Offshore Wind Resource Research Articles

The 3 km Norwegian reanalysis (NORA3) – a validation of offshore wind resources in the North Sea and the Norwegian Sea

Abstract. We validate a new high-resolution (3 km) numerical mesoscale weather simulation for offshore wind power purposes for the time period 2004–2016 for the North Sea and the Norwegian Sea. The 3 km Norwegian reanalysis (NORA3) is a dynamically downscaled data set, forced with state-of-the-art atmospheric reanalysis as boundary conditions. We conduct an in-depth validation of the simulated wind climatology towards the observed wind climatology to determine whether NORA3 can serve as a wind resource data set in the planning phase of future offshore wind power installations. We place special emphasis on evaluating offshore wind-power-related metrics and the impact of simulated wind speed deviations on the estimated wind power and the related variability. We conclude that the NORA3 data are well suited for wind power estimates but give slightly conservative estimates of the offshore wind metrics. In other words, wind speeds in NORA3 are typically 5 % (0.5 m s−1) lower than observed wind speeds, giving an underestimation of offshore wind power of 10 %–20 % (equivalent to an underestimation of 3 percentage points in the capacity factor) for a selected turbine type and hub height. The model is biased towards lower wind power estimates due to overestimation of the wind speed events below typical wind speed limits of rated wind power (u<11–13 m s−1) and underestimation of high-wind-speed events (u>11–13 m s−1). The hourly wind speed and wind power variability are slightly underestimated in NORA3. However, the number of hours with zero power production caused by the wind conditions (around 12 % of the time) is well captured, while the duration of each of these events is slightly overestimated, leading to 25-year return values for zero-power duration being too high for the majority of the sites. The model performs well in capturing spatial co-variability in hourly wind power production, with only small deviations in the spatial correlation coefficients among the sites. We estimate the observation-based decorrelation length to be 425.3 km, whereas the model-based length is 19 % longer.

Impact of the wake deficit model on wind farm yield: A study of yaw-based control optimization

The exploitation of offshore wind resources is considered to have considerable potential in providing carbon-free energy. To increase the economic viability of wind farms, improvement in power generation is sought by mitigating the wake losses. While the industrial standards still favour turbine-level power maximization, the concept of collaborative yaw-based plant-level control has gained significant attention in recent years. The present work investigates the potential of such a wind farm control strategy employing different wake deficit models, for a range of atmospheric conditions and plant layouts. The utilized wake velocity deficit models are the top-hat Jensen model, the Gaussian-shaped Bastankhah model and its novel extension, termed Gauss–Curl Hybrid model, which accounts for secondary steering effects. The yaw control optimization is conducted on a row of eight NREL 5-MW turbines using the FLORIS modelling utility and the SLSQP optimization algorithm. Generally speaking, the Jensen model shows a lack of robustness and is not recommended for yaw control studies. In contrast, the two Gaussian-shaped models are well handled by the optimization algorithm and produce consistent results. More specifically, the Bastankhah model prefers yaw offsets of nearly equal magnitude throughout the whole wind farm except for the most downstream machine that remains aligned with the freestream. On the other hand, the GCH model suggests a large offset at the most upstream turbine, which is gradually reduced at consecutive machines. For the reference wind farm considered, the total power improvement was 3.59% and 14.66% for the Bastankhah and GCH models, respectively.

Evaluating the suitability of Sentinel-1 SAR data for offshore wind resource assessment around Cyprus

Offshore wind offers an excellent opportunity for domestic renewable energy production with a vast potential for future energy systems. Offshore wind resource assessment, however, can be challenging. Remote sensing data e.g., Synthetic Aperture Radar (SAR), provide high spatial resolution detailed information on the spatial variability of offshore wind and have been used for wind resource assessment, as well as for the long-term validation of wind speed estimates from other sources (e.g. Numerical Weather Prediction models). This paper focuses on the evaluation of a 26-month time-series of Sentinel-1 SAR Level 2 OCN products for wind resource assessment in the offshore areas around Cyprus. Sentinel data were evaluated against a 10-year regional reanalysis dataset (UERRA) time-series and wind measurements from 5 coastal meteorological stations in Cyprus. Comparison revealed an overall agreement between the fitted stations and Sentinel Weibull distributions while discrepancies exist between the two data sources and UERRA. Bias observed between Sentinel and UERRA Weibull-derived statistics appears to be spatially dependent. Preliminary wind power assessment results indicate a significant wind power potential for the southwestern offshore areas of Cyprus, surpassing 400 W/m2 on average, offering thus economically viable solutions in terms of a future offshore wind power project development.

