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Dr. Christopher Jung
Environmental Meteorology, Albert-Ludwigs-University of Freiburg, Werthmannstrasse 10, D-79085 Freiburg, Germany

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Journal article
Published: 21 August 2021 in Renewable Energy
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The best wind locations are nowadays often occupied by old, less efficient and relatively small wind turbines. Many of them will soon reach the end of their operating lifetime, or lose financial support. Therefore, repowering comes to the fore. However, social acceptance and land use restrictions have been under constant change since the initial expansions, which makes less area available for new turbines, even on existing sites. For the example of Germany, this study assesses the repowering potential for onshore wind energy in high detail, on the basis of regionally differentiated land eligibility criteria. The results show that under the given regional criteria, repowering will decrease both operating capacity and annual energy yield by roughly 40% compared to the status quo. This is because around half of the wind turbines are currently located in restricted areas, given newly enacted exclusion criteria. Sensitivity analyses on the exclusion criteria show that the minimum distance to discontinuous urban fabric is the most sensitive criterion in determining the number of turbines that can be repowered. As regulations on this can vary substantially across different regions, the location-specific methodology chosen here can assess the repowering potential more realistically than existing approaches.

ACS Style

Jan Frederick Unnewehr; Eddy Jalbout; Christopher Jung; Dirk Schindler; Anke Weidlich. Getting more with less? Why repowering onshore wind farms does not always lead to more wind power generation – A German case study. Renewable Energy 2021, 180, 245 -257.

AMA Style

Jan Frederick Unnewehr, Eddy Jalbout, Christopher Jung, Dirk Schindler, Anke Weidlich. Getting more with less? Why repowering onshore wind farms does not always lead to more wind power generation – A German case study. Renewable Energy. 2021; 180 ():245-257.

Chicago/Turabian Style

Jan Frederick Unnewehr; Eddy Jalbout; Christopher Jung; Dirk Schindler; Anke Weidlich. 2021. "Getting more with less? Why repowering onshore wind farms does not always lead to more wind power generation – A German case study." Renewable Energy 180, no. : 245-257.

Journal article
Published: 04 August 2021 in Weather and Climate Extremes
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Destructive winter storms cause recurring major damage to physical, biological, human, and managed systems in Central Europe. Therefore, detailed knowledge of their future development in many areas of human life is of great importance for planning strategic management decisions. One feature to characterise the winter storm intensity is the daily maximum gust speed for a 10-yr return period (GS10yr). In this study, the development of GS10yr under the representative concentration pathways RCP45 and RCP85 in the near future (2019–2049), mid future (2044–2074), and far future (2069–2099) was assessed. Gust speed projections were derived from 19 regional climate models (RCM) available from the EURO-CORDEX initiative. The GS10yr estimates were first bias-corrected and then combined with the historical winter storm atlas for Germany (GeWiSA) yielding highly resolved (25 m × 25 m) GS10yr grids. The results which are available on a monthly basis, indicate a significant increase in winter storm-related wind gust intensity in October under RCP45 and in November and December under RCP85 towards the end of the 21st century. The proposed methodology allows the quantification of the uncertainty associated with winter storm projections and the development of climate-sensitive storm damage models.

ACS Style

Christopher Jung; Dirk Schindler. Does the winter storm-related wind gust intensity in Germany increase under warming climate? – A high-resolution assessment. Weather and Climate Extremes 2021, 33, 100360 .

AMA Style

Christopher Jung, Dirk Schindler. Does the winter storm-related wind gust intensity in Germany increase under warming climate? – A high-resolution assessment. Weather and Climate Extremes. 2021; 33 ():100360.

Chicago/Turabian Style

Christopher Jung; Dirk Schindler. 2021. "Does the winter storm-related wind gust intensity in Germany increase under warming climate? – A high-resolution assessment." Weather and Climate Extremes 33, no. : 100360.

