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Suche nach „[F.] [Nitsch]“ hat 10 Publikationen gefunden
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    Beitrag (Sammelband oder Tagungsband)

    Luis Ramirez Camargo, Wolfgang Dorner, K. Gruber, F. Nitsch

    Hybrid renewable energy systems to supply electricity to self-sufficient residential buildings in Central Europe

    Energy Procedia (Contributions to the 10th International Conference on Applied Energy ICAE 2018), vol. 158

    2019

    DOI: 10.1016/j.egypro.2019.01.096

    Abstract anzeigen

    This work evaluates potentials of photovoltaic and battery systems with additional micro-generation wind turbines (10.5 kW) to cover electricity demand of residential users in two countries in Central Europe. It relies on high-resolution regional reanalysis data and a techno-economical optimization model. Maps showing the number of wind turbines, photovoltaic and battery systems sizes necessary to supply electricity for clusters of electricity self-sufficient single-family houses across Germany and the Czech Republic are generated. No general trends that apply for the two countries concerning the relation between the sizes of the different technologies were identified. However, it was possible to determine several large areas where the inclusion of small wind turbines decreases the total system costs and considerably reduces the required storage capacities. Results are discussed and compared to previous work on self-sufficient single-family houses.

    NachhaltigElektrotechnik und MedientechnikTC Freyung

    Beitrag (Sammelband oder Tagungsband)

    Luis Ramirez Camargo, Wolfgang Dorner, K. Gruber, F. Nitsch

    Assessing regional reanalysis data sets for planning small-scale renewable energy system

    20th EGU General Assembly, EGU2018, Proceedings from the conference held 4-13 April, 2018 in Vienna, Austria, p.4996

    2018

    Abstract anzeigen

    An accurate resource availability estimation is vital for proper location, sizing and economic viability of renewable energy plants. Large photovoltaic (PV) and wind installations undergo a long and exhaustive planning process that would imply unacceptably high costs for developers of small-scale installations. In a context of abolition of feed-in tariffs, electricity feed-in restricted by grid capacity constraints and storage systems being commercialized at lower costs, the acquisition of high quality solar radiation and wind speed data becomes important also for planners of small scale installations. These data allow the characterization of short-term and inter-annual variability of the resources availability. Global reanalysis data sets provide long time series of these variables with temporal resolutions that can be as high as one hour and at no cost for the final user. However, due to the coarse spatial resolution and relatively low accuracy these products only provide an inferior alternative for data retrieval compared to e.g. satellite derived radiation data sets or advanced interpolation methods for wind speed data. The COSMO-REA6 and COSMOS-REA2 regional reanalysis overcome this limitation by increasing the resolution of the reanalysis to six and two kilometres respectively. The accuracy of these data sets for variables with high relevancy for meteorology, such as rainfall, has been assessed with satisfactory results but an independent evaluation for variables relevant for renewable energy generation has not been performed yet. This work presents an assessment of the variables of these data sets that have been made available to the public until November 2017. This assessment is performed for the area of the federal state of Bavaria in Germany and whole Czech Republic using data of the Bavarian agro-meteorological network and the Czech Hydrometeorological Institute. Accuracy indicators are calculated for horizontal global radiation or cloud coverage (depending on data availability from the weather stations) and wind speeds at 10 meters height. While there are important differences between weather stations and cloud coverage data, the results for wind speeds and global solar irradiance are satisfactory for most of the locations. For certain locations widely used indicators such as the Pearson's correlation coefficient reach values above 0.8 for wind speeds and above 0.9 for global solar irradiance and the mean biased error is consistently lower than 10 W/m2 and can be as low as 0.3 W/m2 for the irradiance data and is, with a few exceptions, lower than 2 m/s in Germany and lower than 1 m/s in the Czech Republic for wind speed data. A total of eight indicators for the hourly data in the period between 1995 and 2015 are calculated, presented, discussed and compared against international literature dealing with data accuracy for solar irradiance and wind speed data sets.