Effect of Climate Variability Events over the Colombian Caribbean Offshore Wind Resource

The need for reducing the CO2 emissions and fossil fuel dependence of several countries generated a growing interest for the Renewables. The Caribbean Sea is characterized by persistent and high magnitude winds, which suggest an important source of offshore wind energy. Recent studies reported that the Colombian Caribbean has a relevant opportunity for developing the offshore wind technology which could complement the energy production when the hydroelectric system is under low generation due to persistent dry conditions generated by El Niño events. The offshore wind energy may complement the energy offer of Colombia. Hence, understanding the impact of climate variability events in the Caribbean over the wind magnitude, contributes to the knowledge of the resource availability for a better planning of future offshore wind farms. In this sense, this study analyzed 39 years of Reanalysis wind data through a time series analysis of the Caribbean to identify the lowest wind speed velocities and when and why they occurred. The results showed that winds of the study area represented by the Caribbean Low level, showed the lowest wind speeds in the short, mid, and long term due to the influence of the seasons, El Niño-Southern Oscillation (ENSO) and the Atlantic Multidecadal Oscillation (AMO).

Assessing boundary condition and parametric uncertainty in numerical-weather-prediction-modeled, long-term offshore wind speed through machine learning and analog ensemble

Abstract. To accurately plan and manage wind power plants, not only does the time-varying wind resource at the site of interest need to be assessed but also the uncertainty connected to this estimate. Numerical weather prediction (NWP) models at the mesoscale represent a valuable way to characterize the wind resource offshore, given the challenges connected with measuring hub-height wind speed. The boundary condition and parametric uncertainty associated with modeled wind speed is often estimated by running a model ensemble. However, creating an NWP ensemble of long-term wind resource data over a large region represents a computational challenge. Here, we propose two approaches to temporally extrapolate wind speed boundary condition and parametric uncertainty using a more convenient setup in which a mesoscale ensemble is run over a short-term period (1 year), and only a single model covers the desired long-term period (20 year). We quantify hub-height wind speed boundary condition and parametric uncertainty from the short-term model ensemble as its normalized across-ensemble standard deviation. Then, we develop and apply a gradient-boosting model and an analog ensemble approach to temporally extrapolate such uncertainty to the full 20-year period, for which only a single model run is available. As a test case, we consider offshore wind resource characterization in the California Outer Continental Shelf. Both of the proposed approaches provide accurate estimates of the long-term wind speed boundary condition and parametric uncertainty across the region (R2>0.75), with the gradient-boosting model slightly outperforming the analog ensemble in terms of bias and centered root-mean-square error. At the three offshore wind energy lease areas in the region, we find a long-term median hourly uncertainty between 10 % and 14 % of the mean hub-height wind speed values. Finally, we assess the physical variability in the uncertainty estimates. In general, we find that the wind speed uncertainty increases closer to land. Also, neutral conditions have smaller uncertainty than the stable and unstable cases, and the modeled wind speed in winter has less boundary condition and parametric sensitivity than summer.

Review on Dynamics of Offshore Floating Wind Turbine Platforms

This paper presents a literature review of the dynamics of offshore floating wind turbine platforms. When moving further offshore, there is an increase in the capacity of wind power. Generating power from renewable resources is enhanced through the extraction of wind energy from an offshore deep-water wind resource. Mounting the turbine on a platform that is not stable brings another difficulty to wind turbine modeling. There is a need to introduce platforms that are more effective to capture this energy, because of the complex dynamics and control of these platforms. This paper highlights the historical developments and progresses in the design of different types of offshore floating wind turbine platforms needed for harvesting the energy from offshore winds. The relative advantages and disadvantages of the platform types with the design challenges are discussed. The major types of floating platforms included in this study are tension leg platform (TLP) type, spar type, and semisubmersible type. This study reviews the previous work on the dynamics of the floating platforms for a single turbine and multiple turbines under various operating environmental conditions. The numerical methods to analyze the aerodynamics of the wind turbine and hydrodynamics of floating platforms are discussed in this paper. This paper also investigates the performance of analytical wake loss models of Jensen, Larsen, and Frandsen that can provide guidelines for using these wake models in future applications. There are still a lot of challenges that need to be addressed to study the accurate behavior of floating platforms operating under combined wind–wave environmental conditions. With the current technological advancements, the offshore floating multi-turbine platform can be a potential solution to harness the abundant offshore wind resource. Based on this literature review, recommendations for future work are suggested.

