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At least 19 records

IEA Wind TCP Task 26: Wind Technology, Cost, and Performance Trends for Denmark, Germany, Ireland, Japan, Norway, Sweden, the European Union, and the United States 2016-2019

The Cost of Wind Energy represents an international collaboration dedicated to exploring the historical and future cost of wind energy in addition to the investigating the market value wind energy may provide. The countries that are currently represented by participating organizations in IEA Wind TCP Task 26 included in this report are Denmark, Germany, Ireland, Japan, Norway, Sweden, the European Union, and the United States. This manuscript documents technology and cost trends from 2008 through 2019 and discusses the trends from 2016 through 2019 that affected the cost of land-based wind energy within each country. The cost of wind energy during this period is compared with the market value of wind energy in the respective electricity market for each country.

17 WIND ENERGY↗

Hybrid Solar Thermal Energy System for District Heating Application

Solar district heating (SDH) systems can be good alternatives to conventional systems when they are optimized with hybrid configurations and thermal energy storage (TES). In this scope, a hybrid renewable thermal energy system (RTES) model has been built combining flat plate collector (FPC) solar system with parabolic trough collector (PTC) system via a heat exchanger and coupled with TES. To undertake the hybridization of the system, System Advisor Model (SAM) software was modified, which allowed control over configurations and more accurate modelling of heat transfer between the collectors. The model is first compared to an existing hybrid solar district heating systems (DHS) system in Taars, Denmark. The results showed a good correlation with an overestimation of only 6.4% compared to most recent heat output. Then the same system configuration was modeled in different geographic locations to investigate the impact of changes in direct normal irradiance (DNI) to the heat sink thermal output of the hybrid system. The results showed that the annual net thermal power output in California, USA can be three times more than the annual net thermal power output in Taars, Denmark. Finally, multiple hybrid configurations with varying solar field sizes were simulated based on the heat demand of two different university campuses DHS. The results showed that, retrofit applications of this hybrid DHS system coupled with TES could reduce the natural gas consumption of the existing systems between 25% and 41%. The use of hybrid RTES highlighted in this paper can be extended to many more opportunities.

district heating↗

Added value of site load measurements in probabilistic lifetime extension: a Lillgrund case study

Site-specific fatigue estimation is an essential part of wind turbine lifetime extension, with various methods depending on data availability. The present study compares probabilistic lifetime extension assessment results for rotor blades with and without load measurements. It also addresses two key questions in such assessments: the applicability of the Frandsen model for estimating waked turbulence under complex and mixed wake conditions and the extrapolation of mid-term data over longer time periods. The case study wind turbine is SWT-2.3-93, located at the edge of the Lillgrund wind farm, situated in the Øresund Strait between Denmark and Sweden. The turbine is extensively instrumented, with 5 years of data available from its supervisory control and data acquisition (SCADA) system. Although the Frandsen turbulence estimates deviate in a different manner from measurements at below- and above-rated mean wind speeds, the model remains a conservative approach for fatigue load prediction and reliability. In the current case study, the site-specific assessment using strain gauge measurements yields a 33 % higher annual fatigue reliability index after 35 years compared to a scenario based on the Frandsen estimation combined with ambient environmental data and a generic aeroelastic model. The results also demonstrate that the sensitivity of fatigue reliability to load uncertainty is negligible when load measurements are used directly but relatively high when relying on the Frandsen model in combination with a generic aeroelastic model. Overall, the high variability of the lifetime extension in different scenarios of data availability and accuracy shows the importance and added value of high-quality measurements combined with wind-farm-level SCADA and a model updated in real time (digital twins).

17 WIND ENERGY↗

Mechanisms of heat flux across the Southern Greenland continental shelf in 1/10° and 1/12° ocean/sea ice simulations

The increased presence of warm Atlantic water on the Greenland continental shelf has been connected to the accelerated melting of the Greenland Ice Sheet, particularly in the southwest and southeast shelf regions. Results from two high-resolution coupled ocean-sea ice simulations that utilized either the 1/10-degree Parallel Ocean Program (POP) or the 1/12-degree HYbrid Coordinate Ocean Model (HYCOM) are used to understand the flux of heat on and off the southern Greenland shelf. The analysis reveals that the region of greatest heat flux onto the shelf is southeast Greenland. On the southwestern shelf, heat is mainly exported from the shelf to the interior basins. We identify differences in the shelf break current structure and on-shelf heat content between the two simulations. Just south of the Denmark strait, there is a seasonally persistent pattern of multi-day variability in the cross-shelf heat flux in both simulations. In the POP simulation, this high-frequency signal results in net on-shore heat flux. In the HYCOM simulation, the signal is weaker and results in net off-shelf heat flux. This variability is consistent with Denmark Strait Overflow eddies traveling along the shelf break.

