An improved method for energy and resource assessment of waves in finite water depths

For cost savings and ease of operation, nearshore regions have been considered as ideal regions for deploying wave energy converters (WECs) and wave farms. As the water depths of these regions may be frequently limited to 50 m or less, they can be considered as being transitional/intermediate to shallow when compared to the wave lengths of interest for wave energy conversion. Since the impact of water depths on propagation of waves is significant, it cannot be ignored in wave energy assessment. According to the basic wave theory, in order to work out accurate wave energy amounts in finite water depth, detailed wave spectral distributions should be given. However, for some practical reasons, there are still some cases where only scatter diagrams and/or the statistical wave parameters are available, whilst the detailed wave spectra are discarded. As a result, the assessments of wave energy and resources are frequently determined by ignoring the effect of water depths or using very simplified approximations. This research paper aims to develop more accurate approximation methods by utilising a number of available parameters such that a better estimate on the wave resource assessment can be achieved even if the detailed wave spectra are not available. As one important goal, the research can provide some important indications on how the measured wave data are effectively presented so that they can be very useful for assessing the wave energy resource, especially in the cases including the effects of finite water depths

A multi-objective optimization model for EVSE deployment at workplaces with smart charging strategies and scheduling policies.

This study proposes a multi-objective optimization model to determine the optimal charging infrastructure for a transition to plug-in electric vehicles (PEVs) at workplaces. The developed model considers all cost aspects of a workplace charging station, i.e. daily levelized electric vehicle supply equipment (EVSE) infrastructure cost, PEV energy and demand charges. These single-objective functions are aggregated in a multi-objective optimization framework to find the Pareto optimal solutions. Smart charging strategies with interrupted and uninterrupted power profiles are proposed to maximize the use of EVSE units. The charging behavior model is developed based on collected workplace charging data. The model is tested with various scheduling policies to investigate their impact on the behaviors of EVSE types from different perspectives. Finally, a sensitivity analysis is performed to assess the impacts of battery sizes and onboard charger ratings on cost behavior. It is shown that the proposed model can achieve up to 7.8% and 14.6% cost savings as compared to single-objective optimal models and the current charging practice, respectively. The unit cost is found to be more sensitive to scheduling policies than the charging strategies. It is also found that the flexibility ratio policy gives the best PEV scheduling with the lowest unit cost and the most efficient use of the grid assets

An investigation into the suitability of GGBS and OPC as low percentage single-component binders for the stabilisation and solidification of harbour dredge material mildly contaminated with metals

The occurrence of contaminated materials encountered during harbour dredging is becoming increasingly problematic for harbour and port authorities. The risks to human health, wildlife and port infrastructure of exposure to such contaminants necessitates the removal or containment of such risks. As with contaminated terrestrial sites the solidification and stabilization (S/S) of this material has been proven to be an effective alternative to disposing of contaminants off-site, typically via dumping at sea or in a landfill. Research, to date, on S/S has been focused on heavily contaminated sediments in large industrial ports. However, with tightening environmental regulations, the limits of acceptable contamination are generally decreasing. This means the number of port dredging projects requiring contaminant remediation is increasing. There is now a need to examine the effectiveness of S/S on harbour sites that are mildly contaminated from both an environmental and project feasibility viewpoint. To that end, this study examines the effectiveness of various S/S mix percentages of ordinary Portland cement (OPC) and ground granulated blast furnace slag (GGBS) in retarding the leaching of contaminants from a mildly contaminated harbour site

Dynamic effects of anchor positional tolerance on tension moored floating wind turbine

For water depths greater than 60m floating wind turbines will become the most economical option for generating offshore wind energy. Tension mooring stabilised units are one type of platform being considered by the offshore wind energy industry. The complex mooring arrangement used by this type of platform means that the dynamics are greatly effected by offsets in the positioning of the anchors. This paper examines the issue of tendon anchor position tolerances. The dynamic effects of three positional tolerances are analysed in survival state using the time domain FASTLink. The severe impact of worst case anchor positional offsets on platform and turbine survivability is shown. The worst anchor misposition combinations are highlighted and should be strongly avoided. Novel methods to mitigate this issue are presented

Drag force as a function of cross section and angle of attack. A hydraulic laboratory dataset for numerical validation

This data relates to a set of hydraulic laboratory experiments in which the flow around four cross-sections was investigated. Each cross section was examined at four angles of attack (0, 5, 10, 90°), seven velocities (0–0.7 m/s in 0.1 m/s steps) and two flow directions. The data is primarily from an array of load cell which monitored the loading on the cross-sections during testing in six degrees of freedom during testing. Video and photographs are also included