GIS-based multi-criteria analysis of offshore wind farm development in Morocco

• GIS-based model using the FAHP for offshore wind farm site suitability analysis. • Different technical, socio-economic and environmental criteria are considered. • Morocco has a great potential for offshore wind farm development. This investigation focuses on offshore wind resource assessment in Morocco using an integrated methodology consisting of Geographic Information System and the Fuzzy Analytic Hierarchy Process. Following the published literature and regional necessities, a set of suitability criteria is defined including eight different site selection criteria and six exclusion factors. A weighted overlay analysis is conducted in order to map the ideal locations for offshore wind energy development in Morocco. The study results highlight a wide offshore area that is most suited for wind farm development. Three high suitable areas are shortlisted within the Atlantic Ocean boundary of Morocco, in proximity to the cities of Essaouira, Boujdour, and Dakhla. The three selected areas are capable of generating around 13.3 GW of electrical power. The suggested methodology can be of immense aid for locating the most suitable areas for offshore wind farms in different regions having equivalent geo-factors.

How important are ports for the offshore wind industry?: the case of Spain

Offshore wind is becoming a new technology to develop a better sustainable world. Its progress is linked to the use of port facilities, where the offshore wind farms can be stored or pre-installed. The aim of this paper is to analyse the storage space availability for ports in terms of being used for the new offshore wind sector. The case of study will be focused on analysing the port facilities in Spain, country with a great offshore wind resource in some specific areas. Results indicate the ports that can be used for the development of offshore wind in Spain. This work is important in order to establish a roadmap of the offshore wind business in Spain, which can repair the economic and social damaged due to SARS-CoV-2 pandemic.

Offshore wind can power Canada

As a maritime nation, Canada is the home to high-quality offshore wind resources. The assessment of Canada's offshore wind resources has a strategic significance for realizing its low-carbon future. This study focused on high-resolution and high-accuracy estimates of offshore wind resources over Canada using satellite-derived wind maps, e.g., CCMP (Cross-Calibrated Multi-Platform) images from 1988 to 2017. The CCMP derived wind speed and density were bias-corrected by ocean surface wind measurements collected from 63 stations located along the seas/lakes in Canada from 1987 to 2018. A series of consistent offshore wind resource maps were produced and analyzed. The results generated from CCMP were then compared with previous assessment (i.e., Environment and Climate Change Canada (ECCC)'s Wind Atlas) and proved to perform better in simulating wind speeds. We estimated the technically available offshore wind area, gross power capacity and gross potential over Canada. For example, a gross potential production of 20.348, 20.441, and 20.376 PWh/year were calculated using three commercial offshore wind turbines, i.e. GE 3.6s, REpower 5 M, and V164–8.0 over the calculated total gross offshore area of 1.053 million km2. It far exceeds the Canada's electricity consumption (i.e., 0.641 PWh) in 2018. In addition, most of the potential power productions are distributed in the Canadian Atlantic and Pacific Oceans, Hudson Bay and St Lawrence, with the mean wind speeds increasing from 1988 to 2017. This study can help to assess offshore wind resources and provide decision-makers with some scientific evidences for developing offshore wind in Canada.

