objective search, by means of a specifically designed Genetic Algorithm, is then used to determine the ideal variation of inputs set for the improvement of the results. Suitable objective functions aiming at the minimization of the maintenance costs and the maximization of the reliability are considered for this purpose. The outcomes obtainable for the assessment of an offshore farm, as well as suggested practices for the optimisation of the Operation and Maintenance (O&M) procedures, are introduced and discussed. Results on the ideal trade-off solutions between conflicting objectives are presented.The work in this paper has been conducted within the multinational Initial Training Network (ITN) OceaNET, funded under the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme FP7/2007-2013/ under REA grant agreement n° 607656. Mojo Maritime (JFMS) have provided access to Mermaid to support, and for integration with, this research

The influence of load history on synthetic rope response

Although used for the station-keeping of offshore equipment for several decades, synthetic ropes have only recently been used for marine renewable energy (MRE) devices. The fundamental mooring load differences between these two applications necessitate the detailed quantification of mooring component performance. Of particular importance for lifecycle analysis, installation and maintenance operations is the evolution of synthetic component performance over time due to load history and fatigue mechanisms. Changes to the stiffness and damping properties of these materials will affect the global response of the device if the mooring system and device responses are closely coupled. To address these uncertainties, tension experiments have been conducted on Nylon parallel-stranded rope samples at IFREMER as part of a MERiFIC (Marine Energy in Far Peripheral and Island Communities) consortium. Measurements are reported from tests involving three new samples subjected to a mixed creep/relaxation and harmonic loading regime. Different initial bedding-in levels are used to investigate the influence of load history on the immediate quasi-static and dynamic properties of the rope. For the load regimes studied, it is found that the rope condition with respect to the load-strain characteristic has a strong influence on the performance of the line.The authors would like to acknowledge the support of the MERiFIC project partners. The project is funded by the European Regional Development Fund through the Interreg IV-A programme

Multi-Objective Optimization of Mooring Systems for Offshore Renewable Energy

This is the author accepted manuscript. The final version is available from EWTEC via the link in this record.This paper presents a method for the optimization of mooring systems in offshore renewable energy systems. This methodology considers the location of anchors as well as the length, material, and diameter of the mooring lines in order to simultaneously minimize the tension in the lines, the cost of the mooring system, and the fatigue damage in the system. By considering these three objectives using a multi-objective approach rather than reduction to a single objective optimization problem allows a Pareto hull of solutions to be obtained representing a range of solutions which balance the three objectives. From this, a system designer can select the design which appropriately balances the trade-off between the competing objectives. In this work, a set of mooring designs that represent efficient solutions for the constraints are found and presented considering the OC4 DeepCWind semi-submersible at Wave Hub. This reliability-based design optimization approach will be applicable to other offshore technology subsystems allowing reliability to be considered in a multi-objective optimization from the design phase.This work is funded by the EPSRC (UK) grant for the United Kingdom Centre for Marine Energy Research (UKCMER) [grant number: EP/P008682/1]

Reliability assessment of tidal stream energy: significance for large-scale deployment in the UK

This is the author accepted manuscript. The final version is available from CRC PressThe UK has ambitious plans to harness its available tidal stream resource, estimated at 95TWh/year by The Crown Estate (2013). The economic viability of large-scale deployments will be largely governed by aspects of plant availability, including reliability. Using available information on environmental parameters of (pre-) consented sites across the UK, this paper explores subassembly target reliability levels for tidal stream devices. Reliability models of devices are investigated to establish the influence of environmental site conditions with regard to underlying subassembly failure rates and target reliability levels. Hence, a relia-bility-focussed perspective on the planned deployments is presented