Journal article
Published: 28 July 2021 in Journal of Cleaner Production
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To reduce the negative implications associated with the use of conventional energies on the environment and human health, intensified renewable energy expansion is inevitable. Wind energy is one of the most promising renewable energies since the theoretical technical wind energy potential is far enough to cover the global electricity consumption. However, various geographical barriers reduce the wind potential to contribute to a more sustainable power supply. The main goal of this study was to quantify the percentage reduction of the theoretical technical wind energy potential due to geographical barriers. The geographical barriers were derived from seven land use models and an elevation model and classified into the restriction categories: (1) inaccessible areas (natural), (2) inaccessible areas (artificial), (3) protected areas, (4) missing infrastructure, and (5) consideration criteria. The theoretical technical wind energy potential was estimated by wind speed distributions from the Global Wind Speed Model and assuming a dense global onshore network of wind turbines within 500 m distances. The results reveal that the most significant theoretical technical wind energy potential loss results from missing infrastructure and soft consideration criteria. The global percentage energy reduction is 96.1 %. In most developing countries, lacking infrastructure was identified as the restriction category resulting in the most notable theoretical technical wind energy potential reduction. This result emphasizes the need to improve the accessibility to wind resources in developing countries by improving the electricity grid. In industrialized countries, consideration criteria (e.g., forests, agricultural areas, proximity to urban areas) cause the greatest theoretical technical wind energy potential reduction. Thus, the extent to which the theoretical technical wind energy potential is exploitable greatly depends on regulations, public acceptance, and agreements on competitive land use. By identifying the most relevant geographical barriers, the results of this study contribute to the development of country-specific frameworks for wind energy expansion.

ACS Style

Christopher Jung; Dirk Schindler. Distance to power grids and consideration criteria reduce global wind energy potential the most. Journal of Cleaner Production 2021, 317, 128472 .

AMA Style

Christopher Jung, Dirk Schindler. Distance to power grids and consideration criteria reduce global wind energy potential the most. Journal of Cleaner Production. 2021; 317 ():128472.

Chicago/Turabian Style

Christopher Jung; Dirk Schindler. 2021. "Distance to power grids and consideration criteria reduce global wind energy potential the most." Journal of Cleaner Production 317, no. : 128472.

Journal article
Published: 06 June 2021 in Energy Conversion and Management
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An important metric for quantifying the greenhouse gas saving potential of wind turbine types is the greenhouse gas payback time. Previous studies revealed that wind speed and wind turbine size are negatively correlated with greenhouse gas payback times. However, so far, payback times were mostly estimated for wind turbine types with a hub height of less than 100 m and rated power below 2000 kW at coarse spatial resolution. It is unclear if the negative correlation with turbine size continues to hold at greater heights since, in general, the change in wind speed increase reduces with higher altitude. Thus, the hypothesis that the size of more giant wind turbine types is not negatively correlated with greenhouse gas payback times was tested. The main goal was to develop a high spatial-resolution atlas of European greenhouse gas payback times considering the small-scale wind resource variability for 33 generic wind turbine types. The greenhouse gas payback times were estimated by first calculating the average monthly energy yields for the wind turbine types with hub heights from 60 to160 m and rated power from 800 to 4200 kW at a 250 m × 250 m spatial resolution grid. Secondly, the wind turbine types’ anticipated greenhouse gas emissions were estimated based on their hub height and rotor diameter. The wind turbine type-related net greenhouse gas emissions were compared with the mean emissions of a natural gas-fired power plant (0.5 kg CO2,eq/kWh). It was found that wind turbine types with rated power and hub height of {2400 kW, 60 m} and {3600 kW, 80 m} have the shortest greenhouse gas payback times. The European median greenhouse gas payback time was estimated at 6.1 months including the wind turbine types with lowest payback times. In the hub height range of 60 to 160 m, the correlation between greenhouse gas payback times and hub height was found to be significantly positive.

ACS Style

Christopher Jung; Dirk Schindler. Modeling wind turbine-related greenhouse gas payback times in Europe at high spatial resolution. Energy Conversion and Management 2021, 243, 114334 .

AMA Style

Christopher Jung, Dirk Schindler. Modeling wind turbine-related greenhouse gas payback times in Europe at high spatial resolution. Energy Conversion and Management. 2021; 243 ():114334.

Chicago/Turabian Style

Christopher Jung; Dirk Schindler. 2021. "Modeling wind turbine-related greenhouse gas payback times in Europe at high spatial resolution." Energy Conversion and Management 243, no. : 114334.

Journal article
Published: 16 May 2021 in Energy
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The preconditions for wind farm installation and operation are high energy yields and accessibility. However, so far, no attempts were made to develop a global scale index integrating energy yields and accessibility of wind farms. Thus, the goal of this study was to create a universally applicable wind farm potential index that enables finding productive and accessible wind farm sites around the world. The wind farm potential index was developed at a very high horizontal resolution (2000 m × 2000 m) using the Global Wind Speed Model and comprehensive land use data. The wind farm capacity factor's global pattern was estimated based on Kappa and Wakeby distributions, and a generic 3.3 MW wind turbine power curve yielding the resource potential index. The geographical potential index integrates 16 geographical restrictions, including the accessibility to the power grid. The correlation coefficients between the resource potential index and geographical potential index were below 0.10 in many countries (61%). The areas with high resource potential and geographical potential were often divergent, e.g., in areas with poorly developed infrastructure. Applying the new wind farm potential index allows a global, consistent assessment of areas suitable for installing and operating wind farms.