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    Zeitschriftenartikel

    Luis Ramirez Camargo, Wolfgang Dorner, K. Gruber, F. Nitsch

    Mapping minimum technical requirements for electricity self-sufficiency of single-family houses using regional reanalysis data and satellite imagery derived data

    Geophysical Research Abstracts, vol. 20, no. EGU2018-12577

    2018

    Abstract anzeigen

    Decreasing prices of photovoltaic (PV) and electricity storage systems have popularized the idea of independency from the grid among household's owners. The basic idea is simple: on the one side, PV installations can easily fit in building's roof-tops while producing more energy per year than a household would require; on the other side, the temporal mismatch between energy generated by the PV system and the electricity consumed by the household can be corrected with storage systems. In theory, this basic concept would require the examination of long time series of weather data and an optimization model in order to find a system configuration that actually fulfils the requirements of a household in a particular location. In practice, such detailed studies would be too expensive for small-scale installations and contractors take system sizing decisions based on empirical values or general sizing guidelines. Motivated by the project CrossEnergy, a research project that studies the future of the energy system in rural areas at the border between Germany and Czech Republic, and by the publication of the COSMO-REA high resolution regional reanalysis data sets for Europe in 2017, this study presents a methodology to generate maps indicating minimum battery and PV sizes for self-sufficient single family houses (SFHs). The methodology consist of three parts. First, settlement data extracted from the LUISA Territorial Modelling platform of the European Commission is used together with standard load profiles to generate spatiotemporal data sets of electricity demand for rural and low density urban areas. Second, spatiotemporal data sets of PV potential are generated based on a) a technical PV model, b) instantaneous solar irradiance and temperature data from the COSMO-REA regional reanalysis data, and c) snow cover data from the Land Surface Analysis Satellite Applications Facility. Third, a linear optimization model, relying on the data sets of the two previous parts, serves to define PV and battery systems sizes and to generate the corresponding maps. The resulting maps cover Germany and Czech Republic and are generated for multiple technical and weather dependent scenarios. The results show how complicated it could be to achieve a complete independence from the grid in certain locations and offer a scientifically based source of information for sizing PV-battery systems in the two countries. An outlook how to apply the methodology to the whole CORDEX Euro area and for future work is provided.

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    Zeitschriftenartikel

    Luis Ramirez Camargo, K. Gruber, F. Nitsch

    Assessing variables of regional reanalysis data sets relevant for modelling small-scale renewable energy systems

    Renewable Energy, vol. 133, pp. 1468-1478

    2018

    DOI: 10.1016/j.renene.2018.09.015

    Abstract anzeigen

    An accurate resource availability estimation is vital for proper location, sizing and economic viability of renewable energy plants. Large photovoltaic (PV) and wind installations undergo a long and exhaustive planning process that would imply unacceptably high costs for developers of small-scale installations. In a context of abolition of feed-in tariffs, electricity feed-in restricted by grid capacity constraints and storage systems being commercialized at lower costs, the acquisition of high quality solar radiation and wind speed data becomes important also for planners of small scale installations. These data allow the characterization of short-term and inter-annual variability of the resources availability. Global reanalysis data sets provide long time series of these variables with temporal resolutions that can be as high as one hour and at no cost for the final user. However, due to the coarse spatial resolution and relatively low accuracy these products only provide an inferior alternative for data retrieval compared to e.g. satellite derived radiation data sets or advanced interpolation methods for wind speed data. The COSMO-REA6 and COSMOS-REA2 regional reanalysis overcome this limitation by increasing the resolution of the reanalysis to six and two kilometres respectively. The accuracy of these data sets for variables with high relevancy for meteorology, such as rainfall, has been assessed with satisfactory results but an independent evaluation for variables relevant for renewable energy generation has not been performed yet. This work presents an assessment of the variables of these data sets that have been made available to the public until November 2017. This assessment is performed for the area of the federal state of Bavaria in Germany and whole Czech Republic using data of the Bavarian agro-meteorological network and the Czech Hydrometeorological Institute. Accuracy indicators are calculated for horizontal global radiation or cloud coverage (depending on data availability from the weather stations) and wind speeds at 10 meters height. While there are important differences between weather stations and cloud coverage data, the results for wind speeds and global solar irradiance are satisfactory for most of the locations. For certain locations widely used indicators such as the Pearson’s correlation coefficient reach values above 0.8 for wind speeds and above 0.9 for global solar irradiance and the mean biased error is consistently lower than 10 W/m2 and can be as low as 0.3 W/m2 for the irradiance data and is, with a few exceptions, lower than 2 m/s in Germany and lower than 1 m/s in the Czech Republic for wind speed data. A total of eight indicators for the hourly data in the period between 1995 and 2015 are calculated, presented, discussed and compared against international literature dealing with data accuracy for solar irradiance and wind speed data sets.

