scholarly journals Combining shallow-water and analytical wake models for tidal array micro-siting

2021 ◽  
Author(s):  
Connor Jordan ◽  
Davor Dundovic ◽  
Anastasia Fragkou ◽  
Georgios Deskos ◽  
Daniel Coles ◽  
...  
Keyword(s):  
Computational Cost ◽  
Complex Problem ◽  
Ocean Model ◽  
Power Performance ◽  
Flow Speeds ◽  
Tidal Stream ◽  
Entire Flow ◽  
Wake Model ◽  
Placement Algorithm ◽  
Hydrodynamic Effects

Array optimisation is critical for improving power performance and reducing infrastructure costs thereby helping enable tidal-stream energy to become a competitive renewable energy source. However, ascertaining an optimal array layout is a highly complex problem, subject to the specific site hydrodynamics characterisation and multiple inter-disciplinary constrains. In this work, we present a novel optimisation approach that combines an analytical-based wake model, FLORIS, with an ocean model, Thetis. The approach is demonstrated with applications of increasing complexity. By utilising the method of analytical wake superposition, the addition or alteration of turbine position does not require re-calculation of the entire flow field, thus allowing the use of simple heuristic techniques to perform optimisation at a fraction of the computational cost of more sophisticated methods. Using a custom condition-based placement algorithm, this methodology is applied to the Pentland Firth for 24 turbines with a rated speed of 3.05 m/s, demonstrating practical implications whilst also considering the temporal variability of the tide. Micro-siting using this technique generated an array 12% more productive on average than a staggered layout, despite flow speeds regularly exceeding the rated value. Performance was further evaluated through assessment of the optimised layout within the ocean model that represents the turbines through a discrete turbine representation.Used iteratively, this methodology could be applied to deliver improved array configurations in a manner that accounts for local hydrodynamic effects.

scholarly journals Hydrodynamic Effects of Tidal-Stream Power Extraction for Varying Turbine Operating Conditions

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3240
Author(s):  
Lilia Flores Mateos ◽  
Michael Hartnett
Keyword(s):  
Thrust Force ◽  
Operating Conditions ◽  
Blockage Ratio ◽  
Stream Power ◽  
Power Extraction ◽  
Tidal Stream ◽  
Electrical Generation ◽  
Hydrodynamic Effects ◽  
Turbine Wake ◽  
Tidal Stream Power

Realistic evaluation of tidal-stream power extraction effects on local hydrodynamics requires the inclusion of the turbine’s operating conditions (TOC). An alternative approach for simulating the turbine’s array energy capture at a regional scale, momentum sink-TOC, is used to assess the impact of power extraction. The method computes a non-constant thrust force calculated based on the turbine’s operating conditions, and it uses the wake induction factor and blockage ratio to characterise the performance of a turbine. Additionally, the momentum sink-TOC relates the changes produced by power extraction, on the velocity and sea surface within the turbine’s near-field extension, to the turbine’s thrust force. The method was implemented in two hydrodynamic models that solved gradually varying flows (GVF) and rapidly varying flows (RVF). The local hydrodynamic effects produced by tidal-stream power extraction for varying the turbine’s operating conditions was investigated in (i) the thrust and power coefficient calculation, (ii) flow rate reduction, and (iii) tidal currents’ velocity and elevation profiles. Finally, for a turbine array that operates at optimal conditions, the potential energy resource was assessed. The maximisation of power extraction for electrical generation requires the use of an optimum turbine wake induction factor and an adequate blockage ratio, so that the power loss due to turbine wake mixing is reduced. On the other hand, the situations where limiting values of these parameters are used should be avoided as they lead to negligible power available. In terms of hydrodynamical models, an RVF solver provided a more accurate evaluation of the turbine’s operating conditions effect on local hydrodynamics. Particularly satisfactory results were obtained for a partial-fence. In the case of a fence configuration, the GVF solver was found to be a computationally economical tool to pre-assess the resource; however, caution should be taken as the solver did not accurately approximate the velocity decrease produced by energy extraction.

scholarly journals The energy yield potential of a large tidal stream turbine array in the Alderney Race

2020 ◽  
Vol 378 (2178) ◽  
pp. 20190502 ◽  
Author(s):  
D. S. Coles ◽  
L. S. Blunden ◽  
A. S. Bahaj
Keyword(s):  
Large Scale ◽  
Tidal Energy ◽  
Yield Potential ◽  
Energy Yield ◽  
Ambient Flow ◽  
Flow Speeds ◽  
Tidal Stream ◽  
Original Array ◽  
Array Performance ◽  
Tidal Stream Turbine

