| 1. |
- Hallgren, Christoffer, et al.
(författare)
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A Single-Column Method to Identify Sea and Land Breezes in Mesoscale-Resolving NWP Models
- 2023
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Ingår i: Weather and forecasting. - : American Meteorological Society. - 0882-8156 .- 1520-0434. ; 38:6, s. 1025-1039
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Tidskriftsartikel (refereegranskat)abstract
- One of the most prominent mesoscale phenomena in the coastal zone is the sea-breeze/land-breeze circula-tion. The pattern and its implications for the weather in coastal areas are well described, and with mesoscale-resolving operational NWP models the circulation can be captured. In this study, a straightforward method to identify sea and land breezes based on the change in wind direction in the column above a grid point on the coastline is presented. The method was tested for southern Sweden using archived output from the HARMONIE-AROME model with promising results, describing both the seasonal and diurnal cycles well. In areas with a complex coastline, such as narrow straits, the concept of the land-sea breeze becomes less clear, and several ways to address this problem for the suggested method are discussed. With an operational index of the sea and land breezes, the forecaster can better understand and express the weather situation and add value for people in the coastal zone. Further, the indices can be used to study systematic biases in the model and to create climatologies of the sea and land breezes.
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| 2. |
- Hallgren, Christoffer
(författare)
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Assessment of green power production in Antarctica
- 2013
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Traditionally, fossil fuels have been the energy source to power research stations in Antarctica. With increasing awareness of climate change and local environmental effects associated with use of fossil fuels, the demand for replacement green energy power supply have increased rapidly.In this article, the potential for wind and solar power in Antarctica is assessed. The study is based on 34 years of reanalysis data from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) focusing on the location for the experiment ARIANNA (Antarctic Ross Ice-Shelf Antenna Neutrino Array). Results are compared with the stations Mawson and Princess Elisabeth, where wind and solar power already is operational, and with the Amundsen-Scott station.The average wind speed for the ARIANNA site is around 7.5 m/s during winter and 6.0 m/s during summer. Comparing with Princess Elisabeth, the average wind speed is approximately 5 m/s lower.The generally low wind speeds at the ARIANNA site suggest that wind turbines with a low cut-in speed should be used. The strong influence from katabatic winds make wind direction persistent, which is preferable.The potential for solar power production at ARIANNA is expected to be 10% lower comparing with Princess Elisabeth.
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| 3. |
- Hallgren, Christoffer, et al.
(författare)
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Brief communication : On the definition of the low-level jet
- 2023
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Ingår i: Wind Energy Science. - : Copernicus Publications. - 2366-7443 .- 2366-7451. ; 8:11, s. 1651-1658
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Tidskriftsartikel (refereegranskat)abstract
- Low-level jets (LLJs) are examples of non-logarithmic wind speed profiles affecting wind turbine power production, wake recovery, and structural/aerodynamic loading. However, there is no consensus regarding which definition should be applied for jet identification. In this study we argue that a shear definition is more relevant to wind energy than a falloff definition. The shear definition is demonstrated and validated through the development of a European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation reanalysis (ERA5) LLJ climatology for six sites. Identification of LLJs and their morphology, frequency, and intensity is critically dependent on the (i) vertical window of data from which LLJs are extracted and (ii) the definition employed.
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| 4. |
- Hallgren, Christoffer, 1989-
(författare)
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Characterization and forecasting of wind conditions over the Baltic Sea
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- To meet the increasing demand of sustainably produced electricity, the total number of installed wind turbines is rapidly increasing globally. Although onshore installations are dominating, offshore wind power is taking a greater share of the market every year. Offshore, the wind is generally stronger than onshore and with the possibility to construct bigger turbines the electricity yield is also greater per turbine. Furthermore, it is possible to build larger wind farms offshore than onshore. The Baltic Sea is an area of high interest to many stakeholders and a major expansion of offshore wind power is expected in the region in the coming decades.As the Baltic Sea is a semi-enclosed sea with relatively short distances to the coast from anywhere in the basin, there are many mesoscale meteorological phenomena occurring, affecting the shape of the wind profile and the preconditions for wind power. This thesis focuses on these wind profiles, utilizing multi-year lidar observations and state-of-the-art numerical models. Wind profiles with a local maximum, i.e., low-level jets, are of special interest as they are frequently occurring over the Baltic Sea. These non-ideal wind speed profiles are characterized in terms of frequency and effects on turbulent properties, and the best way to define the low-level jets is investigated. Furthermore, the change in wind direction with height is addressed and a new index to automatically identify sea and land breeze circulations in operational weather prediction models is created. Finally, different post-processing methods to improve short-term forecasts of wind power production are compared and a recommendation on how to combine the methods depending on the weather situation is presented. Altogether, the research in this thesis adds a piece to the puzzle in reaching further understanding of the Baltic Sea wind conditions. The findings will be useful also in other coastal areas in siting, farm layout, and load analysis as well as in creating improved power production forecasts for offshore wind turbines.