58 GEOSCIENCES↗

WhiteWind: White Etching Crack (WEC) Bearing Failures in Wind Turbine: Cooperative Research and Development, CRADA Number CRD-18-00758 (Final Report)

A WEC is a particularly aggressive, unpredictable and wide spread rolling element bearing failure mode that is common for large multi-megawatt (MW) wind turbines. WEC is considered the single most expensive failure mode for all wind turbine components, and there is currently no commercial solution. The Technical University of Denmark (DTU) is leading the WhiteWind project to investigate WECs through funding provided by the Innovation Fund Denmark. Other project partners include Vestas, SKF, Expanite, Rheinisch-Westfalische Technische Hochschule Aachen University (RWTH Aachen), and Argonne National Laboratory. The objective of the overall project is to develop a new surface engineered WEC-resistant bearing material using novel surface engineering techniques that shall provide a commercially competitive alternative to existing wind turbine bearings. NREL will support the project by providing existing measured bearing loads and validating models of drivetrain loads.

17 WIND ENERGY↗

PV Performance Modeling - Data and Resources

The Photovoltaic (PV) Performance Modeling Collaborative (PVPMC) organized a blind PV performance modeling intercomparison to allow PV modelers to blindly test their models and modeling ability against real system data. Measured weather and irradiance data were provided along with detailed descriptions of PV systems from two locations (Albuquerque, New Mexico, USA and Roskilde, Denmark). Participants were asked to simulate the plane-of-array irradiance, module temperature, and DC power output from six systems and submit their results to Sandia for processing. This dataset includes seven MS-Excel sheets with instructions, notes and all necessary data (weather, irradiance, temperature, power) used for the data analysis of the blind modeling comparison. The hourly data represent six different systems from Albuquerque, NM and Roskilde, Denmark over a period of one year. These data are useful for PV performance model validation studies.

14 SOLAR ENERGY↗

Benchmarking of three DWM-based wake models at below-rated wind speeds

Wind turbine wake models are essential tools for predicting power losses and structural loads in wind farms. Among these, the dynamic wake meandering (DWM) model, included as a recommended approach in the International Electrotechnical Commission design standard, is a widely used engineering-fidelity method that balances accuracy and computational cost. This study compares the performance of three DWM-based wake model implementations (from the Technical University of Denmark, the National Renewable Energy Laboratory, and the Institute for Energy Technology) under below-rated wind speed conditions. Model predictions of wake flow, power output, and structural loads for a four-turbine row are evaluated across different ambient turbulence levels and wind-direction misalignments and compared against high-fidelity large-eddy simulation results. All three models captured the overall wake evolution and mean turbine performance with reasonable accuracy; their predicted time-averaged thrust and power were typically within 5 %–10 % of the large-eddy simulation benchmark. However, notable differences emerged in wake structure and unsteady load predictions, with discrepancies increasing for turbines further downstream. These differences highlight the importance of modelling choices such as wake summation and turbulence treatment, which strongly influence power-deficit and fatigue-load predictions. Comparison with large-eddy simulations reveals each approach's strengths and weaknesses, indicating where improvements are needed. Overall, the findings point to specific refinements for DWM models to improve their fidelity, ultimately enabling more robust wake predictions for wind farm design and operation.

17 WIND ENERGY↗

Multifaceted drivers for onshore wind energy repowering and their implications for energy transition

Wind energy is anticipated to become a backbone of the future energy system. Ageing wind turbine fleets, increasing land-use constraints and rising relevance of societal factors make the deployment of land-based (onshore) wind energy ever more complicated. Consequently, repowering is expected to become a rapidly growing point of focus for the wind industry. Here we propose a more holistic and socially informed project-level approach to analyse repowering activity that enables a more robust understanding of the process and potentials. We demonstrate that for wind pioneer in Denmark, only 67% of the capacity removed in repowering projects was related to the physical space needed for a new turbine. Other factors that drive repowering include regulation (for example, noise-related, 8–17%), development principles (for example, aesthetics, 7–20%) and political bargaining (4–13%). The recognition of repowering as a negotiated process between host communities and wind developers will probably be critical to unlock the full potential of wind energy in the future.

17 WIND ENERGY↗

Blind photovoltaic modeling intercomparison: A multidimensional data analysis and lessons learned

The Photovoltaic (PV) Performance Modeling Collaborative (PVPMC) organized a blind PV performance modeling intercomparison to allow PV modelers to blindly test their models and modeling ability against real system data. Measured weather and irradiance data were provided along with detailed descriptions of PV systems from two locations (Albuquerque, New Mexico, USA, and Roskilde, Denmark). Participants were asked to simulate the plane-of-array irradiance, module temperature, and DC power output from six systems and submit their results to Sandia for processing. The results showed overall median mean bias (i.e., the average error per participant) of 0.6% in annual irradiation and –3.3% in annual energy yield. While most PV performance modeling results seem to exhibit higher precision and accuracy as compared to an earlier blind PV modeling study in 2010, human errors, modeling skills, and derates were found to still cause significant errors in the estimates.