This research provides an updated energy yield assessment for a large tidal stream turbine array in the Alderney Race. The original array energy yield estimate was presented in 2004. Enhancements to this original work are made through the use of a validated two-dimensional hydrodynamic model, enabling the resolution of flow modelling to be improved and the impacts of array blockage to be quantified. Results show that a range of turbine designs (i.e. rotor diameter and power capacity) are needed for large-scale development, given the spatial variation in bathymetry and flow across the Alderney Race. Array blockage causes a reduction in flow speeds in the array of up to 2.5 m s −1 , increased flow speeds around the array of up to 1 m s −1 and a reduction in the mean volume flux through the Alderney Race of 8%. The annual energy yield estimate of the array is 3.18 TWh, equivalent to the electricity demand of around 1 million homes. The capacity factor of the array is 18%, implying sub-optimal array design. This result demonstrates the need for turbine rated speed to be selected based on the altered flow regime, not the ambient flow. Further enhancement to array performance is explored through increases to rotor diameter and changes to device micro-siting, demonstrating the significant potential for array performance improvement. This article is part of the theme issue ‘New insights on tidal dynamics and tidal energy harvesting in the Alderney Race’.

scholarly journals Multi-Physics Ensemble versus Atmosphere–Ocean Coupled Model Simulations for a Tropical-Like Cyclone in the Mediterranean Sea

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 202 ◽  
Author(s):  
Antonio Ricchi ◽  
Mario Marcello Miglietta ◽  
Davide Bonaldo ◽  
Guido Cioni ◽  
Umberto Rizza ◽  
...  
Keyword(s):  
High Resolution ◽  
Mediterranean Sea ◽  
Computational Cost ◽  
Ocean Model ◽  
Surface Fluxes ◽  
Ocean Modeling ◽  
Sea Surface ◽  
Regional Ocean Modeling System ◽  
The Mediterranean ◽  
Physics Ensemble

Between 19 and 22 January 2014, a baroclinic wave moving eastward from the Atlantic Ocean generated a cut-off low over the Strait of Gibraltar and was responsible for the subsequent intensification of an extra-tropical cyclone. This system exhibited tropical-like features in the following stages of its life cycle and remained active for approximately 80 h, moving along the Mediterranean Sea from west to east, eventually reaching the Adriatic Sea. Two different modeling approaches, which are comparable in terms of computational cost, are analyzed here to represent the cyclone evolution. First, a multi-physics ensemble using different microphysics and turbulence parameterization schemes available in the WRF (weather research and forecasting) model is employed. Second, the COAWST (coupled ocean–atmosphere wave sediment transport modeling system) suite, including WRF as an atmospheric model, ROMS (regional ocean modeling system) as an ocean model, and SWAN (simulating waves in nearshore) as a wave model, is used. The advantage of using a coupled modeling system is evaluated taking into account air–sea interaction processes at growing levels of complexity. First, a high-resolution sea surface temperature (SST) field, updated every 6 h, is used to force a WRF model stand-alone atmospheric simulation. Later, a two-way atmosphere–ocean coupled configuration is employed using COAWST, where SST is updated using consistent sea surface fluxes in the atmospheric and ocean models. Results show that a 1D ocean model is able to reproduce the evolution of the cyclone rather well, given a high-resolution initial SST field produced by ROMS after a long spin-up time. Additionally, coupled simulations reproduce more accurate (less intense) sea surface heat fluxes and a cyclone track and intensity, compared with a multi-physics ensemble of standalone atmospheric simulations.

Effects on hydrodynamics and ecological costs of climate change and tidal stream energy extraction in a shelf sea

2020 ◽  
Author(s):  
Michela De Dominicis ◽  
Judith Wolf ◽  
Dina Sadykova ◽  
Beth Scott ◽  
Alexander Sadykov ◽  
...  
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Scenario ◽  
Tidal Energy ◽  
Ocean Model ◽  
Future Climate ◽  
Biogeochemical Model ◽  
Energy Extraction ◽  
Shelf Sea ◽  
Tidal Stream