    NachhaltigElektrotechnik und MedientechnikTC Freyung

    Zeitschriftenartikel

    Luis Ramirez Camargo, Wolfgang Dorner, K. Gruber, F. Nitsch

    Electricity self-sufficiency of single-family houses in Germany and the Czech Republic

    Applied Energy, vol. 228, no. 15 October 2018, pp. 902-915

    2018

    DOI: 10.1016/j.apenergy.2018.06.118

    Abstract anzeigen

    Motivated by a research project that studies the future of the energy system in rural areas at the border between Germany and the Czech Republic, and by the publication of the COSMO-REA high-resolution regional reanalysis data sets for Europe in 2017, this study presents a methodology for generating maps indicating minimum battery and photovoltaics sizes for self-sufficient single-family houses. The methodology consists of three subsequent parts: First, spatiotemporal data sets of electricity demand for single-family houses in rural and low-density urban areas are generated. Second, spatiotemporal data sets of photovoltaics potential are computed based on (a) a technical photovoltaics model, (b) two decades of hourly solar irradiance and temperature data, and (c) snow cover data from the Land Surface Analysis Satellite Applications Facility. Third, a linear optimization model serves to define photovoltaics and battery systems sizes and to generate the corresponding maps. The resulting maps cover Germany and the Czech Republic and are generated for 18 technical and weather-dependent scenarios. The results show how challenging it could be to achieve complete independence from the grid in certain locations. Especially relevant for the sizing of the systems are long periods (several days in a row) of low photovoltaic energy generation due to overcast sky conditions or snow cover of the panels. Furthermore, the results offer a scientifically based source of information for sizing photovoltaics and battery systems in the two countries.

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    Vortrag

    Luis Ramirez Camargo, K. Gruber, F. Nitsch

    Assessment of complementarity between wind power and photovoltaic installations to supply residential electric demand in Germany and the Czech Republic

    International Symposium on Regional Reanalysis (ISRR) 2018, Bonn

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    Vortrag

    Luis Ramirez Camargo, Wolfgang Dorner, K. Gruber, F. Nitsch

    Does the mix make the magic? Spatiotemporal modelling to assess residential electricity self-sufficiency based on photovoltaics, wind power and batteries

    AGIT Symposium & Expo 2018 - Angewandte Geoinformatik, Salzburg, Österreich

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    Vortrag

    Luis Ramirez Camargo, Wolfgang Dorner, K. Gruber, F. Nitsch

    Mapping minimum technical requirements for electricity self-sufficiency of single-family houses using regional reanalysis data and satellite imagery derived data

    European Geosciences Union (EGU) General Assembly 2018, Wien, Österreich

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    Vortrag

    Luis Ramirez Camargo, Wolfgang Dorner, K. Gruber, F. Nitsch

    Assessing variables of regional reanalysis data sets relevant for modelling small-scale renewable energy systems

    European Geosciences Union (EGU) General Assembly 2018, Wien, Österreich

    Abstract anzeigen

    Data that allow the characterization of short-term and inter-annual variability of renewable energy resources availability are becoming highly valuable for energy system modellers. Global reanalysis data provide long time series of records without gaps and full spatial coverage at no cost for the final user. However, these exhibit coarse spatial resolution. The COSMO-REA6 and COSMOS-REA2 regional reanalysis for Europe overcome this limitation by increasing the resolution of the reanalysis to six and two kilometres respectively. This work presents an assessment of solar radiation and wind speed variables of these data sets that were available to the public in January 2018. This assessment is performed using data of the Bavarian agro-meteorological network and the Czech Hydrometeorological Institute. Eight accuracy indicators for hourly data in the period 1995–2015 are calculated. Widely used indicators such as the Pearson's correlation coefficient in some cases reach values above 0.82 for wind speeds and above 0.92 for global horizontal irradiance. The mean bias error is consistently better than ± 9.3 W/m2 for the full set of irradiance data, ±25.1 W/m2 for only day-time irradiance data and is, with a few exceptions, lower than ± 1 m/s for the wind speed data.

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    Luis Ramirez Camargo, F. Nitsch

    Maps of Germany and the Czech Republic with photovoltaic and battery system sizes for electricity self-sufficient single-family houses under 18 technical and weather dependent scenarios

    DOI: 10.17632/txvbyxbp9t.1