14 SOLAR ENERGY↗

Influence of building heat distribution temperatures on the energy performance and sizing of 5th generation district heating and cooling networks

This paper investigates the energy performance and sizing criteria of 5th generation district heating and cooling (5GDHC) networks as a function of the heat distribution temperature in the building systems connected to the district network. An energy simulation model of a 5GDHC network was developed in Modelica for a case study located in Denmark. Calculations were carried out for four different building heating systems. Simulation results show that reducing the heat distribution temperatures from 70 °C to 23 °C leads to around 40% annual electric energy savings (from 10.4 kWh/m 2 to 6.2 kWh/m 2 ) for the operation of the heat pumps. Heat distribution temperatures of 23 °C cause higher water mass flow rates through the network, leading to annual electric energy consumption for the circulation pumps that are almost doubled (from 0.16 kWh/m 2 to 0.3 kWh/m 2 ) compared to the reference case at 70 °C. Furthermore, the paper discusses how the results obtained from the Danish case study can be generalized and applied to other cases using a simplified mathematical approach. In conclusion, it is found that about 1.5% of electric energy savings can be achieved for each temperature degree reduction in the heat distribution system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Automatic voltage regulation application for PV inverters in low-voltage distribution grids – A digital twin approach

This paper proposes a hierarchical coordinated control strategy for PV inverters to keep voltages in low-voltage (LV) distribution grids within specified limits. The top layer of the proposed architecture consists of the designed automatic voltage regulation (AVR) application, which has access to voltage measurements and grid parameters from the LV distribution grid, both current and historical. The AVR application solves a constrained optimization problem, which provides a set of local control set-points that bring the voltage across the grid within bounds. The middle layer consists of a local Volt/VAR controller, which is adjusted by the AVR app, while the bottom layer is the inner-loop controller of the PV inverter. The proposed method not only improves the voltage quality in the grid but also manages the reactive power outputs of PV inverters efficiently. Further, a digital twin of the cyber-physical system has also been employed that interacts with the control system to ensure its appropriate operation. The effectiveness of the proposed methodology is demonstrated on a representative low-voltage feeder located in Denmark.

24 POWER TRANSMISSION AND DISTRIBUTION↗

From lab to table: Expanding gastronomic possibilities with fermentation using the edible fungus Neurospora intermedia

Fermentation is a powerful tool for enhancing flavor, improving sustainability, and expanding creative possibilities in the kitchen. However, most fermentations done in gastronomic contexts are restricted to a small set of readily available microbial species. Expanding beyond this limited biological diversity holds promise to unlock new gastronomic innovation. Here, we explore novel culinary applications of Neurospora intermedia, an edible fungus traditionally used in Java, Indonesia to produce the fermented food oncom. Our work demonstrates that N. intermedia can be readily used in the production of oncom-like meat alternatives with non-traditional substrates, as well as in the production of enzymes for starch-to-sugar conversion. As an example, we harness secreted N. intermedia starch-degrading enzymes to produce an amazake that has a distinct volatile aroma composition compared to traditional amazake produced with Aspergillus oryzae. In addition to providing texture and flavor, N. intermedia can be used to add an orange color to dishes due to the development of brightly colored spores and aerial mycelia. This property, along with its secreted enzymes, was utilized to create a dish for fine-dining restaurant Alchemist in Copenhagen, Denmark. Overall, the novel foods produced in this study were rated favorably in consumer trials, indicating a broad sensory appeal of N. intermedia across different culinary applications and cultural contexts. The protocols and approaches presented in this study represent a new addition to the chef's toolbox that hold promise to expand gastronomic possibilities with fermentation in restaurants and beyond.

59 BASIC BIOLOGICAL SCIENCES↗

Meeting report: The first soil viral workshop 2022

Soil viral ecology is a growing research field; however, the state of knowledge still lags behind that of aquatic systems. Therefore, to facilitate progress, the first Soil Viral Workshop was held to encourage international scientific discussion and collaboration, suggest guidelines for future research, and establish soil viral research as a concrete research area. The workshop took place at Søminestationen, Denmark, between 15 and 17th of June 2022. The meeting was primarily held in person, but the sessions were also streamed online. The workshop was attended by 23 researchers from ten different countries and from a wide range of subfields and career stages. Eleven talks were presented, followed by discussions revolving around three major topics: viral genomics, virus-host interactions, and viruses in the soil food web. The main take-home messages and suggestions from the discussions are summarized in this report.