ACS Style

Christopher Jung; Dirk Schindler. A global wind farm potential index to increase energy yields and accessibility. Energy 2021, 231, 120923 .

AMA Style

Christopher Jung, Dirk Schindler. A global wind farm potential index to increase energy yields and accessibility. Energy. 2021; 231 ():120923.

Chicago/Turabian Style

Christopher Jung; Dirk Schindler. 2021. "A global wind farm potential index to increase energy yields and accessibility." Energy 231, no. : 120923.

Journal article
Published: 08 April 2021 in Energy Conversion and Management
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Among the renewable energy sources, the highest share of European net electricity generation comes from wind power. However, the European onshore wind resource’s volatile nature is a significant challenge in ensuring a constant national electricity supply. Therefore, this study examined the potential of complementary use of national wind resources available in 33 European countries. The complementarity of the national wind resources was assessed for 1971–2010 by identifying the time scales explaining the largest part of the variance in the time series of daily wind energy yield. The results of a novel combination of wavelet analysis, graph models, and dynamic time warping indicate that the wind energy yield shows the most substantial variations at the annual, seasonal, and multi-day scales. Geographical proximity is a critical factor in the complementarity of national wind energy yields. At all evaluated time scales, the wind energy yield in most central and western European countries is strongly correlated, forming a large supranational network with low potential for complementary use of national wind resources. Although the seasonal component of daily wind energy yield is shifted between the European countries by up to several weeks, which would create potential for complementary use, domestic electricity consumption often exceeds the usable wind resources. Domestic electricity consumption was found to be a major barrier to the transboundary exchange of wind energy. Based on the results obtained for the European onshore wind resource’s spatiotemporal dynamics, it must be assumed that the potential for regular complementary transboundary use of wind resources is limited.

ACS Style

Dirk Schindler; Sophia Schmidt-Rohr; Christopher Jung. On the spatiotemporal complementarity of the European onshore wind resource. Energy Conversion and Management 2021, 237, 114098 .

AMA Style

Dirk Schindler, Sophia Schmidt-Rohr, Christopher Jung. On the spatiotemporal complementarity of the European onshore wind resource. Energy Conversion and Management. 2021; 237 ():114098.

Chicago/Turabian Style

Dirk Schindler; Sophia Schmidt-Rohr; Christopher Jung. 2021. "On the spatiotemporal complementarity of the European onshore wind resource." Energy Conversion and Management 237, no. : 114098.

Research article
Published: 19 January 2021 in International Journal of Energy Research
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The power law is most often applied to extrapolate the near‐surface wind speed to the wind turbine hub height. Due to variations of the meteorological conditions, the power law exponent varies over time. Usually, no long‐term wind speed measurements from multiple heights are available which would allow time‐dependent and spatially explicit power law exponent estimations. Instead, often the mean of the power law exponent or a constant value of 0.14 is assumed. The goal of this study was to quantify the error in wind potential assessments resulting from applying the mean of the power law exponent or a value of 0.14. The data base for this study are the hourly wind speed time series at 10 and 100 m above ground available for the period 2007 to 2018 from the ERA5 reanalysis project at a global 0.25° × 0.25° grid. The errors in the estimation of the wind power density and the capacity factor were calculated. It was found that, onshore, the global median of the absolute percentage error related to the wind power density using the mean of the power law exponent is 7.5%. Assuming a constant value of 0.14, the power law is less accurate (absolute percentage error: 37.1%). For the estimation of the capacity factor the absolute percentage errors are 5.5% and 36.9%. Based on the results of this study, the use of time‐dependent and spatially explicit power law exponents is suggested. In the absence of long‐term wind speed measurements from multiple heights, the results provide a comprehensive global overview of the errors to be expected from using the mean of the power law exponent or assuming a value of 0.14. In many regions where the wind resource is abundant, using the mean of the power law exponent only leads to minor errors in capacity factor estimation. There, the assessment of wind resources with small errors is possible, even in the absence of long‐term wind speed measurements at different heights.

ACS Style

Christopher Jung; Dirk Schindler. The role of the power law exponent in wind energy assessment: A global analysis. International Journal of Energy Research 2021, 45, 8484 -8496.

AMA Style

Christopher Jung, Dirk Schindler. The role of the power law exponent in wind energy assessment: A global analysis. International Journal of Energy Research. 2021; 45 (6):8484-8496.

Chicago/Turabian Style

Christopher Jung; Dirk Schindler. 2021. "The role of the power law exponent in wind energy assessment: A global analysis." International Journal of Energy Research 45, no. 6: 8484-8496.