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| 5. |
- Hallgren, Christoffer, et al.
(författare)
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Classification and properties of non-idealized coastal wind profiles - an observational study
- 2022
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Ingår i: Wind Energy Science. - : Copernicus Publications. - 2366-7443 .- 2366-7451. ; 7:3, s. 1183-1207
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Tidskriftsartikel (refereegranskat)abstract
- Non-idealized wind profiles frequently occur over the Baltic Sea and are important to take into consideration for offshore wind power, as they affect not only the power production but also the loads on the structure and the behavior of the wake behind the turbine. In this observational study, we classified non-idealized profiles as the following wind profiles having negative shear in at least one part of the lidar wind profile between 28 and 300 m: low-level jets (with a local wind maximum in the profile), profiles with a local minimum and negative profiles. Using observations spanning over 3 years, we show that these non-idealized profiles are common over the Baltic Sea in late spring and summer, with a peak of 40 % relative occurrence in May. Negative profiles (in the 28-300 m layer) mostly occurred during unstable conditions, in contrast to low-level jets that primarily occurred in stable stratification. There were indications that the strong shear zone of low-level jets could cause a relative suppression of the variance for large turbulent eddies compared to the peak of the velocity spectra, in the layer below the jet core. Swell conditions were found to be favorable for the occurrence of negative profiles and profiles with a local minimum, as the waves fed energy into the surface layer, resulting in an increase in the wind speed from below.
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| 6. |
- Hallgren, Christoffer, et al.
(författare)
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Looking for an Offshore Low-Level Jet Champion among Recent Reanalyses : A Tight Race over the Baltic Sea
- 2020
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Ingår i: Energies. - : MDPI. - 1996-1073. ; 13:14
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Tidskriftsartikel (refereegranskat)abstract
- With an increasing interest in offshore wind energy, focus has been directed towards large semi-enclosed basins such as the Baltic Sea as potential sites to set up wind turbines. The meteorology of this inland sea in particular is strongly affected by the surrounding land, creating mesoscale conditions that are important to take into consideration when planning for new wind farms. This paper presents a comparison between data from four state-of-the-art reanalyses (MERRA2, ERA5, UERRA, NEWA) and observations from LiDAR. The comparison is made for four sites in the Baltic Sea with wind profiles up to 300 m. The findings provide insight into the accuracy of reanalyses for wind resource assessment. In general, the reanalyses underestimate the average wind speed. The average shear is too low in NEWA, while ERA5 and UERRA predominantly overestimate the shear. MERRA2 suffers from insufficient vertical resolution, which limits its usefulness in evaluating the wind profile. It is also shown that low-level jets, a very frequent mesoscale phenomenon in the Baltic Sea during late spring, can appear in a wide range of wind speeds. The observed frequency of low-level jets is best captured by UERRA. In terms of general wind characteristics, ERA5, UERRA, and NEWA are similar, and the best choice depends on the application.
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| 7. |
- Hallgren, Christoffer, et al.
