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

2021 ◽  
Vol 6 (6) ◽  
pp. 1501-1519
Author(s):  
Ida Marie Solbrekke ◽  
Asgeir Sorteberg ◽  
Hilde Haakenstad
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Offshore Wind ◽  
Data Set ◽  
Norwegian Sea ◽  
Offshore Wind Power ◽  
Wind Speeds ◽  
The North ◽  
The North Sea ◽  
Simulated Wind

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.

scholarly journals Norwegian hindcast archive (NORA3) – A validation of offshore wind resources in the North Sea and Norwegian Sea

2021 ◽  
Author(s):  
Ida Marie Solbrekke ◽  
Asgeir Sorteberg ◽  
Hilde Haakenstad
Keyword(s):  
Wind Power ◽  
Power Production ◽  
Offshore Wind ◽  
Norwegian Sea ◽  
Offshore Wind Power ◽  
Wind Speeds ◽  
The North ◽  
The North Sea ◽  
Wind Events ◽  
Simulated Wind

Abstract. A new high-resolution (3 km) numerical mesoscale weather simulation spanning the period 2004–2018 is validated for offshore wind power purposes for the North Sea and Norwegian Sea. The NORwegian hindcast Archive (NORA3) was created by dynamical downscaling, forced with state-of-the-art hourly atmospheric reanalysis as boundary conditions. A validation of the simulated wind climatology has been carried out to determine the ability of NORA3 to act as a tool for planning future offshore wind power installations. Special emphasis is placed on evaluating offshore wind power-related metrics and the impact of simulated wind speed deviations on the estimated wind power and the related variability. The general conclusion of the validation is that the NORA3 data is rather well suited for wind power estimates, but gives slightly conservative estimates on the offshore wind metrics. Wind speeds are typically 5 % (0.5 ms−1) lower than observed wind speeds, giving an underestimation of offshore wind power of 10 %–20 % (equivalent to an underestimation of 3 percentage point in the capacity factor), for a selected turbine type and hub height. The model is biased towards lower wind power estimates because of overestimation of the frequency of low-speed wind events (< 10 ms−1) and underestimation of high-speed wind events (> 10 ms−1). The hourly wind speed and wind power variability are slightly underestimated in NORA3. However, the number of hours with zero power production (around 12 % of the time) is fairly 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 four of the six sites. The model is relatively good at capturing spatial co-variability in hourly wind power production among the sites. However, the observed decorrelation length was estimated to be 432 km, whereas the model-based length was 19 % longer.

scholarly journals North Sea region energy system towards 2050: integrated offshore grid and sector coupling drive offshore wind installations

2020 ◽  
Author(s):  
Matti Koivisto ◽  
Juan Gea-Bermúdez ◽  
Polyneikis Kanellas ◽  
Kauhshik Das ◽  
Poul Sørensen
Keyword(s):  
Power Plant ◽  
Wind Power ◽  
North Sea ◽  
Energy System ◽  
Offshore Wind ◽  
Wind Power Plant ◽  
Offshore Wind Power ◽  
The North ◽  
The North Sea ◽  
Wind Curtailment

Abstract. This paper analyses several energy system scenarios towards 2050 for the North Sea region. With focus on offshore wind power, the impacts of meshed offshore grid and sector coupling are studied. First, a project-based scenario, where each offshore wind power plant is connected individually to onshore, is compared to a meshed grid scenario. Both the amount of offshore wind installed and the level of curtailment are assessed. Then, these results are compared to a scenario with sector coupling included. The results show that while the introduction of a meshed grid can increase the amount of offshore wind installed towards 2050, sector coupling is expected to be a more important driver for increasing offshore wind installations. In addition, sector coupling can significantly decrease the level of offshore wind curtailment.

scholarly journals A new roughness parameterization accounting for wind-wave (mis)alignment

2018 ◽  
Author(s):  
Sara Porchetta ◽  
Orkun Temel ◽  
Domingo Muñoz-Esparza ◽  
Joachim Reuder ◽  
Jaak Monbaliu ◽  
...  
Keyword(s):  
Wind Wave ◽  
Climate Modeling ◽  
Numerical Models ◽  
Offshore Wind ◽  
Wave Direction ◽  
Data Set ◽  
Wind Speeds ◽  
The North ◽  
Effective Roughness ◽  
The North Sea