Journal article
Published: 14 October 2020 in Sustainable Energy Technologies and Assessments
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The intermittent nature of wind energy is a major challenge transforming the energy sector from fossil fuels to renewables. Depending on the location, results from previous studies show that the availability of wind energy can strongly vary over a year. However, although global temporal wind speed fluctuations are complex on the monthly and seasonal scales, they have been rarely quantified so far. Thus, the goals of this study were to assess the annual cycle and intra-annual variability of wind power around the world. A comprehensive dataset of more than 7000 globally distributed near-surface wind speed time series was analyzed. After extrapolation to a typical wind turbine hub height of 120 m, the monthly and seasonal mean wind speed, wind power density, and intra-annual variability were calculated. The system of wind speed distributions, which consists of the Burr-Generalized Extreme Value, Kappa, and Wakeby distributions, was fitted to all wind speed time series and used to estimate wind turbine related capacity factors. The greatest global wind resource was found for spring (global mean capacity factor: 0.272). In summer, the global wind resource decreased by 20.7%. The results reveal the greatest intra-annual variability in regions affected by the Indian monsoon circulation.

ACS Style

Christopher Jung; Dirk Schindler. The annual cycle and intra-annual variability of the global wind power distribution estimated by the system of wind speed distributions. Sustainable Energy Technologies and Assessments 2020, 42, 100852 .

AMA Style

Christopher Jung, Dirk Schindler. The annual cycle and intra-annual variability of the global wind power distribution estimated by the system of wind speed distributions. Sustainable Energy Technologies and Assessments. 2020; 42 ():100852.

Chicago/Turabian Style

Christopher Jung; Dirk Schindler. 2020. "The annual cycle and intra-annual variability of the global wind power distribution estimated by the system of wind speed distributions." Sustainable Energy Technologies and Assessments 42, no. : 100852.

Journal article
Published: 16 September 2020 in Energy Conversion and Management
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An important aspect of planning the future expansion of wind energy is the consideration of changes in available wind resources due to climate change. In previous studies simulations of the future behavior of wind resources were derived from regional climate models at coarse spatial resolutions not suitable for wind energy potential assessment at the wind turbine scale. Thus, this study investigates the hypothesis that changes in future wind resources initiated by climate change will influence important aspects of small-scale wind resource assessment. A new approach is introduced that can be used to quantify the (1) spatial wind resource availability, (2) temporal wind resource availability, and (3) geographical complementarity under climate change at the wind turbine scale. The assessment of the future spatiotemporal variations in wind resources is based on an ensemble of near-surface (10 m) wind speed time series at a daily resolution for the period 1981–2099 from 35 different regional climate models. Using the highly resolved (horizontal resolution: 200 m × 200 m) Wind Speed-Wind Shear model, the near-surface wind speed time series were bias-corrected and extrapolated to a wind turbine hub height of 140 m at the sites of the current wind turbines in Germany. Bias correction was carried out by matching the quantile distributions from the regional climate models and the Wind Speed-Wind Shear model. Afterward, a power curve of a modern 3.45 MW wind turbine was applied to calculate daily capacity factors. The results indicate small long-term changes in the wind resource availability under the representative concentration pathways 4.5 and 8.5. It was found, that the influence of the interannual variability of the German wind resource exceeds the influence of climate change on the wind resource. The newly developed approach goes beyond previous wind resource assessments under climate change because it offers the opportunity for the spatially explicit investigation of different aspects of wind resource assessment which allows to develop more sophisticated wind energy expansion plans. Although the results are valid only for the study area, the proposed methodology is portable to any other region around the world.

ACS Style

Christopher Jung; Dirk Schindler. Introducing a new approach for wind energy potential assessment under climate change at the wind turbine scale. Energy Conversion and Management 2020, 225, 113425 .

AMA Style

Christopher Jung, Dirk Schindler. Introducing a new approach for wind energy potential assessment under climate change at the wind turbine scale. Energy Conversion and Management. 2020; 225 ():113425.

Chicago/Turabian Style

Christopher Jung; Dirk Schindler. 2020. "Introducing a new approach for wind energy potential assessment under climate change at the wind turbine scale." Energy Conversion and Management 225, no. : 113425.