Quantitative insights into the differences of variability and intermittency between wind and solar resources on spatial and temporal scales in China

Variability and intermittency are the intrinsic nature of wind and solar resources. Expanded wind and solar power development in China requires a deeper understanding of their differences in variability and intermittency, both spatially and temporally. To address this issue, this study provides a systematic quantitative comparison of the variability and intermittency between wind and solar resources across China. Compared with wind resources, solar resources show regular spatial patterns and highly similar temporal characteristics. Solar resources usually have larger daily variation amplitudes (1.0–3.5 times) and are more intermittent (1.0–10.0 times) than wind resources in most regions. Solar resources fluctuate 1.0–8.0 times faster than wind resources in western Xinjiang, most of central and southern China, and north and east of northeast China. However, the variation rate of solar resources is approximately 0.1–0.5 times the wind resources in the Qinghai–Tibet plateau and East China Sea. In general, wind and solar resources fluctuate faster and are more intermittent in spring and autumn. Onshore wind resources are more variable and intermittent in the periods of 6:00–12:00 and 16:00–22:00. However, the variability and intermittency of offshore wind resources are weak and have very small intra-day changes compared with onshore wind resources. Solar resources are usually more variable and intermittent during the periods of 2–4 h after sunrise and 2–4 h before sunset. Furthermore, the intra-day changes in the variability and intermittency of solar resources are significantly greater than the inter-month changes. Those quantitative insights contribute to better and more efficiently mitigate the variability and intermittency of wind and solar resources.

New methods to improve the vertical extrapolation of near-surface offshore wind speeds

Abstract. Accurate characterization of the offshore wind resource has been hindered by a sparsity of wind speed observations that span offshore wind turbine rotor-swept heights. Although public availability of floating lidar data is increasing, most offshore wind speed observations continue to come from buoy-based and satellite-based near-surface measurements. The aim of this study is to develop and validate novel vertical extrapolation methods that can accurately estimate wind speed time series across rotor-swept heights using these near-surface measurements. We contrast the conventional logarithmic profile against three novel approaches: a logarithmic profile with a long-term stability correction, a single-column model, and a machine-learning model. These models are developed and validated using 1 year of observations from two floating lidars deployed in US Atlantic offshore wind energy areas. We find that the machine-learning model significantly outperforms all other models across all stability regimes, seasons, and times of day. Machine-learning model performance is considerably improved by including the air–sea temperature difference, which provides some accounting for offshore atmospheric stability. Finally, we find no degradation in machine-learning model performance when tested 83 km from its training location, suggesting promising future applications in extrapolating 10 m wind speeds from spatially resolved satellite-based wind atlases.

Numerical and Physical Modeling of a Tension-Leg Platform for Offshore Wind Turbines

In order to tap the world wide offshore wind resources above deep waters, cost efficient floating platforms are inevitable. Tension-Leg Platforms (TLPs) could enable that crucial cost reduction in floating wind due to their smaller size and lighter weight compared to spars and semi-submersibles. The continuous development of the GICON®-TLP is driven by computer-aided engineering. So-called aero-hydro-servo-elastic coupled simulations are state-of-the-art for predicting loads and simulating the global system behavior for floating offshore wind turbines. Considering the complexity of such simulations, it is good scientific praxis to validate these numerical calculations by use of scaled model testing. This paper addresses the setup of the scaled model testing as carried out at the offshore basin of the École Centrale de Nantes, as well as the numerical model for the GICON®-TLP. The results of dedicated decay tests of the scaled model are used to validate the computational model at the first stage and to determine the natural frequencies of the system. Besides different challenges to the scaled model during the survey, it was possible to take these difficulties into account when updating the numerical model. The results show good agreements for the tank tests and the numerical model.

A hybrid solution for offshore wind resource assessment from limited onshore measurements

In wind resource assessments, which are critical to the pre-construction of wind farms, measurements by LiDARs or masts are a source of high-fidelity data, but are expensive and scarce in space and time, particularly for offshore sites. On the other hand, numerical simulations, using for example the Weather Research and Forecasting (WRF) model, generate temporally and spatially continuous data with relatively low-fidelity. A hybrid approach is proposed here to combine the merit of measurements and simulations for the assessment of offshore wind. Firstly a temporal data fusion using deep Multi Fidelity Gaussian Process Regression (MF-GPR) is performed to combine the intermittent measurement and the continuous simulation data at an onshore location. Then a spatial data fusion using a neural network with Non-linear Autoregression (NAR) and Non-linear Autoregression with external input (NARX) are conducted to project the wind from onshore to offshore. The numerical and measured wind speeds along the west coast of Denmark were used to evaluate the method. We show that the proposed data fusion technique using a gappy onshore measurement results in accurate offshore wind resource assessment within a 2% margin error.