Description of an 8 MW reference wind turbine

An 8 MW wind turbine is described in terms of mass distribution, dimensions, power curve, thrust curve, maximum design load and tower configuration. This turbine has been described as part of the EU FP7 project LEANWIND in order to facilitate research into logistics and naval architecture efficiencies for future offshore wind installations. The design of this 8 MW reference wind turbine has been checked and validated by the design consultancy DNV-GL. This turbine description is intended to bridge the gap between the NREL 5 MW and DTU 10 MW reference turbines and thus contribute to the standardisation of research and development activities in the offshore wind energy industry

Modelling air compressibility in OWC devices with deformable air chambers

Air compressibility effects play an important role in large-scale Oscillating Water Column (OWC) wave energy converters. Air compressibility is however not scalable with Froude similarity law. An existing scaling method enables correctly reproducing the air compressibility at the model scale, but its implementation is effortful and becomes cumbersome for floating devices and tests at relatively large scales (1/15th–1/2th). Air compressibility is therefore commonly ignored in model-scale tank testing of conventional OWC devices, which can lead to substantially unrealistic results on the device performance relative to the full-scale device. In the case of the Tupperwave device, which is a closed circuit OWC device, correctly modelling air compressibility during tank testing is however essential because the device relies on air compressibility to work. In this paper, a new method for modelling air compressibility at the model scale is presented. The method uses variable volume chambers, which mimic air compressibility by storing energy under the form of strain energy. This method reduces the difficulties of implementation and enhances the application of the existing method to larger scales. Various applications to this method are identified and described, including the presentation of a novel OWC concept

Physical and numerical analysis of a concept offshore wind farm service vessel hull design

Wind turbine maintenance and access during high sea states is a key issue for the successful operation of an offshore wind farm. Currently there is a 1.5m significant wave height (Hs) limit for the standard ‘step over’ method of transferring personnel to an offshore wind turbine. Increasing the Hs that offshore wind turbines can be accessed at would reduce the lifetime, levelised cost of energy and address a health and safety issue. The paper addresses this issue by examining a concept hull design for an offshore wind farm service vessel. The proposed design reduces the vessel’s heave and motion by dampening its response to the wave motion. The design underwent both numerical and physical methods of testing. The numerical modelling was carried out in a 3-D wave basin built in ANSYS CFX and is based on symmetry across the hull which allows for three degrees of freedom. Physical modelling at 1:25 scale took place in the wave basin at Beaufort Research in University College Cork. A number of variations of the concept were tested and the results showed the aspects of the concept that could be beneficial to personnel transfer, through reduced response amplitude operators at zero forward speed

Offshore wind speed short-term forecasting based on a hybrid method: swarm decomposition and meta-extreme learning machine.

As the share of global offshore wind energy in the electricity generation portfolio is rapidly increasing, the grid integration of large-scale offshore wind farms is becoming of interest. Due to the intermittency of wind, the stability of power systems is challenging. Therefore, accurate and fast offshore short-term wind speed forecasting tools play important role in maintaining reliability and safe operation of the power system. This paper proposes a novel hybrid offshore wind forecasting model based on swarm decomposition (SWD) and meta-extreme learning machine (Meta-ELM). This approach combines the advantages of SWD which has proven efficiency for non-stationary signals, with Meta-ELM which provides faster calculation with a lower computational burden. In order to enhance accuracy and stability, the signal is decomposed by implementing a swarm-prey hunting algorithm in SWD. To validate the model, a comparison against four conventional and state-of-the-art hybrid models is performed. The implemented models are tested on two real wind datasets. The results demonstrate that the proposed model outperforms the counterparts for all performance metrics considered. The proposed hybrid approach can also improve the performance of the Meta-ELM model as a well-known and robust method

Geospatial dimensions of the renewable energy transition — The importance of prioritisation

The renewable energy transition is a priority for many researchers, policy makers, and political leaders because it is projected to stop the dependence of economic growth on increasing fossil fuel use and thus curtail climate change. This study examines how expert judgments affect development decisions to enable the renewable energy transition. Geospatial Multi-Criteria Decision Analyses (MCDA) are frequently used to select offshore wind energy (OWE) sites, however, they are often weak and/or often rely on limited judgement. The Analytical Hierarchy Process is used here with 25 diverse experts to assess the variability in priorities for OWE siting criteria. A geospatial MCDA is implemented using experts' individual priorities, aggregated weights and Monte Carlo simulations. Case study results reveal large variations in expert opinions and bias strongly affecting MCDAs weighted by single decision-makers. A group-decision approach is proposed to strengthen consent for OWE, underpinning the renewable energy transition