Journal article
Published: 30 May 2020 in Energy Conversion and Management
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The anticipated greater penetration of the variable renewable energies wind and solar in the future energy mix could be facilitated by exploiting their complementarity, thereby improving the balance between energy supply and demand. Based on the hypothesis that a complementary use of wind and solar is possible, this investigation provides information about the spatiotemporal scales on which there is potential for the synergistic use of wind and solar in Germany. The results show that the wind-solar complementarity depends very much on the time scale under consideration. Regardless of the spatial scale, potential for complementarity is greatest on the seasonal scale, where the annual cycles of surface incoming solar radiation and surface wind speed show the strongest anti-correlation. On all other scales studied, including daily and inter-annual scales, the potential for wind-solar complementarity is significantly lower with wind and solar being usually very weakly anti-correlated or being uncorrelated. On these scales, there is hardly any compensation of times with low solar resource by the wind resource and vice versa. There is also hardly any solar-solar or wind-wind complementarity in different regions because their regional inter-regime dynamics are similar and do not show any significant differences. From the results, it is therefore concluded that there is little potential for the complementary use of wind and solar in Germany, except on the seasonal scale. Germany’s low complementarity potential reinforces the need to systematically advance other options for mitigating the individual volatilities of wind and solar such as energy storage systems and transboundary exchange of renewable power in a pan-European electricity grid. Although the results are limited to a single country, the proposed novel data-driven approach can be readily transferred to study wind-solar complementarity in other parts of the world. It enables for the first time the consistent small-scale assessment of wind-solar complementarity in large, transnational areas and has the potential for being established as an essential tool to improve electrical grid operability.

ACS Style

Dirk Schindler; Hein Dieter Behr; Christopher Jung. On the spatiotemporal variability and potential of complementarity of wind and solar resources. Energy Conversion and Management 2020, 218, 113016 .

AMA Style

Dirk Schindler, Hein Dieter Behr, Christopher Jung. On the spatiotemporal variability and potential of complementarity of wind and solar resources. Energy Conversion and Management. 2020; 218 ():113016.

Chicago/Turabian Style

Dirk Schindler; Hein Dieter Behr; Christopher Jung. 2020. "On the spatiotemporal variability and potential of complementarity of wind and solar resources." Energy Conversion and Management 218, no. : 113016.

Journal article
Published: 20 March 2020 in Energy Conversion and Management
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A new model for mapping the near-surface wind speed L-moments on a high spatial resolution scale (250 m × 250 m) is introduced (GloWiSMo). The target variables are the first five L-moments of 6146 globally distributed wind speed time series. ERA5 reanalysis wind speed available on a 0.25° × 0.25° grid was used as predictor representing the large-scale wind field. Eleven predictors derived from a land cover model and a digital elevation model were applied to integrate the influence of small-scale surface properties on the wind field. The model is based on a least-squares boosting approach which is a machine learning algorithm. The parameters of the Kappa and Wakeby distribution were estimated based on the modeled L-moments. By applying the power law, the near-surface wind speed distribution can be extrapolated to any hub height. Here, we selected a typical wind turbine hub height of 120 m to demonstrate the potential of GloWiSMo. It was found that the relevance of a predictor on the spatial variability of the wind resource changes with the size of the investigation area. While the roughness length is a decisive factor for the large-scale spatial variability of the wind resource, the relative elevation is an important factor for the small-scale spatial variability. Rigorous model evaluation was performed using a validation dataset containing 598 globally distributed wind speed time series. The coefficient of determination calculated for the first L-moment was found to be 0.83. Based on the evaluation results, we argue that the developed model enables accurate and spatially explicit wind resource estimates at a very high spatial resolution.

ACS Style

Christopher Jung; Dirk Schindler. Integration of small-scale surface properties in a new high resolution global wind speed model. Energy Conversion and Management 2020, 210, 112733 .

AMA Style

Christopher Jung, Dirk Schindler. Integration of small-scale surface properties in a new high resolution global wind speed model. Energy Conversion and Management. 2020; 210 ():112733.

Chicago/Turabian Style

Christopher Jung; Dirk Schindler. 2020. "Integration of small-scale surface properties in a new high resolution global wind speed model." Energy Conversion and Management 210, no. : 112733.

Journal article
Published: 23 November 2019 in Atmosphere
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A new approach for modeling daily precipitation (RR) at very high spatial resolution (25 m × 25 m) was introduced. It was used to develop the Precipitation Atlas for Germany (GePrA). GePrA is based on 2357 RR time series measured in the period 1981–2018. It provides monthly percentiles (p) of the large-scale RR patterns which were mapped by a thin plate spline interpolation (TPS). A least-squares boosting (LSBoost) approach and orographic predictor variables (PV) were applied to integrate the small-scale precipitation variability in GePrA. Then, a Weibull distribution (Wei) was fitted to RRp. It was found that the mean monthly sum of RR ( R R ¯ s u m ) is highest in July (84 mm) and lowest in April (49 mm). A great dependency of RR on the elevation (ε) was found and quantified. Model validation at 425 stations showed a mean coefficient of determination (R2) of 0.80 and a mean absolute error (MAE) of less than 10 mm in all months. The high spatial resolution, including the effects of the local orography, make GePrA a valuable tool for various applications. Since GePrA does not only describe R R ¯ s u m , but also the entire monthly precipitation distributions, the results of this study enable the seasonal differentiation between dry and wet period at small scales.