09 BIOMASS FUELS↗

Deep Learning-Enabled MS/MS Spectrum Prediction Facilitates Automated Identification Of Novel Psychoactive Substances

The market for illicit drugs has been reshaped by the emergence of more than 1100 new psychoactive substances (NPS) over the past decade, posing a major challenge to the forensic and toxicological laboratories tasked with detecting and identifying them. Tandem mass spectrometry (MS/MS) is the primary method used to screen for NPS within seized materials or biological samples. The most contemporary workflows necessitate labor-intensive and expensive MS/MS reference standards, which may not be available for recently emerged NPS on the illicit market. Here, we present NPS-MS, a deep learning method capable of accurately predicting the MS/MS spectra of known and hypothesized NPS from their chemical structures alone. NPS-MS is trained by transfer learning from a generic MS/MS prediction model on a large data set of MS/MS spectra. We show that this approach enables a more accurate identification of NPS from experimentally acquired MS/MS spectra than any existing method. We demonstrate the application of NPS-MS to identify a novel derivative of phencyclidine (PCP) within an unknown powder seized in Denmark without the use of any reference standards. We anticipate that NPS-MS will allow forensic laboratories to identify more rapidly both known and newly emerging NPS. NPS-MS is available as a web server at https://nps-ms.ca/, which provides MS/MS spectra prediction capabilities for given NPS compounds. Additionally, it offers MS/MS spectra identification against a vast database comprising approximately 8.7 million predicted NPS compounds from DarkNPS and 24.5 million predicted ESI-QToF-MS/MS spectra for these compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Future Projections of EURO‐CORDEX Raw and Bias‐Corrected Daily Maximum Wind Speeds Over Scandinavia

Twenty historical and future Coordinated Regional Climate Downscaling Experiment ensemble for Europe simulations are bias corrected to investigate the future changes in the daily maximum wind speed over Scandinavia. We use quantile mapping to adjust the wind for the historical period (1985–2014) and quantile delta mapping for two future periods (2041–2070, 2071–2100, RCP8.5) with the 3-km spatial resolution NORA3 hindcast as the reference data set. Decomposing the variance, we find that most of the inter-model spread in the bias and the response to climate change is due to the regional climate model over land and mainly to the general climate model over sea. On average, the mean daily maximum wind speed is projected to increase everywhere except along the western coast of Norway and Denmark. In summer, we see an opposite sign over Sweden and Finland. The Norwegian Sea experiences weaker mean and high wind whereas the Baltic Sea experiences a strengthening. Bias correction influences the amplitude of the response, not the response pattern. Wind speed distributions can have different shapes in the future, with, for example, a flattening of the distribution off the coast of Norway with more frequent weak and very strong winds. Apart from a few locations in Norway, we find an increase in the number of days in the local highest historical wind category. Overall, summer exhibits opposite signals compared to the three other seasons. At country scale, the sign of the change in the mean and 98th percentile varies greatly depending on the region and among the simulations, especially for Norway.

54 ENVIRONMENTAL SCIENCES↗

Arctic extreme precipitation changes from 1980 to 2022 in response to sea ice decline and enhanced atmospheric rivers

Arctic extreme precipitation (EP) broadly impacts permafrost degradation, glacier and snow cover changes, and ice sheet mass balance as well as ecosystems. However, investigation of EP spatiotemporal variations over the Arctic remains challenging, and their primary drivers are still poorly understood. Performance estimation of three state-of-the-art reanalysis products (Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA-5), and Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2)) against gauge-based precipitation observations reveals that MERRA-2 outperforms other reanalysis for Arctic EP changes. Based on MERRA-2 data, both annual EP amount and occurrence days averaged over the Arctic show statistically significant positive trends during 1980–2022 (3.37 ± 1.03 mm dec −1 and 0.42 ± 0.17 d dec −1 , respectively), with the most pronounced increase in the autumn. Spatial heterogeneity in annual and seasonal EP trends is found across the Arctic, with the largest positive annual trends of 30 mm dec −1 over the Bering Sea and the Denmark Strait. The significant EP increase is closely associated with intensified atmospheric rivers (ARs) and widespread decline in sea ice concentration (SIC). Specially, SIC and ARs are responsible for 12% and 50% of Arctic EP inter-annual variance, respectively, while ARs directly contribute 28.3% of the total annual EP amounts. These findings explain the mechanistic controls on Arctic EP, providing critical insights for projecting polar weather and climate extremes and their impacts on the Arctic environment.

atmospheric rivers↗