(författare)
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Machine learning methods to improve spatial predictions of coastal wind speed profiles and low-level jets using single-level ERA5 data
- 2024
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Ingår i: Wind Energy Science. - : Copernicus Publications. - 2366-7443 .- 2366-7451. ; 9:4, s. 821-840
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Tidskriftsartikel (refereegranskat)abstract
- Observations of the wind speed at heights relevant for wind power are sparse, especially offshore, but with emerging aid from advanced statistical methods, it may be possible to derive information regarding wind profiles using surface observations. In this study, two machine learning (ML) methods are developed for predictions of (1) coastal wind speed profiles and (2) low-level jets (LLJs) at three locations of high relevance to offshore wind energy deployment: the US Northeastern Atlantic Coastal Zone, the North Sea, and the Baltic Sea. The ML models are trained on multiple years of lidar profiles and utilize single-level ERA5 variables as input. The models output spatial predictions of coastal wind speed profiles and LLJ occurrence. A suite of nine ERA5 variables are considered for use in the study due to their physics-based relevance in coastal wind speed profile genesis and the possibility to observe these variables in real-time via measurements. The wind speed at 10 ma.s.l. and the surface sensible heat flux are shown to have the highest importance for both wind speed profile and LLJ predictions. Wind speed profile predictions output by the ML models exhibit similar root mean squared error (RMSE) with respect to observations as is found for ERA5 output. At typical hub heights, the ML models show lower RMSE than ERA5 indicating approximately 5 % RMSE reduction. LLJ identification scores are evaluated using the symmetric extremal dependence index (SEDI). LLJ predictions from the ML models outperform predictions from ERA5, demonstrating markedly higher SEDIs. However, optimization utilizing the SEDI results in a higher number of false alarms when compared to ERA5.
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| 8. |
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| 9. |
- Hallgren, Christoffer, et al.
(författare)
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The smoother the better? : A comparison of six post-processing methods to improve short-term offshore wind power forecasts in the Baltic Sea
- 2021
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Ingår i: Wind Energy Science. - : Copernicus Publications. - 2366-7443 .- 2366-7451. ; 6:5, s. 1205-1226
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Tidskriftsartikel (refereegranskat)abstract
- With a rapidly increasing capacity of electricity generation from wind power, the demand for accurate power production forecasts is growing. To date, most wind power installations have been onshore and thus most studies on production forecasts have focused on onshore conditions. However, as offshore wind power is becoming increasingly popular it is also important to assess forecast quality in offshore locations. In this study, forecasts from the high-resolution numerical weather prediction model AROME was used to analyze power production forecast performance for an offshore site in the Baltic Sea. To improve the AROME forecasts, six post-processing methods were investigated and their individual performance analyzed in general as well as for different wind speed ranges, boundary layer stratifications, synoptic situations and in low-level jet conditions. In general, AROME performed well in forecasting the power production, but applying smoothing or using a random forest algorithm increased forecast skill. Smoothing the forecast improved the performance at all wind speeds, all stratifications and for all synoptic weather classes, and the random forest method increased the forecast skill during low-level jets. To achieve the best performance, we recommend selecting which method to use based on the forecasted weather conditions. Combining forecasts from neighboring grid points, combining the recent forecast with the forecast from yesterday or applying linear regression to correct the forecast based on earlier performance were not fruitful methods to increase the overall forecast quality.
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| 10. |
- Hallgren, Christoffer, et al.
(författare)
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The winds are twisting: analysis of strong directional shear across the rotor plane using coastal lidar measurements and ERA5
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The change of wind direction with height (the directional shear) affects both the power production from a wind turbine, wake effects and aerodynamic loading. In this study, a climatology of the relative occurrence of strong directional shear over Scandinavia is created using 43 years of hourly ERA5 data covering the height range of a modern wind turbine and at wind speeds of operation. It is shown that strong directional shear (≥15° over the rotor) is occurring 20-30% of the time over land and 10-25% of the time over the extended Baltic Sea. The height of the atmospheric boundary-layer and the wind speed at hub height are identified as the most important predictors for strong directional shear, with low boundary-layer heights and weak winds being the main causes. Associated with this, a strong land-sea seasonality is observed. Further, ERA5 is validated against lidar soundings from two coastal sites, both indicating a major underestimation in the distribution of the directional shear in ERA5. Especially in strongly stratified boundary-layers ERA5 struggles, with 25% of the data having errors exceeding 24° and 28° for Östergarnsholm and Utö respectively.
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