ACS Style

Christopher Jung; Dirk Schindler. Precipitation Atlas for Germany (GePrA). Atmosphere 2019, 10, 737 .

AMA Style

Christopher Jung, Dirk Schindler. Precipitation Atlas for Germany (GePrA). Atmosphere. 2019; 10 (12):737.

Chicago/Turabian Style

Christopher Jung; Dirk Schindler. 2019. "Precipitation Atlas for Germany (GePrA)." Atmosphere 10, no. 12: 737.

Journal article
Published: 01 October 2019 in Energy Conversion and Management
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ACS Style

Christopher Jung; Dirk Schindler. Changing wind speed distributions under future global climate. Energy Conversion and Management 2019, 198, 1 .

AMA Style

Christopher Jung, Dirk Schindler. Changing wind speed distributions under future global climate. Energy Conversion and Management. 2019; 198 ():1.

Chicago/Turabian Style

Christopher Jung; Dirk Schindler. 2019. "Changing wind speed distributions under future global climate." Energy Conversion and Management 198, no. : 1.

Review
Published: 01 October 2019 in Renewable and Sustainable Energy Reviews
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ACS Style

Christopher Jung; Dirk Schindler. Wind speed distribution selection – A review of recent development and progress. Renewable and Sustainable Energy Reviews 2019, 114, 1 .

AMA Style

Christopher Jung, Dirk Schindler. Wind speed distribution selection – A review of recent development and progress. Renewable and Sustainable Energy Reviews. 2019; 114 ():1.

Chicago/Turabian Style

Christopher Jung; Dirk Schindler. 2019. "Wind speed distribution selection – A review of recent development and progress." Renewable and Sustainable Energy Reviews 114, no. : 1.

Journal article
Published: 11 July 2019 in Atmosphere
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Long-term gust speed (GS) measurements were used to develop a winter storm atlas of the 98 most severe winter storms in Germany in the period 1981–2018 (GeWiSa). The 25 m × 25 m storm-related GS fields were reconstructed in a two-step procedure: Firstly, the median gust speed ( G S ˜ ) of all winter storms was modeled by a least-squares boosting (LSBoost) approach. Orographic features and surface roughness were used as predictor variables. Secondly, the quotient of GS related to each winter storm to G S ˜ , which was defined as storm field factor (STF), was calculated and mapped by a thin plate spline interpolation (TPS). It was found that the mean study area-wide GS associated with the 2007 storm Kyrill is highest (29.7 m/s). In Southern Germany, the 1999 storm Lothar, with STF being up to 2.2, was the most extreme winter storm in terms of STF and GS. The results demonstrate that the variability of STF has a considerable impact on the simulated GS fields. Event-related model validation yielded a coefficient of determination (R2) of 0.786 for the test dataset. The developed GS fields can be used as input to storm damage models representing storm hazard. With the knowledge of the storm hazard, factors describing the vulnerability of storm exposed objects and structures can be better estimated, resulting in improved risk management.

ACS Style

Christopher Jung; Dirk Schindler. Historical Winter Storm Atlas for Germany (GeWiSA). Atmosphere 2019, 10, 387 .

AMA Style

Christopher Jung, Dirk Schindler. Historical Winter Storm Atlas for Germany (GeWiSA). Atmosphere. 2019; 10 (7):387.

Chicago/Turabian Style

Christopher Jung; Dirk Schindler. 2019. "Historical Winter Storm Atlas for Germany (GeWiSA)." Atmosphere 10, no. 7: 387.

Journal article
Published: 30 March 2019 in Energy Conversion and Management
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In a large number of previous studies, the technical wind energy potential was estimated from national to global scale. Usually, it was assumed that the underlying meteorological potential remains constant over time. However, the wind resource greatly varies on different temporal scales including inter-annual and multi-decadal scales. In this study, the long-term variability of national and global technical wind energy potentials was assessed for the period 1971–2010 based on wind speed data from the coupled atmosphere/land-surface/ocean-wave model ERA-20C. Within this period, the annual national and global wind energy generation was reconstructed assuming an average number of 0.01–0.25 wind turbines per km2 sited on geographically non-restricted areas. The applied wind turbines have an average rated power of 3.67 MW and a hub height of 100 m. While no significant trend in technical wind energy potential was found in the majority of the countries studied, the Mann-Kendall and Cox-Stuart trend tests revealed significantly increasing trends in 37 countries and significantly decreasing trends in 10 countries. In addition, the results show that the inter-annual variability of the wind energy potential is influenced not only by the wind resource itself, but also by the rate of wind turbine expansion. From the presented results it is clear that the quantification of the long-term variability of the wind energy potential is an important prerequisite for controlling and adapting the expansion of wind energy on national and global scales to future electricity consumption.

