International Journal of Marine Energy最新文献

The energy flow rate per unit flow area of water flow is quite high compared to air flow. This is because of high density of water compared to that of air. Hence, hydrokinetic turbine has the potential to extract more power compared to wind turbine for the same size of a turbine. The Darrieus turbine is one of the best options which can be used as a hydrokinetic turbine due to its high coefficient of power. In present work, the experimental investigations are carried out to study the hydrodynamic performance of three bladed Darrieus turbine with NACA0015, NACA0018 and NACA4415 blades for different solidities. Maxwell’s velocity correction method is used to account for blockage effect. NACA0015 and NACA0018 provide highest coefficient of power of 0.15 at a solidity of around 0.382. Experiments are extended to evaluate performance for four bladed rotors with symmetric-NACA0018 and cambered-NACA4415 hydrofoils. Both the hydrofoils provide a coefficient of power of around 0.13 but at different solidities. The effect of spanwise and streamwise distance on performance of a Darrieus turbine is investigated for its use as hydrofarm. A minimum distance of 7D along the streamwise direction and 3D along the spanwise direction are essential in a hydrofarm using Darrieus turbines.

This paper runs forecasting experiments for wave energy over a range of 22 sites worldwide. The wave parameters are derived from physics-based model simulations. In order to better represent the sea state variability, the model values are embedded in noise drawn from several distributions, with seasonal weights, based on wave buoy data. Converter matrices are used to calculate the power output, and the power series are aggregated to create large wave farms. Three types of wave energy converters are simulated: an attenuator, a floating heave buoy array, and an oscillating flap device. Forecasting tests are run over horizons of 1–4 h, and reserves are calculated. By analyzing multiple sites over wide distances, it is possible to identify underlying parallels in the findings. First, despite differences in weather patterns and bathymetry, the forecast errors lie in a fairly narrow range. At the 1 h horizon, the errors for the attenuator range from a high of 7.6 percent and a low of 4.7 percent, with a mean of 5.8 percent. The errors for the heave buoy array range from a high of 7.9 percent to a low of 2.4 percent, with a mean of 5.5 percent. The errors for the oscillating flap device range from a high of 8.9 percent to a low of 4.9 percent, with a mean of 6.5 percent. The narrow range of the errors indicates that from the standpoint of predicting wave energy, the similarities among sites outweigh the differences. Second, reserves required to balance surpluses and shortages of power are substantially lower than the costs associated with wind and solar. Using an average of the 22 sites, at the 1-h horizon, capacity-up reserves (needed to offset power deficits) range from 5.1 to 6.2 percent of the power. Capacity-down reserves (needed to offset power surpluses) range from 5.4 to 6.9 percent of the power. Third, forecast accuracy shows a mild inverse relationship to the wave energy – all other things being equal, higher energy sites are more difficult to predict. However, the main determinant of forecast accuracy is the probability distribution. When the distribution has heavy tails, forecast errors and reserve costs are higher. Taken together, these factors account for 70 percent of the forecast error.

This article presents a practical method for predicting the power output of tidal farms with device wake interactions. The method uses Reynolds-averaged Navier-Stokes (RANS) simulations to predict turbine wakes and bathymetry effects. The power of each turbine depends on the local velocity, which is influenced by other turbine wakes. Therefore, the accuracy of power predictions depends heavily on proper wake modeling. This is a critical issue for the tidal power industry because best practice for predicting tidal farm energy yield has yet to be established, and wake interaction effects may drastically alter energy yield in a dense turbine farm.

This article introduces a methodology which accurately predicts power output while minimizing computational expense, named the tuned actuator disk approach (TADA). Rotors are resolved using 9–15 elements across their diameter, allowing for very fast simulations of multiple turbines. The model is tuned to match known thrust and power operational profiles for a set of calibration cases based either on experiments or a limited set of high-resolution simulations. In this study, TADA was used to model a tandem configuration of two scaled rotors in a flume tank, and gave accurate predictions of the rotor thrust, power and wake velocities. Predictions of thrust and power became independent of grid density with more than 15 elements spanning the rotor diameter, however errors associated with using 9 elements were limited to 3% for thrust and 6% for power. Once calibrated for a specific turbine and computational mesh, TADA can be used in full farm-scale simulations at reasonable computational expense, which is an important capability for predicting tidal farm energy yield.