<p>The aim of this work is to analyse the potential impacts of tidal energy extraction on the marine environment. We wanted to put them in the broader context of the possibly greater and global ecological threat of climate change. Here, we present how very large (hypothetical) tidal stream arrays and a ''business as usual'' future climate scenario can change the hydrodynamics of a seasonally stratified shelf sea, and consequently modify ecosystem habitats and animals’ behaviour.</p><p>The Scottish Shelf Model, an unstructured grid three-dimensional ocean model, has been used to reproduce the present and the future state of the NW European continental shelf. While the marine biogeochemical model ERSEM (European Regional Seas Ecosystem Model) has been used to describe the corresponding biogeochemical conditions. Four scenarios have been modelled: present conditions and projected future climate in 2050, each with and without very large scale tidal stream arrays in Scottish Waters (UK). This allows us to evaluate the potential effect of climate change and large scale energy extraction on the hydrodynamics and biogeochemistry. We found that climate change and tidal energy extraction both act in the same direction, in terms of increasing stratification due to warming and reduced mixing, however, the effect of climate change is ten times larger. Additionally, the ecological costs and benefits of these contrasting pressures on mobile predator and prey marine species are evaluated using ecological statistical models.</p>

scholarly journals Monitoring offshore wind farm power performance with SCADA data and an advanced wake model

2017 ◽  
Vol 2 (1) ◽  
pp. 175-187 ◽  
Author(s):  
Niko Mittelmeier ◽  
Tomas Blodau ◽  
Martin Kühn
Keyword(s):  
Power Output ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Power Performance ◽  
Power Normalization ◽  
Efficient Detection ◽  
Asset Value ◽  
Output Ratio ◽  
Wake Model

Abstract. Wind farm underperformance can lead to significant losses in revenues. The efficient detection of wind turbines operating below their expected power output and immediate corrections help maximize asset value. The method, presented in this paper, estimates the environmental conditions from turbine states and uses pre-calculated lookup tables from a numeric wake model to predict the expected power output. Deviations between the expected and the measured power output ratio between two turbines are an indication of underperformance. The confidence of detected underperformance is estimated by a detailed analysis of the uncertainties of the method. Power normalization with reference turbines and averaging several measures performed by devices of the same type can reduce uncertainties for estimating the expected power. A demonstration of the method's ability to detect underperformance in the form of degradation and curtailment is given. An underperformance of 8 % could be detected in a triple-wake condition.

scholarly journals Monitoring offshore wind farm power performance with SCADA data and advanced wake model

2016 ◽  
Author(s):  
Niko Mittelmeier ◽  
Tomas Blodau ◽  
Martin Kühn
Keyword(s):  
Power Output ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Power Performance ◽  
Efficient Detection ◽  
Asset Value ◽  
Measurement Devices ◽  
Wake Model ◽  
Measured Power

Abstract. Wind farm underperformance can lead to significant losses in revenues. Efficient detection of wind turbines operating below their expected power output and immediate corrections help maximise asset value. The presented method estimates the environmental conditions from turbine states and uses pre-calculated power matrices from a numeric wake model to predict the expected power output. Deviations between the expected and the measured power output are an indication of underperformance. The confidence of detected underperformance is estimated by detailed analysis of uncertainties of the method. Power normalisation with reference turbines and averaging several measurement devices can reduce uncertainties for estimating the expected power. A demonstration of the method’s ability to detect underperformance in the form of degradation and curtailment is given. Underperformance of 8 % could be detected in a triple wake condition.

scholarly journals Efficient estimation of time-mean states of ocean models using 4D-Var and implicit time-stepping

2007 ◽  
Vol 14 (6) ◽  
pp. 777-788
Author(s):  
A. D. Terwisscha van Scheltinga ◽  
H. A. Dijkstra
Keyword(s):  
Ocean Circulation ◽  
Signal To Noise Ratio ◽  
Singular Spectrum Analysis ◽  
Computational Cost ◽  
Ocean Model ◽  
Efficient Estimation ◽  
Implicit Time ◽  
Time Stepping ◽  
High Frequency Variability ◽  
Mean State

Abstract. We propose an efficient method for estimating a time-mean state of an ocean model subject to given observations using implicit time-stepping. The new method uses (i) an implicit implementation of the 4D-Var method to fit the model trajectory to the observations, and (ii) a pre-processor which applies a multi-channel singular spectrum analysis to enhance the signal-to-noise ratio of the observational data and to filter out the high frequency variability. This approach enables one to estimate the time-mean model state using larger time-steps than is possible with an explicit model. The performance of the method is presented for two test cases within a barotropic quasi-geostrophic nonlinear model of the wind-driven double-gyre ocean circulation. The method turns out to be accurate and, in comparison with the time-mean state computed with an explicit version of the model, relatively cheap in computational cost.