ACS Style

Christopher Jung; Diana Taubert; Dirk Schindler. The temporal variability of global wind energy – Long-term trends and inter-annual variability. Energy Conversion and Management 2019, 188, 462 -472.

AMA Style

Christopher Jung, Diana Taubert, Dirk Schindler. The temporal variability of global wind energy – Long-term trends and inter-annual variability. Energy Conversion and Management. 2019; 188 ():462-472.

Chicago/Turabian Style

Christopher Jung; Diana Taubert; Dirk Schindler. 2019. "The temporal variability of global wind energy – Long-term trends and inter-annual variability." Energy Conversion and Management 188, no. : 462-472.

Journal article
Published: 11 January 2019 in Energy
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The statistical air density distribution was modeled on a high-spatial resolution scale (200 m × 200 m) and the error by using constant standard air density was estimated using Germany as study area. Daily mean air temperature and air pressure time series of 144 meteorological measuring stations operated in the period 1979-2014 were used to calculate air density in the very common hub height for newly installed wind turbines of 140 m. The parameters of the statistical air density distributions were mapped for the whole of Germany. By applying a 2.4 MW power curve and the wind speed-wind shear model, study area-wide annual energy yield was calculated assuming constant standard air density and using the modeled air density distributions. The results from the comparison of the energy yields demonstrate that the total area with energy yield > 7.0 GWh/yr is slightly smaller (0.7%) when air density is considered to be variable. Based on the results of this study, the influence of air density on the wind energy yield of low elevation coastal sites and high elevation mountain sites can now be quantified in the study area. This will contribute to a more efficient use of the wind resource.

ACS Style

Christopher Jung; Dirk Schindler. The role of air density in wind energy assessment – A case study from Germany. Energy 2019, 171, 385 -392.

AMA Style

Christopher Jung, Dirk Schindler. The role of air density in wind energy assessment – A case study from Germany. Energy. 2019; 171 ():385-392.

Chicago/Turabian Style

Christopher Jung; Dirk Schindler. 2019. "The role of air density in wind energy assessment – A case study from Germany." Energy 171, no. : 385-392.

Journal article
Published: 10 January 2019 in Agricultural and Forest Meteorology
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Empirical forest storm damage models can assist in identifying the key factors of the occurrence of storm damage in order to develop locally adapted measures to minimize damage in forests. Yet, there is a significant lack of knowledge in these models concerning the correlation between storm damage and high-impact near-surface airflow. To improve our understanding in this field, we built Random Forests (RF) and Generalized Linear Models (GLM) for evaluating the association between high resolution gust speed data and long-term, multi-event forest storm damage data from long-term permanent forest growth and yield plots. The tested gust speed data were derived from two different gust speed models: a numerical non-hydrostatic mesoscale model and a statistical model. In all RF and GLM models gust speed was a statistically significant predictor. The performance of the evaluated empirical models was very high (area under the receiver operating characteristic curve values AUC = 0.86–0.99). Depending on the type of model, the relative importance of gust speed was moderate to very high (up to 35%). However, starting from models using all significant predictors and excluding gust speed, the performance loss was almost negligible in all models. Furthermore, modeling long-term storm damage for each storm event individually performed better compared to modeling average long-term, event-unspecific storm damage. Our results demonstrate that empirical storm damage models using only gust speed as a predictor can reach moderate (GLM) to very high (RF) performance, even without any other information on terrain and forest attributes. However, if detailed terrain and forest data are available, empirical storm damage models may have such a high performance that adding gust speed data improves them very little. The correlation between gust speed and storm damage in the coupled modeling system is a fundamental first step in being able to evaluate potential changes of forest storm damage in a changing climate with potentially changing wind regimes. Additionally, further improvements could be achieved by improved representation of airflow in complex forest.

ACS Style

Axel T. Albrecht; Christopher Jung; Dirk Schindler. Improving empirical storm damage models by coupling with high-resolution gust speed data. Agricultural and Forest Meteorology 2019, 268, 23 -31.