The long-term monitoring of seabirds around proposed marine renewable energy (MRE) sites is vital to assess the large-scale and long-term environmental impacts of MRE installations. Marine radar could be a valuable tool to augment traditional seabird surveys but the problem of aspect dependency of the generic radar cross section (RCS) of live birds in flight must be understood before radar data is correctly interpreted. A marine radar multiple target tracking algorithm (‘GANNET’) was applied to data from an un-calibrated, horizontally polarised, 10 kW X-band marine radar sited at the European Marine Energy Centre (EMEC) tidal renewable energy test site, Scotland U.K. From 24 days of data over 1.84 million target readings were recorded. For each target reading the radar aspect angle (bearing of radar beam incident on target), range and non-dimensional echo magnitude were derived allowing a view to be generated of the variation of echo magnitude with aspect angle for all tracked targets. The resulting polar diagram shows a significant change in echo magnitude with range between side-on and head/tail-on aspects indicating a large contribution of the RCS from the wings of birds in flight. The species-unspecific detectability of seabirds, especially at long range, is found to be strongly dependent on aspect angle. This has direct implications for the use of marine radar equipment for avian monitoring at proposed and active marine energy sites and must be taken into account if data from these radars are to be used to augment traditional bird abundance and area use surveys conducted by human observers.

Performance characterization of oscillating water column (OWC) wave energy converters (WEC) is commonly assessed by conducting physical scale model experiments of OWC models fitted with orifice plates to the air chamber to both; simulate the power take off (PTO), and measure the air flow rate. Generally it is assumed that a single calibration factor can be used for bi-directional air flow measurement, however this paper shows the assumption can be in-accurate and that it is necessary to have separate inflow and outflow calibration factors. This paper presents (i) a novel method for in-situ calibration of an orifice and (ii) a simple algorithm to reduce noise during air flow reversal (low air chamber pressure differential). Application of this technique results in more accurate flow rate prediction and consequently, better prediction of the power absorbed by the power take-off for OWCs.

This paper reports the findings of an experimental study investigating the influence of blade roughness on the performance of a vertical axis tidal turbine. Due to their design, vertical axis turbines undergo periods of stall, i.e. flow separation from the blade, during each revolution. It is hypothesised that roughening turbine blades delays flow separation (in analogy to flows over rough bluff bodies) and hence diminishes turbine stall which in turn should result in an increase in turbine performance. Laboratory experiments were undertaken in Cardiff University’s hydraulics laboratory, testing vertical axis turbines with rotors comprising smooth and rough blades. Three different blade surface roughnesses were tested, with the results showing a significant reduction in performance when the turbine is operating at high chord Reynolds numbers and with rough blades. In addition, the combined effect of blade roughness and rotor solidity as well as blade roughness and number-of-blades on the performance of vertical axis turbines are analysed. It is shown that solidity and number-of-blades appear to be similarly influential than blade roughness.

Experts’ judgement is employed in offshore risk assessment because reliable failure data for quantitative risk analysis are scarce. The challenges with this practice lies with knowledge-based uncertainties which renders risk expression and estimation, hence components’ risk-based prioritisation, subjective to the assessor – even for the same case study. In this paper, a new risk assessment framework is developed to improve the fidelity and consistency of prioritisation of components of complex offshore engineering systems based on expert judgement. Unlike other frameworks, such as the Failure Mode and Effect Criticality Analysis, it introduces two additional dimensions: variables and parameters, to allow more effective scoring. These additional dimensions provide the much needed and uniform information that will assist experts with the estimation of probability of occurrence, severity of consequence and safeguards, herein referred to as 3-D methodology. In so doing, it achieves a more systematic approach to risk description and estimation compared to the conventional Risk Priority Number (RPN) of FMECA. Finally, the framework is demonstrated on a real case study of a wave energy converter (WEC) and conclusions of the assessment proved well in comparison and prioritisation.

Offshore wind and wave power are expected to offer viable alternatives to fossil fuels in the future. We assessed the predictability of available global offshore wind and wave power for lead times of up to 9 days using a state-of-the-art wave model and a six-member multi-model ensemble of operational numerical weather predictions during the boreal summer and winter for the period 2008–2012. The results show that wave power is predictable over large areas of the global ocean with a prediction error of <20% at a lead time of 3 days. In the tropical ocean, wave power can be accurately predicted even 9 days in advance. The predictability of wind power was generally low compared to that of wave power. However, wind power can be predicted 5 days in advance with the lower ensemble spread in the Pacific trade wind zone.

This paper describes a new maximum power point tracking (MPPT) algorithm developed to control a wave energy converter (WEC) in random seas. This algorithm, named the cycling MPPT algorithm, is compared to a perturb and observe algorithm described in numerous literature. Both algorithms were initially tested during 2012 ocean tests of the half-scale prototype Wave Energy Technology – New Zealand (WET-NZ) WEC off the Oregon coast. During these sea trials the perturb and observe algorithm failed to provide effective control of the WET-NZ, while the cycling algorithm was observed to give effective control. More complete investigations were later carried out using MATLAB-Simulink simulations of an autonomous WEC (AWEC) being developed at Oregon State University. The results of the AWEC simulations also showed the cycling algorithm provided better control than the perturb and observe algorithm. The operation of the cycling algorithm was fully characterized during the AWEC simulations and these results are presented.