Efficient Dynamic Analysis of a Nonlinear Wave Energy Harvester Model

2016 ◽  
Vol 138 (4) ◽  
Author(s):  
Pol D. Spanos ◽  
Felice Arena ◽  
Alessandro Richichi ◽  
Giovanni Malara
Keyword(s):  
Monte Carlo ◽  
Linear System ◽  
Wave Energy ◽  
Alternative Energy ◽  
Energy Harvester ◽  
Single Point ◽  
Computational Cost ◽  
Complex Problem ◽  
Statistical Linearization ◽  
Monte Carlo Techniques

In recent years, wave energy harvesting systems have received considerable attention as an alternative energy source. Within this class of systems, single-point harvesters are popular at least for preliminary studies and proof-of-concept analyses in particular locations. Unfortunately, the large displacements of a single-point wave energy harvester are described by a set of nonlinear equations. Further, the excitation is often characterized statistically and in terms of a relevant power spectral density (PSD) function. In the context of this complex problem, the development of efficient techniques for the calculation of reliable harvester response statistics is quite desirable, since traditional Monte Carlo techniques involve nontrivial computational cost. The paper proposes a statistical linearization technique for conducting expeditiously random vibration analyses of single-point harvesters. The technique is developed by relying on the determination of a surrogate linear system identified by minimizing the mean square error between the linear system and the nonlinear one. It is shown that the technique can be implemented via an iterative procedure, which allows calculating statistics, PSDs, and probability density functions (PDFs) of the response components. The reliability of the statistical linearization solution is assessed vis-à-vis data from relevant Monte Carlo simulations. This novel approach can be a basis for constructing computationally expeditious assessments of various design alternatives.

The value of tidal-stream energy resource to off-grid communities

2020 ◽  
Author(s):  
Matt Lewis ◽  
John Maskell ◽  
Daniel Coles ◽  
Michael Ridgill ◽  
Simon Neill
Keyword(s):  
Energy Resource ◽  
Distribution Networks ◽  
Ocean Model ◽  
Offshore Wind ◽  
Published Data ◽  
Electricity Supply ◽  
Power Curve ◽  
Mean Flow ◽  
Tidal Stream ◽  
Tidal Stream Energy

<p>Tidal-stream energy research has often focused on the applicability of the resource to large electricity distribution networks, or reducing costs so it can compete with other renewables (such as offshore wind). Here we explore how tidal electricity may be worth the additional cost, as the quality and predictability of the electricity could be advantageous – especially to remote “off-grid” communities and industry.</p><p>The regular motion from astronomical forces allows the tide to be predicted far into the future, and therefore idealised scenarios of phasing tidal electricity supply to demand can be explored. A normalised tidal-stream turbine power curve, developed from published data on 15 devices, was developed. Tidal harmonics of a region, based on ocean model output, were used in conjunction with this normalised tidal-stream power curve, and predictions of yield and the timing of electricity supply were made. Such analysis allows the type and number of turbines needed for a specific community requirement, as well as a resource-led tidal turbine optimisation for a region. For example, with a simple M2 tide (12.42hour period) of 2m/s peak flow, which represents mean flow conditions, a rated turbine speed of 1.8m/s gives the highest yield-density of all likely turbine configurations (i.e. calculated from power density and so ignores turbine diameter), and with a 41% Capacity Factor. Furthermore, as tidal current and power predictions can be made, we explore the battery size needed for a given electricity demand timeseries (e.g. baseload, or offshore aquaculture). Our analysis finds tidal-stream energy could be much more useful than other forms of renewable energy to off-grid communities due to the predictability and persistence of the electricity supply. Moreover, our standardised power curve method will facilitate technical tidal energy resource assessment for any region.</p>

scholarly journals ALGORITMOS GENÉTICOS APLICADOS NA CRIAÇÃO DE AGENDAS DE HORÁRIO SEMANAL DE AULAS

2019 ◽  
Vol 11 (4) ◽  
pp. 1-9
Author(s):  
Raildo Santos de Lima ◽  
Nilmaer Souza da Silva ◽  
Rafael Bratifich ◽  
Renato Carlos Camacho Neves
Keyword(s):  
Genetic Algorithms ◽  
Computational Cost ◽  
Complex Problem ◽  
Class Schedule

Determining a weekly class schedule is a computationally complex problem whose computational cost can increase exponentially in relation to the number of variables involved in the solution. There areseveral software on the market that build this timetable based on deterministic rules. Alternatively, we intend to build this solution using Genetic Algorithms, making use of its exploratory capacity in multidimensional spaces.

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