REFOS: A Renewable Energy Multi-Purpose Floating Offshore System

The present paper deals with the development of a multi-purpose floating tension leg platform (TLP) concept suitable for the combined offshore wind and wave energy resources exploitation, taking into account the prevailing environmental conditions at selected locations along the European coastline. The examined Renewable Energy Multi-Purpose Floating Offshore System (REFOS) platform encompasses an array of hydrodynamically interacting oscillating water column (OWC) devices, moored through tensioned tethers as a TLP platform supporting a 10 MW wind turbine (WT). The system consists of a triangular platform supported by cylindrical floaters, with the WT mounted at the deck’s center and the cylindrical OWC devices at its corners. Details of the modelling of the system are discussed and hydro-aero-elastic coupling between the floater; the mooring system; and the WT is presented. The analysis incorporates the solutions of the diffraction; the motion- and the pressure-dependent radiation problems around the moored structure, along with the aerodynamics of the WT into an integrated design approach validated through extensive experimental hydrodynamic scaled-down model tests. The verified theoretical results attest to the importance of the WT loading and the OWC characteristics on the dynamics of the system.

Uncertainty analysis of the future cost of wind energy on climate change mitigation

We conduct uncertainty analysis on the impacts of the future cost of wind energy on global electricity generation and the value of wind energy to climate change mitigation. We integrate data on global onshore and offshore wind energy cost and resources into the Global Climate Assessment Model (GCAM), and then propagate uncertainty based on distributions derived from an expert elicitation study on the future cost of onshore and offshore wind energy. The share of wind energy electricity generation in 2035, without a global policy on CO2 emissions, ranges between 4% and more than triple the 2019 share of 5.3%. Under a 1.5°C cap, this range is wider, with shares up to 34%. This range of uncertainty implies the need for flexible systems and policies, allowing large amounts to be deployed if needed. We explore whether a breakthrough in wind energy could prevent the demand for natural gas as a bridge technology to a low carbon economy, and find that uncertainty in wind energy is only pertinent for medium-stringency policies, such as a $60/t carbon tax. Under this scenario, there is a 95% chance that the cost of wind energy will be low enough to lead to an immediate reduction in the share of natural gas. In contrast, under a business-as-usual scenario without a breakthrough in cost, natural gas is highly likely to continue increasing in share of electricity generation. Under a 1.5°C cap, natural gas will decrease in share regardless of wind energy cost.

Offshore Wind Resource Assessment of Thailand Using Remote Sensing Technique

This paper presents the evaluation of the offshore wind resource of Thailand (the Gulf of Thailand and the Andaman Sea) using remote sensing technique. The wind speed at height of 10 m above mean sea level (A.M.S.L.) was measured using SeaWinds Scatterometer on QuickSCAT by NASA. The QuickSCAT satellite images in 1999-2009 with resolution of 1ox1o was interpreted and validated using the measured wind speed provided by the ship observation, buoy data and numerical weather prediction models. The wind speed was interpolated for 1 km resolution enhancement and extrapolated to the height of 50 m A.M.S.L.. The monthly and annual mean wind speed maps were presented in order to show the spatial and temporal variation of offshore wind energy potential. Results showed that QuickSCAT satellite images interpretation gave lower bias in the rage of wind speed of 3-18 m/s, however, the bias was high for wind speed more than 20 m/s. It found that offshore mean wind speed at height of 50 m A.M.S.L. was in the range of 3.0-6.0 m/s where the middle part of Thai offshore had the highest potential with the wind speed in the rage of 7.0-10.0 m/s. The offshore wind speed had high potential during June until August due to the influence of southwest monsoon.

Exploiting offshore wind and solar resources in the Mediterranean using ERA5 reanalysis data

Commercial electricity production from marine renewable sources is becoming a necessity at a global scale. Offshore wind and solar resources can be combined to reduce construction and maintenance costs. In this respect, the aim of this study is two-fold: i) analyse offshore wind and solar resource and their variability in the Mediterranean Sea at the annual and seasonal scales based on the recently published ERA5 reanalysis dataset, and; ii) perform a preliminary assessment of some important features of complementarity, synergy, and availability of the examined resources using an event-based probabilistic approach. A robust coefficient of variation is introduced to examine the variability of each resource and a joint coefficient of variation is implemented for the first time to evaluate the joint variability of offshore wind and solar potential. The association between the resources is examined by introducing a robust measure of correlation, along with the Pearson’s r and Kendall’s τ correlation coefficient and the corresponding results are compared. Several metrics are used to examine the degree of complementarity affected by variability and intermittency issues. Areas with high potential and low variability for both resources include the Aegean and Alboran seas, while significant synergy (over 52%) is identified in the gulfs of Lion, Gabes and Sidra, Aegean Sea and northern Cyprus Isl. The advantage of combining these two resources is highlighted at selected locations in terms of the monthly energy production.