AMA Style

Axel T. Albrecht, Christopher Jung, Dirk Schindler. Improving empirical storm damage models by coupling with high-resolution gust speed data. Agricultural and Forest Meteorology. 2019; 268 ():23-31.

Chicago/Turabian Style

Axel T. Albrecht; Christopher Jung; Dirk Schindler. 2019. "Improving empirical storm damage models by coupling with high-resolution gust speed data." Agricultural and Forest Meteorology 268, no. : 23-31.

Short communication
Published: 23 November 2018 in International Journal of Hydrogen Energy
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Wind-to-hydrogen (WH) is a promising option for reducing greenhouse gas emissions in the transport sector. Therefore, the reduction potential of fossil fuels by WH was estimated taking meteorological, geographical, and technical constraints into account. The wind resource estimation is based on the application of the high-resolution (200 m × 200 m) wind speed-wind shear model (WSWS). Together with the power curves of the six most frequently installed wind turbines in 2017, WSWS was used to assess Germany's technical wind energy potential. The WH and fossil fuel reduction potentials were calculated based on proton exchange membrane electrolysis. Results from the wind resource assessment demonstrate that in addition to the currently realized wind energy (89 TWh/yr in 2017), which is directly used for electricity generation, Germany's technical onshore potential for WH is 780 TWh/yr. This amount of renewable energy available for WH could replace 80.1% of the fossil fuels currently used in the transport sector.

ACS Style

Christopher Jung; Linda Nagel; Dirk Schindler; Leonie Grau. Fossil fuel reduction potential in Germany's transport sector by wind-to-hydrogen. International Journal of Hydrogen Energy 2018, 43, 23161 -23167.

AMA Style

Christopher Jung, Linda Nagel, Dirk Schindler, Leonie Grau. Fossil fuel reduction potential in Germany's transport sector by wind-to-hydrogen. International Journal of Hydrogen Energy. 2018; 43 (52):23161-23167.

Chicago/Turabian Style

Christopher Jung; Linda Nagel; Dirk Schindler; Leonie Grau. 2018. "Fossil fuel reduction potential in Germany's transport sector by wind-to-hydrogen." International Journal of Hydrogen Energy 43, no. 52: 23161-23167.

Journal article
Published: 01 October 2018 in Energy Conversion and Management
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The fitting of empirical wind speed distributions is an important component in wind turbine energy yield assessment. Its accuracy depends on both the adequacy of the fitting function and the quality of the fitted wind speed data. Therefore, the system of wind speed distributions was recently introduced to further improve the statistical estimation of wind turbine energy yield. The system of wind speed distributions incorporates the three complement distributions Kappa, Wakeby and Burr-Generalized Extreme Value. In contrast to the progress that has been made in the statistical description of wind speed distributions, there is little research on the effects of poor quality data on the estimation of wind turbine energy yield. Therefore, the goal of this study was to evaluate the robustness of the system of wind speed distributions against typical wind speed data shortcomings such as (1) measurement errors, (2) missing data, and (3) low temporal resolution. The database were quality-controlled wind speed time series from 187 measurement stations of the German Meteorological Service located in Germany with a 10-minute temporal resolution. The investigated time series cover the period from July 2016 to December 2017. The original wind speed time series were modified by (1) rounding them to 0.5 m/s and 1 m/s steps, (2) reducing data availability to 1.0% and 0.5%, (3) reducing the temporal resolution. Afterwards, the original and the modified wind speed time series were fitted to the system of wind speed distributions. Ten goodness-of-fit metrics were applied for comparison of the original wind speed distributions with the modified distributions fitted to the system of wind speed distributions. Overall, it was found that the system of wind speed distributions is robust against common quality issues in the wind speed time series. Applying a 2.5 MW wind turbine power curve and fitting the system of wind speed distributions to integer wind speed data, the mean percentage annual energy yield error was estimated at 3.3%. Fitting the system of wind speed distributions to wind speed data with very low data availability of 0.5% of the original data, the annual energy yield over all stations was underestimated at −8.2%. The results of this investigation will help adequately addressing the biases caused by poor quality wind speed data, and thus, help to improve wind turbine energy yield assessment.

ACS Style

Christopher Jung; Dirk Schindler. Sensitivity analysis of the system of wind speed distributions. Energy Conversion and Management 2018, 177, 376 -384.

AMA Style

Christopher Jung, Dirk Schindler. Sensitivity analysis of the system of wind speed distributions. Energy Conversion and Management. 2018; 177 ():376-384.

Chicago/Turabian Style

Christopher Jung; Dirk Schindler. 2018. "Sensitivity analysis of the system of wind speed distributions." Energy Conversion and Management 177, no. : 376-384.