Abstract. Two-way feedback occurs between offshore wind and waves. However, the influence of the waves on the wind profile remains remains understudied, in particular the momentum transfer between the sea surface and the atmosphere. Previous studies showed that for swell waves it is possible to have increasing wind speeds in case of aligned wind-wave directions. However, the opposite is valid for opposed wind-wave directions, where a decrease in wind velocity is observed. Up to now, this behavior has not been included in most numerical models due to the lack of an appropriate parameterization of the resulting effective roughness length. Using an extensive data set of offshore measurements in the North Sea and the Atlantic Ocean, we show that the wave roughness affecting the wind is indeed dependent on the alignment between the wind and wave direction. Moreover, we propose a new roughness parameterization taking into account the dependence on alignment, consisting of an enhanced roughness for increasing misalignment. Using this new roughness parameterization in numerical models will facilitate a better representation of offshore wind, which is relevant to many applications including offshore wind energy and climate modeling.

scholarly journals MISALIGNMENT AND LAG TIME OF WIND AND WAVE OCCURRENCE BASED ON 10 YEARS MEASUREMENTS IN THE NORTH SEA NEAR THE GERMAN COAST

2018 ◽  
pp. 13
Author(s):  
Arndt Hildebrandt ◽  
Remo Cossu
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
North Sea ◽  
Offshore Wind ◽  
Wave Loads ◽  
Wind Speeds ◽  
The North ◽  
The North Sea ◽  
The Impact ◽  
The Waves

There are several intentions to analyze the correlation of wind and wave data, especially in the North Sea. Fatigue damage is intensified by wind and wave loads acting from different directions, due to the misaligned aerodynamic damping of the rotor regarding the wave loads from lateral directions. Furthermore, construction time and costs are mainly driven by the operational times of the working vessels, which strongly depend on the wind and wave occurrence and correlation. Turbulent wind can rapidly change its direction and intensity, while the inert water waves react slowly in relation to the wind profile. Tuerk (2008) investigates the impact of wind and turbulence on offshore wind turbines by analyzing data of four years. The study shows that the wave height is increasing with higher wind speeds but when the wind speed drops the reaction of the waves is postponed. The dependence of the wave height on the wind speed is varying because of the atmospheric stability and different wind directions. Fischer et al. (2011) estimated absolute values of misalignment between wind and waves located in the Dutch North Sea. The study presents decreasing misalignment for increasing wind speeds, ranging up to 90 degrees for wind speeds below 12 m/s and up to 30 degrees for wind speeds above 20 m/s. Bredmose et al. (2013) present a method of offshore wind and wave simulation by using metocean data. The study describes characteristics of the wind and wave climate for the North and Baltic Sea as well as the directional distribution of wind and waves. Güner et al. (2013) cover the development of a statistical wave model for the Karaburun coastal zone located at the southwest coast of the Black Sea with the help of wind and wave measurements and showed that the height of the waves is directly correlating with the duration of the wind for the last four hours.

scholarly journals North Sea region energy system towards 2050: integrated offshore grid and sector coupling drive offshore wind power installations

2020 ◽  
Vol 5 (4) ◽  
pp. 1705-1712
Author(s):  
Matti Koivisto ◽  
Juan Gea-Bermúdez ◽  
Polyneikis Kanellas ◽  
Kaushik Das ◽  
Poul Sørensen
Keyword(s):  
Wind Power ◽  
North Sea ◽  
Energy System ◽  
Offshore Wind ◽  
Wind Power Plant ◽  
Offshore Wind Power ◽  
The North ◽  
The North Sea ◽  
Wind Curtailment ◽  
Power Installations

Abstract. This paper analyses several energy system scenarios towards 2050 for the North Sea region. With a focus on offshore wind power, the impacts of meshed offshore grid and sector coupling are studied. First, a project-based scenario, where each offshore wind power plant is connected individually to the onshore power system, is compared to a meshed grid scenario. Both the amount of offshore wind power installed and the level of curtailment are assessed. Then, these results are compared to a scenario with sector coupling included. The results show that while the introduction of a meshed grid can increase the amount of offshore wind power installed towards 2050, sector coupling is expected to be a more important driver for increasing offshore wind power installations. In addition, sector coupling can significantly decrease the level of offshore wind curtailment.

scholarly journals Multi-decadal offshore wind power variability can be mitigated through optimized European allocation

2020 ◽  
Author(s):  
Charlotte Neubacher ◽  
Jan Wohland ◽  
Dirk Witthaut
Keyword(s):  
Power Generation ◽  
Time Series ◽  
Wind Power ◽  
North Sea ◽  
Wind Power Generation ◽  
Offshore Wind ◽  
Offshore Wind Power ◽  
The North ◽  
The North Sea