Understanding and mitigating the impact of data gaps on offshore wind resource estimates

Abstract. Like almost all measurement datasets, wind energy siting data are subject to data gaps that can for instance originate from a failure of the measurement devices or data loggers. This is in particular true for offshore wind energy sites where the harsh climate can restrict the accessibility of the measurement platform, which can also lead to much longer gaps than onshore. In this study, we investigate the impact of data gaps, in terms of a bias in the estimation of siting parameters and its mitigation by correlation and filling with mesoscale model data. Investigations are performed for three offshore sites in Europe, considering 2 years of parallel measurement data at the sites, and based on typical wind energy siting statistics. We find a mitigation of the data gaps' impact, i.e. a reduction of the observed biases, by a factor of 10 on mean wind speed, direction and Weibull scale parameter and a factor of 3 on Weibull shape parameter. With increasing gap length, the gaps' impact increases linearly for the overall measurement period while this behaviour is more complex when investigated in terms of seasons. This considerable reduction of the impact of the gaps found for the statistics of the measurement time series almost vanishes when considering long-term corrected data, for which we refer to 30 years of reanalysis data.

Seasonal distribution and variability of surface winds in the Indonesian seas using scatterometer and reanalysis data

AbstractThe distribution and variability of surface winds in the seas and straits in the Maritime Continent, or the Indonesian seas, are investigated using scatterometer wind measurements and reanalysis wind data. This study focuses on the detailed climatology of surface winds in the Indonesian seas and has significant implications for a better understanding of regional climate, meteorological disasters, and offshore wind resource. The monsoon winds predominantly blow over the seas along the routes formed by the coastlines of the large islands and the chains of the small islands. The wind speeds are persistently strong along these routes, and the major direction of the variability in winds is well aligned with these routes. The wind jets are formed in the central part of the routes. The interisland gaps and channels form wind jets of various scales. The Australian winter monsoon is stronger and more persistent than the East Asian winter monsoon in the Indonesian seas. The onset of each monsoon differs by approximately 40 days between the east and west of the Indonesian seas. The amplitudes and spatial extents of diurnally varying winds dominate along the northern coasts of Java Island and the small islands to the east, along the northwest and northeast coasts of Borneo, along the coast of southern Sulawesi Island, and to the southwest of Papua, and vanish along the centre lines of the monsoon routes. Sea areas with a large amplitude of diurnally varying wind are much the same throughout the year. The amplitude of diurnally varying wind has an annual maximum in September in the southern Indonesian seas, possibly in correspondence with the annual maximum of the temperature difference between land and sea.

Assessing the Technical Offshore Wind Energy Potential in Lagos, Nigeria

Looking at the current state of things globally and the greenhouse effect renewable energy sources are no longer a matter of choice. The population of Lagos coupled with the perpetually erratic power supply makes renewable energy the new and sure way to go especially as an alternative supply of electricity. The nation as a whole has a peak generation of 5300MW on average which is only about 30% of its actual needs. The use of renewable energy in Nigeria is growing but so is the population this study seeks to ascertain the possibility of using offshore wind energy as an alternative power supply in Lagos Nigeria. The onshore wind energy resource has been fairly explored but its counterpart offshore wind energy has not been explored. This study focuses on the technical assessment of offshore wind resources on the Gulf of Guinea around the Lagos Nigeria region. Having analysed wind data from existing literature and analysed offshore wind farm construction the paper presents a technical layout of the number of turbines per the specified area and the potential output using Aerodyn SCD 8.0/168 as a case study. The results show that the annual energy demand of about 96.36TWh in Lagos can be met with the annual generation of about 191.2TWh for a wind farm at the shore and 200TWh for waters with depth less than 50m.