&lt;p&gt;Wind power generation is a promising technology to reduce greenhouse gas emissions in line with the Paris Agreement. &amp;#160;In the recent years, the global offshore wind market grew around 30% per year but the full potential of this technology is still not fully exploited. In fact, offshore wind power has the potential to generate more than the worldwide energy demand of today. The high variability of wind on many different timescales does, however, pose serious technical challenges for system integration and system security. &amp;#160;With a few exceptions, little focus has been given to multi-decadal variability. Our research therefore focuses on timescales exceeding ten years.&lt;/p&gt;&lt;p&gt;Based on detrended wind data from the coupled centennial reanalysis CERA-20C, we calculate long-term offshore wind power generation time series across Europe and analyze their variability with a focus on the North Sea, the Mediterranean Sea and the Atlantic Ocean. Our approach is based on two independent spectral analysis methods, namely power spectral density and singular spectrum analysis. The latter is particularly well suited for relatively short and noisy time series. In both methods an AR(1)-process is considered as a realistic model for the noisy background. The analysis is complemented by computing the 20yr running mean to also gain insight into long term developments and quantify benefits of large-scale balancing.&lt;/p&gt;&lt;p&gt;We find strong indications for two significant multidecadal modes, which appear consistently independent of the statistical method and at all locations subject to our investigation. Moreover, we reveal potential to mitigate multidecadal offshore wind power generation variability via spatial balancing in Europe. In particular, optimized allocations off the Portuguese coast and in the North Sea allow for considerably more stable wind power generation on multi-decadal time scales.&lt;/p&gt;

scholarly journals Production and Cost Assessment of Offshore Wind Power in the North Sea

2021 ◽  
Vol 1934 (1) ◽  
pp. 012019
Author(s):  
J N Sørensen ◽  
G C Larsen ◽  
A Cazin-Bourguignon
Keyword(s):  
Wind Power ◽  
North Sea ◽  
Offshore Wind ◽  
Cost Assessment ◽  
Offshore Wind Power ◽  
The North ◽  
The North Sea

scholarly journals A new roughness length parameterization accounting for wind–wave (mis)alignment

2019 ◽  
Vol 19 (10) ◽  
pp. 6681-6700 ◽  
Author(s):  
Sara Porchetta ◽  
Orkun Temel ◽  
Domingo Muñoz-Esparza ◽  
Joachim Reuder ◽  
Jaak Monbaliu ◽  
...  
Keyword(s):  
Roughness Length ◽  
Wind Wave ◽  
Climate Modeling ◽  
Numerical Models ◽  
Offshore Wind ◽  
Data Set ◽  
Wind Speeds ◽  
The North ◽  
Effective Roughness ◽  
The North Sea

Abstract. Two-way feedback occurs between offshore wind and waves. However, the influence of the waves on the wind profile remains understudied, in particular the momentum transfer between the sea surface and the atmosphere. Previous studies showed that for swell waves it is possible to have increasing wind speeds in case of aligned wind–wave directions. However, the opposite is valid for opposed wind–wave directions, where a decrease in wind velocity is observed. Up to now, this behavior has not been included in most numerical models due to the lack of an appropriate parameterization of the resulting effective roughness length. Using an extensive data set of offshore measurements in the North Sea and the Atlantic Ocean, we show that the wave roughness length affecting the wind is indeed dependent on the alignment between the wind and wave directions. Moreover, we propose a new roughness length parameterization, taking into account the dependence on alignment, consisting of an enhanced roughness length for increasing misalignment. Using this new roughness length parameterization in numerical models might facilitate a better representation of offshore wind, which is relevant to many applications including offshore wind energy and climate modeling.

Prediction of Wind Speed, Potential Wind Power, and the Associated Uncertainties for Offshore Wind Farm Using Deep Learning

2020 ◽  
Author(s):  
Do-Eun Choe ◽  
Gary Talor ◽  
Changkyu Kim
Keyword(s):  
Power Generation ◽  
Deep Learning ◽  
Wind Speed ◽  
Wind Power ◽  
Wind Power Generation ◽  
Offshore Wind ◽  
Weather Data ◽  
Local Wind ◽  
Offshore Wind Power ◽  
The Future

Abstract Floating offshore wind turbines hold great potential for future solutions to the growing demand for renewable energy production. Thereafter, the prediction of the offshore wind power generation became critical in locating and designing wind farms and turbines. The purpose of this research is to improve the prediction of the offshore wind power generation by the prediction of local wind speed using a Deep Learning technique. In this paper, the future local wind speed is predicted based on the historical weather data collected from National Oceanic and Atmospheric Administration. Then, the prediction of the wind power generation is performed using the traditional methods using the future wind speed data predicted using Deep Learning. The network layers are designed using both Long Short-Term Memory (LSTM) and Bi-directional LSTM (BLSTM), known to be effective on capturing long-term time-dependency. The selected networks are fine-tuned, trained using a part of the weather data, and tested using the other part of the data. To evaluate the performance of the networks, a parameter study has been performed to find the relationships among: length of the training data, prediction accuracy, and length of the future prediction that is reliable given desired prediction accuracy and the training size.

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